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All publications at Proceedings of the 32nd International Conference on Machine Learning (ICML-15)
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Low-Rank Matrix Recovery from Row-and-Column Affine Measurements
Avishai Wagner and Or Zuk
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


A Hybrid Approach for Probabilistic Inference using Random Projections
Michael Zhu and Stefano Ermon
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Long Short-Term Memory Over Recursive Structures
Xiaodan Zhu, Parinaz Sobihani and Hongyu Guo
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Towards a Lower Sample Complexity for Robust One-bit Compressed Sensing
Rongda Zhu and Quanquan Gu
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


$\ell_{1,p}$-Norm Regularization: Error Bounds and Convergence Rate Analysis of First-Order Methods
Zirui Zhou, Qi Zhang and Anthony M. So
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Safe Subspace Screening for Nuclear Norm Regularized Least Squares Problems
Qiang Zhou and Qi Zhao
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


On the Relationship between Sum-Product Networks and Bayesian Networks
Han Zhao, Mazen Melibari and Pascal Poupart
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Adaptive Stochastic Alternating Direction Method of Multipliers
Peilin Zhao, Jinwei Yang, Tong Zhang and Ping Li
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Stochastic Optimization with Importance Sampling for Regularized Loss Minimization
Peilin Zhao and Tong Zhang
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Markov Mixed Membership Models
Aonan Zhang and John Paisley
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Distributed Estimation of Generalized Matrix Rank: Efficient Algorithms and Lower Bounds
Yuchen Zhang, Martin Wainwright and Michael Jordan
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


DiSCO: Distributed Optimization for Self-Concordant Empirical Loss
Yuchen Zhang and Xiao Lin
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Stochastic Primal-Dual Coordinate Method for Regularized Empirical Risk Minimization
Yuchen Zhang and Xiao Lin
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Learning Submodular Losses with the Lovasz Hinge
Jiaqian Yu and Matthew Blaschko
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Non-Gaussian Discriminative Factor Models via the Max-Margin Rank-Likelihood
Xin Yuan, Ricardo Henao, Ephraim Tsalik, Raymond Langley and Lawrence Carin
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Accelerated Online Low Rank Tensor Learning for Multivariate Spatiotemporal Streams
Rose Yu, Dehua Cheng and Yan Liu
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Geometric Conditions for Subspace-Sparse Recovery
Chong You and Rene Vidal
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Learning Word Representations with Hierarchical Sparse Coding
Dani Yogatama, Manaal Faruqui, Chris Dyer and Noah Smith
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Binary Embedding: Fundamental Limits and Fast Algorithm
Xinyang Yi, Constantine Caramanis and Eric Price
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


A Convex Exemplar-based Approach to MAD-Bayes Dirichlet Process Mixture Models
En-hsu Yen, Xin Lin, Kai Zhong, Pradeep Ravikumar and Inderjit Dhillon
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Sparse Subspace Clustering with Missing Entries
Congyuan Yang, Daniel Robinson and Rene Vidal
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


A Divide and Conquer Framework for Distributed Graph Clustering
Wenzhuo Yang and Huan Xu
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Streaming Sparse Principal Component Analysis
Wenzhuo Yang and Huan Xu
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


A Unified Framework for Outlier-Robust PCA-like Algorithms
Wenzhuo Yang and Huan Xu
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Theory of Dual-sparse Regularized Randomized Reduction
Tianbao Yang, Lijun Zhang, Rong Jin and Shenghuo Zhu
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


An Explicit Sampling Dependent Spectral Error Bound for Column Subset Selection
Tianbao Yang, Lijun Zhang, Rong Jin and Shenghuo Zhu
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron Courville, Ruslan Salakhudinov, Rich Zemel and Yoshua Bengio
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Deep Edge-Aware Filters
Li Xu, Jimmy Ren, Qiong Yan, Renjie Liao and Jiaya Jia
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


CUR Algorithm for Partially Observed Matrices
Miao Xu, Rong Jin and Zhi-hua Zhou
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Pushing the Limits of Affine Rank Minimization by Adapting Probabilistic PCA
Bo Xin and David Wipf
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Is Feature Selection Secure against Training Data Poisoning?
Huang Xiao, Battista Biggio, Gavin Brown, Giorgio Fumera, Claudia Eckert and Fabio Roli
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


On Identifying Good Options under Combinatorially Structured Feedback in Finite Noisy Environments
Yifan Wu, Andras Gyorgy and Csaba Szepesvari
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


An Online Learning Algorithm for Bilinear Models
Yuanbin Wu and Shiliang Sun
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Inference in a Partially Observed Queuing Model with Applications in Ecology
Kevin Winner, Garrett Bernstein and Dan Sheldon
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Kernel Interpolation for Scalable Structured Gaussian Processes (KISS-GP)
Andrew Wilson and Hannes Nickisch
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Efficient Learning in Large-Scale Combinatorial Semi-Bandits
Zheng Wen, Branislav Kveton and Azin Ashkan
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Learning Parametric-Output HMMs with Two Aliased States
Roi Weiss and Boaz Nadler
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Submodularity in Data Subset Selection and Active Learning
Kai Wei, Rishabh Iyer and Jeff Bilmes
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Privacy for Free: Posterior Sampling and Stochastic Gradient Monte Carlo
Yu-xiang Wang, Stephen Fienberg and Alex Smola
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Safe Screening for Multi-Task Feature Learning with Multiple Data Matrices
Jie Wang and Jieping Ye
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


A Deterministic Analysis of Noisy Sparse Subspace Clustering for Dimensionality-reduced Data
Yining Wang, Yu-xiang Wang and Aarti Singh
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Metadata Dependent Mondrian Processes
Yi Wang, Bin Li, Yang Wang and Fang Chen
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Multi-Task Learning for Subspace Segmentation
Yu Wang, David Wipf, Qing Ling, Wei Chen and Ian Wassell
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


On Deep Multi-View Representation Learning
Weiran Wang, Raman Arora, Karen Livescu and Jeff Bilmes
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


DP-space: Bayesian Nonparametric Subspace Clustering with Small-variance Asymptotics
Yining Wang and Jun Zhu
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Ordinal Mixed Membership Models
Seppo Virtanen and Mark Girolami
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


A Deeper Look at Planning as Learning from Replay
Harm Vanseijen and Rich Sutton
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Low Rank Approximation using Error Correcting Coding Matrices
Shashanka Ubaru, Arya Mazumdar and Yousef Saad
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Efficient Training of LDA on a GPU by Mean-for-Mode Estimation
Jean-baptiste Tristan, Joseph Tassarotti and Guy Steele
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Modeling Order in Neural Word Embeddings at Scale
Andrew Trask, David Gilmore and Matthew Russell
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


High Confidence Policy Improvement
Philip Thomas, Georgios Theocharous and Mohammad Ghavamzadeh
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


A trust-region method for stochastic variational inference with applications to streaming data
Lucas Theis and Matt Hoffman
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Generalization error bounds for learning to rank: Does the length of document lists matter?
Ambuj Tewari and Sougata Chaudhuri
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Vector-Space Markov Random Fields via Exponential Families
Wesley Tansey, Oscar Padilla, Arun S. Suggala and Pradeep Ravikumar
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Learning Scale-Free Networks by Dynamic Node Specific Degree Prior
Qingming Tang, Siqi Sun and Jinbo Xu
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Guaranteed Tensor Decomposition: A Moment Approach
Gongguo Tang and Parikshit Shah
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


On the Rate of Convergence and Error Bounds for LSTD($\lambda$)
Manel Tagorti and Bruno Scherrer
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Qualitative Multi-Armed Bandits: A Quantile-Based Approach
Balazs Szorenyi, Robert Busa-fekete, Paul Weng and Eyke Hüllermeier
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Counterfactual Risk Minimization: Learning from Logged Bandit Feedback
Adith Swaminathan and Thorsten Joachims
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Convergence rate of Bayesian tensor estimator and its minimax optimality
Taiji Suzuki
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Complete Dictionary Recovery Using Nonconvex Optimization
Ju Sun, Qing Qu and John Wright
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Message Passing for Collective Graphical Models
Tao Sun, Dan Sheldon and Akshat Kumar
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Multi-view Sparse Co-clustering via Proximal Alternating Linearized Minimization
Jiangwen Sun, Jin Lu, Tingyang Xu and Jinbo Bi
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Information Geometry and Minimum Description Length Networks
Ke Sun, Jun Wang, Alexandros Kalousis and Stephan Marchand-maillet
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Safe Exploration for Optimization with Gaussian Processes
Yanan Sui, Alkis Gotovos, Joel Burdick and Andreas Krause
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Learning Fast-Mixing Models for Structured Prediction
Jacob Steinhardt and Percy Liang
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Reified Context Models
Jacob Steinhardt and Percy Liang
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Unsupervised Learning of Video Representations using LSTMs
Nitish Srivastava, Elman Mansimov and Ruslan Salakhudinov
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Context-based Unsupervised Data Fusion for Decision Making
Erfan Soltanmohammadi, Mort Naraghi-pour and Mihaela Schaar
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Scalable Bayesian Optimization Using Deep Neural Networks
Jasper Snoek, Oren Rippel, Kevin Swersky, Ryan Kiros, Nadathur Satish, Narayanan Sundaram, Mostofa Patwary, Mr Prabhat and Ryan Adams
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


MRA-based Statistical Learning from Incomplete Rankings
Eric Sibony, Stéphan Clemençon and Jérémie Jakubowicz
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Sparse Variational Inference for Generalized GP Models
Rishit Sheth, Yuyang Wang and Roni Khardon
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


On Greedy Maximization of Entropy
Dravyansh Sharma, Ashish Kapoor and Amit Deshpande
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


A Stochastic PCA and SVD Algorithm with an Exponential Convergence Rate
Ohad Shamir
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Telling cause from effect in deterministic linear dynamical systems
Naji Shajarisales, Dominik Janzing, Bernhard Schoelkopf and Michel Besserve
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


An Empirical Study of Stochastic Variational Inference Algorithms for the Beta Bernoulli Process
Amar Shah, David Knowles and Zoubin Ghahramani
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Approval Voting and Incentives in Crowdsourcing
Nihar Shah, Dengyong Zhou and Yuval Peres
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Entropy evaluation based on confidence intervals of frequency estimates : Application to the learning of decision trees
Mathieu Serrurier and Henri Prade
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Trust Region Policy Optimization
John Schulman, Sergey Levine, Pieter Abbeel, Michael Jordan and Philipp Moritz
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Removing systematic errors for exoplanet search via latent causes
Bernhard Schölkopf, David Hogg, Dun Wang, Dan Foreman-mackey, Dominik Janzing, Carl-johann Simon-gabriel and Jonas Peters
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Universal Value Function Approximators
Tom Schaul, Daniel Horgan, Karol Gregor and David Silver
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Scalable Nonparametric Bayesian Inference on Point Processes with Gaussian Processes
Yves-laurent K. Samo and Stephen Roberts
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Markov Chain Monte Carlo and Variational Inference: Bridging the Gap
Tim Salimans, Diederik Kingma and Max Welling
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Global Convergence of Stochastic Gradient Descent for Some Non-convex Matrix Problems
Christopher D. Sa, Christopher Re and Kunle Olukotun
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Dynamic Sensing: Better Classification under Acquisition Constraints
Oran Richman and Shie Mannor
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Variational Inference with Normalizing Flows
Danilo Rezende and Shakir Mohamed
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Celeste: Variational inference for a generative model of astronomical images
Jeffrey Regier, Andrew Miller, Jon Mcauliffe, Ryan Adams, Matt Hoffman, Dustin Lang, David Schlegel and Mr Prabhat
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Statistical and Algorithmic Perspectives on Randomized Sketching for Ordinary Least-Squares
Garvesh Raskutti and Michael Mahoney
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Convex Calibrated Surrogates for Hierarchical Classification
Harish Ramaswamy, Ambuj Tewari and Shivani Agarwal
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Entropy-Based Concentration Inequalities for Dependent Variables
Liva Ralaivola and Massih-reza Amini
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Ranking from Stochastic Pairwise Preferences: Recovering Condorcet Winners and Tournament Solution Sets at the Top
Arun Rajkumar, Suprovat Ghoshal, Lek-heng Lim and Shivani Agarwal
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Bayesian Multiple Target Localization
Purnima Rajan, Weidong Han, Raphael Sznitman, Peter Frazier and Bruno Jedynak
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Robust Estimation of Transition Matrices in High Dimensional Heavy-tailed Vector Autoregressive Processes
Huitong Qiu, Sheng Xu, Fang Han, Han Liu and Brian Caffo
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Distributional Rank Aggregation, and an Axiomatic Analysis
Adarsh Prasad, Harsh Pareek and Pradeep Ravikumar
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Convex Formulation for Learning from Positive and Unlabeled Data
Marthinus D. Plessis, Gang Niu and Masashi Sugiyama
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Learning Program Embeddings to Propagate Feedback on Student Code
Chris Piech, Jonathan Huang, Andy Nguyen, Mike Phulsuksombati, Mehran Sahami and Leonidas Guibas
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Multi-instance multi-label learning in the presence of novel class instances
Anh Pham, Raviv Raich, Xiaoli Fern and Jesús P. Arriaga
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


A Theoretical Analysis of Metric Hypothesis Transfer Learning
Michaël Perrot and Amaury Habrard
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Approximate Dynamic Programming for Two-Player Zero-Sum Markov Games
Julien Perolat, Bruno Scherrer, Bilal Piot and Olivier Pietquin
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Preference Completion: Large-scale Collaborative Ranking from Pairwise Comparisons
Dohyung Park, Joe Neeman, Jin Zhang, Sujay Sanghavi and Inderjit Dhillon
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Adaptive Belief Propagation
Georgios Papachristoudis and John Fisher
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Proteins, Particles, and Pseudo-Max-Marginals: A Submodular Approach
Jason Pacheco and Erik Sudderth
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Robust partially observable Markov decision process
Takayuki Osogami
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


K-hyperplane Hinge-Minimax Classifier
Margarita Osadchy, Tamir Hazan and Daniel Keren
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Coordinate Descent Converges Faster with the Gauss-Southwell Rule Than Random Selection
Julie Nutini, Mark Schmidt, Issam Laradji, Michael Friedlander and Hoyt Koepke
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Rademacher Observations, Private Data, and Boosting
Richard Nock, Giorgio Patrini and Arik Friedman
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


A General Analysis of the Convergence of ADMM
Robert Nishihara, Laurent Lessard, Ben Recht, Andrew Packard and Michael Jordan
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


On Symmetric and Asymmetric LSHs for Inner Product Search
Behnam Neyshabur and Nathan Srebro
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Alpha-Beta Divergences Discover Micro and Macro Structures in Data
Karthik Narayan, Ali Punjani and Pieter Abbeel
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Consistent Multiclass Algorithms for Complex Performance Measures
Harikrishna Narasimhan, Harish Ramaswamy, Aadirupa Saha and Shivani Agarwal
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Optimizing Non-decomposable Performance Measures: A Tale of Two Classes
Harikrishna Narasimhan, Purushottam Kar and Prateek Jain
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Feature-Budgeted Random Forest
Feng Nan, Joseph Wang and Venkatesh Saligrama
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Nested Sequential Monte Carlo Methods
Christian Naesseth, Fredrik Lindsten and Thomas Schon
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Threshold Influence Model for Allocating Advertising Budgets
Atsushi Miyauchi, Yuni Iwamasa, Takuro Fukunaga and Naonori Kakimura
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Learning from Corrupted Binary Labels via Class-Probability Estimation
Aditya Menon, Brendan V. Rooyen, Cheng S. Ong and Bob Williamson
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Bayesian and Empirical Bayesian Forests
Taddy Matthew, Chun-sheng Chen, Jun Yu and Mitch Wyle
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Optimizing Neural Networks with Kronecker-factored Approximate Curvature
James Martens and Roger Grosse
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Fixed-point algorithms for learning determinantal point processes
Zelda Mariet and Suvrit Sra
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Swept Approximate Message Passing for Sparse Estimation
Andre Manoel, Florent Krzakala, Eric Tramel and Lenka Zdeborovà
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Budget Allocation Problem with Multiple Advertisers: A Game Theoretic View
Takanori Maehara, Akihiro Yabe and Ken-ichi Kawarabayashi
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Gradient-based Hyperparameter Optimization through Reversible Learning
Dougal Maclaurin, David Duvenaud and Ryan Adams
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Controversy in mechanistic modelling with Gaussian processes
Benn Macdonald, Catherine Higham and Dirk Husmeier
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Adding vs. Averaging in Distributed Primal-Dual Optimization
Chenxin Ma, Virginia Smith, Martin Jaggi, Michael Jordan, Peter Richtarik and Martin Takac
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Finding Linear Structure in Large Datasets with Scalable Canonical Correlation Analysis
Zhuang Ma, Yichao Lu and Dean Foster
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Support Matrix Machines
Luo Luo, Yubo Xie, Zhihua Zhang and Wu-jun Li
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Learning Transferable Features with Deep Adaptation Networks
Mingsheng Long, Yue Cao, Jianmin Wang and Michael Jordan
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


The Benefits of Learning with Strongly Convex Approximate Inference
Ben London, Bert Huang and Lise Getoor
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Variational Inference for Gaussian Process Modulated Poisson Processes
Chris Lloyd, Tom Gunter, Michael Osborne and Stephen Roberts
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Bipartite Edge Prediction via Transductive Learning over Product Graphs
Hanxiao Liu and Yiming Yang
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Scalable Model Selection for Large-Scale Factorial Relational Models
Chunchen Liu, Lu Feng, Ryohei Fujimaki and Yusuke Muraoka
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Non-Linear Cross-Domain Collaborative Filtering via Hyper-Structure Transfer
Yan-fu Liu, Cheng-yu Hsu and Shan-hung Wu
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


A Convex Optimization Framework for Bi-Clustering
Shiau H. Lim, Yudong Chen and Huan Xu
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Double Nystr\" om Method: An Efficient and Accurate Nystr\"om Scheme for Large-Scale Data Sets
Woosang Lim, Minhwan Kim, Haesun Park and Kyomin Jung
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Entropic Graph-based Posterior Regularization
Maxwell Libbrecht, Michael Hoffman, Jeff Bilmes and William Noble
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Landmarking Manifolds with Gaussian Processes
Dawen Liang and John Paisley
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


A Multitask Point Process Predictive Model
Wenzhao Lian, Ricardo Henao, Vinayak Rao, Joseph Lucas and Lawrence Carin
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Generative Moment Matching Networks
Yujia Li, Kevin Swersky and Rich Zemel
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Non-Stationary Approximate Modified Policy Iteration
Boris Lesner and Bruno Scherrer
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Hashing for Distributed Data
Cong Leng, Jiaxiang Wu, Jian Cheng, Xi Zhang and Hanqing Lu
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Boosted Categorical Restricted Boltzmann Machine for Computational Prediction of Splice Junctions
Taehoon Lee and Sungroh Yoon
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Distributed Box-Constrained Quadratic Optimization for Dual Linear SVM
Ching-pei Lee and Dan Roth
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Phrase-based Image Captioning
Remi Lebret, Pedro Pinheiro and Ronan Collobert
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Unsupervised Riemannian Metric Learning for Histograms Using Aitchison Transformations
Tam Le and Marco Cuturi
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Improved Regret Bounds for Undiscounted Continuous Reinforcement Learning
K. Lakshmanan, Ronald Ortner and Daniil Ryabko
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Cascading Bandits: Learning to Rank in the Cascade Model
Branislav Kveton, Csaba Szepesvari, Zheng Wen and Azin Ashkan
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


From Word Embeddings To Document Distances
Matt Kusner, Yu Sun, Nicholas Kolkin and Kilian Q. Weinberger
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Differentially Private Bayesian Optimization
Matt Kusner, Jacob Gardner, Roman Garnett and Kilian Q. Weinberger
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Attribute Efficient Linear Regression with Distribution-Dependent Sampling
Doron Kukliansky and Ohad Shamir
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


The Hedge Algorithm on a Continuum
Walid Krichene, Maximilian Balandat, Claire Tomlin and Alexandre Bayen
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


On TD(0) with function approximation: Concentration bounds and a centered variant with exponential convergence
Nathaniel Korda and Prashanth La
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Optimal Regret Analysis of Thompson Sampling in Stochastic Multi-armed Bandit Problem with Multiple Plays
Junpei Komiyama, Junya Honda and Hiroshi Nakagawa
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Manifold-valued Dirichlet Processes
Hyunwoo Kim, Jia Xu, Baba Vemuri and Vikas Singh
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Surrogate Functions for Maximizing Precision at the Top
Purushottam Kar, Harikrishna Narasimhan and Prateek Jain
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Asymmetric Transfer Learning with Deep Gaussian Processes
Melih Kandemir
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


High Dimensional Bayesian Optimisation and Bandits via Additive Models
Kirthevasan Kandasamy, Jeff Schneider and Barnabas Poczos
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


The Composition Theorem for Differential Privacy
Peter Kairouz, Sewoong Oh and Pramod Viswanath
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


An Empirical Exploration of Recurrent Network Architectures
Rafal Jozefowicz, Wojciech Zaremba and Ilya Sutskever
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Blitz: A Principled Meta-Algorithm for Scaling Sparse Optimization
Tyler Johnson and Carlos Guestrin
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


The Kendall and Mallows Kernels for Permutations
Yunlong Jiao and Jean-philippe Vert
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Abstraction Selection in Model-based Reinforcement Learning
Nan Jiang, Alex Kulesza and Satinder Singh
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Atomic Spatial Processes
Sean Jewell, Neil Spencer and Alexandre Bouchard-côté
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


A Fast Variational Approach for Learning Markov Random Field Language Models
Yacine Jernite, Alexander Rush and David Sontag
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Faster cover trees
Mike Izbicki and Christian Shelton
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Sergey Ioffe and Christian Szegedy
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Risk and Regret of Hierarchical Bayesian Learners
Jonathan Huggins and Josh Tenenbaum
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


JUMP-Means: Small-Variance Asymptotics for Markov Jump Processes
Jonathan Huggins, Karthik Narasimhan, Ardavan Saeedi and Vikash Mansinghka
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Deterministic Independent Component Analysis
Ruitong Huang, Andras Gyorgy and Csaba Szepesvári
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Log-Euclidean Metric Learning on Symmetric Positive Definite Manifold with Application to Image Set Classification
Zhiwu Huang, Ruiping Wang, Shiguang Shan, Xianqiu Li and Xilin Chen
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Large-scale Distributed Dependent Nonparametric Trees
Zhiting Hu, Ho Qirong, Avinava Dubey and Eric Xing
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


PU Learning for Matrix Completion
Cho-jui Hsieh, Nagarajan Natarajan and Inderjit Dhillon
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


PASSCoDe: Parallel ASynchronous Stochastic dual Co-ordinate Descent
Cho-jui Hsieh, Hsiang-fu Yu and Inderjit Dhillon
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Online Tracking by Learning Discriminative Saliency Map with Convolutional Neural Network
Seunghoon Hong, Tackgeun You, Suha Kwak and Bohyung Han
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


PeakSeg: constrained optimal segmentation and supervised penalty learning for peak detection in count data
Toby Hocking, Guillem Rigaill and Guillaume Bourque
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


A Unifying Framework of Anytime Sparse Gaussian Process Regression Models with Stochastic Variational Inference for Big Data
Trong N. Hoang, Quang M. Hoang and Bryan Low
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Fictitious Self-Play in Extensive-Form Games
Johannes Heinrich, Marc Lanctot and David Silver
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


A Nearly-Linear Time Framework for Graph-Structured Sparsity
Chinmay Hegde, Piotr Indyk and Ludwig Schmidt
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


HawkesTopic: A Joint Model for Network Inference and Topic Modeling from Text-Based Cascades
Xinran He, Theodoros Rekatsinas, James Foulds, Lise Getoor and Yan Liu
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Classification with Low Rank and Missing Data
Elad Hazan, Roi Livni and Yishay Mansour
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Rebuilding Factorized Information Criterion: Asymptotically Accurate Marginal Likelihood
Kohei Hayashi, Shin-ichi Maeda and Ryohei Fujimaki
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Consistent estimation of dynamic and multi-layer block models
Qiuyi Han, Kevin Xu and Edoardo Airoldi
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Cheap Bandits
Manjesh Hanawal, Venkatesh Saligrama, Michal Valko and Remi Munos
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Large-scale log-determinant computation through stochastic Chebyshev expansions
Insu Han, Dmitry Malioutov and Jinwoo Shin
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Off-policy Model-based Learning under Unknown Factored Dynamics
Assaf Hallak, Francois Schnitzler, Timothy Mann and Shie Mannor
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Deep Learning with Limited Numerical Precision
Suyog Gupta, Ankur Agrawal, Kailash Gopalakrishnan and Pritish Narayanan
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Moderated and Drifting Linear Dynamical Systems
Jinyan Guan, Kyle Simek, Ernesto Brau, Clayton Morrison, Emily Butler and Kobus Barnard
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


A New Generalized Error Path Algorithm for Model Selection
Bin Gu and Charles Ling
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Scaling up Natural Gradient by Sparsely Factorizing the Inverse Fisher Matrix
Roger Grosse and Ruslan Salakhudinov
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


DRAW: A Recurrent Neural Network For Image Generation
Karol Gregor, Ivo Danihelka, Alex Graves, Danilo Rezende and Daan Wierstra
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


BilBOWA: Fast Bilingual Distributed Representations without Word Alignments
Stephan Gouws, Yoshua Bengio and Greg Corrado
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Discovering Temporal Causal Relations from Subsampled Data
Mingming Gong, Kun Zhang, Bernhard Schoelkopf, Dacheng Tao and Philipp Geiger
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


A Modified Orthant-Wise Limited Memory Quasi-Newton Method with Convergence Analysis
Pinghua Gong and Jieping Ye
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Hidden Markov Anomaly Detection
Nico Goernitz, Mikio Braun and Marius Kloft
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


How Hard is Inference for Structured Prediction?
Amir Globerson, Tim Roughgarden, David Sontag and Cafer Yildirim
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Algorithms for the Hard Pre-Image Problem of String Kernels and the General Problem of String Prediction
Sébastien Giguère, Amélie Rolland, Francois Laviolette and Mario Marchand
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


A Provable Generalized Tensor Spectral Method for Uniform Hypergraph Partitioning
Debarghya Ghoshdastidar and Ambedkar Dukkipati
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


MADE: Masked Autoencoder for Distribution Estimation
Mathieu Germain, Karol Gregor, Iain Murray and Hugo Larochelle
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Causal Inference by Identification of Vector Autoregressive Processes with Hidden Components
Philipp Geiger, Kun Zhang, Bernhard Schoelkopf, Mingming Gong and Dominik Janzing
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Intersecting Faces: Non-negative Matrix Factorization With New Guarantees
Rong Ge and James Zou
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Distributed Inference for Dirichlet Process Mixture Models
Hong Ge, Yutian Chen, Moquan Wan and Zoubin Ghahramani
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


On the Optimality of Multi-Label Classification under Subset Zero-One Loss for Distributions Satisfying the Composition Property
Maxime Gasse, Alexandre Aussem and Haytham Elghazel
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Finding Galaxies in the Shadows of Quasars with Gaussian Processes
Roman Garnett, Shirley Ho and Jeff Schneider
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Online Learning of Eigenvectors
Dan Garber, Elad Hazan and Tengyu Ma
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Faster Rates for the Frank-Wolfe Method over Strongly-Convex Sets
Dan Garber and Elad Hazan
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Unsupervised Domain Adaptation by Backpropagation
Yaroslav Ganin and Victor Lempitsky
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Scalable Deep Poisson Factor Analysis for Topic Modeling
Zhe Gan, Changyou Chen, Ricardo Henao, David Carlson and Lawrence Carin
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Improving the Gaussian Process Sparse Spectrum Approximation by Representing Uncertainty in Frequency Inputs
Yarin Gal and Richard Turner
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Latent Gaussian Processes for Distribution Estimation of Multivariate Categorical Data
Yarin Gal, Yutian Chen and Zoubin Ghahramani
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


A Relative Exponential Weighing Algorithm for Adversarial Utility-based Dueling Bandits
Pratik Gajane, Tanguy Urvoy and Fabrice Clérot
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Un-regularizing: approximate proximal point and faster stochastic algorithms for empirical risk minimization
Roy Frostig, Rong Ge, Sham Kakade and Aaron Sidford
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Latent Topic Networks: A Versatile Probabilistic Programming Framework for Topic Models
James Foulds, Shachi Kumar and Lise Getoor
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Fast Kronecker Inference in Gaussian Processes with non-Gaussian Likelihoods
Seth Flaxman, Andrew Wilson, Daniel Neill, Hannes Nickisch and Alex Smola
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Enabling scalable stochastic gradient-based inference for Gaussian processes by employing the Unbiased LInear System SolvEr (ULISSE)
Maurizio Filippone and Raphael Engler
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Learning Local Invariant Mahalanobis Distances
Ethan Fetaya and Shimon Ullman
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Mind the duality gap: safer rules for the Lasso
Olivier Fercoq, Alexandre Gramfort and Joseph Salmon
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Random Coordinate Descent Methods for Minimizing Decomposable Submodular Functions
Alina Ene and Huy Nguyen
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Dealing with small data: On the generalization of context trees
Ralf Eggeling, Mikko Koivisto and Ivo Grosse
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Scalable Variational Inference in Log-supermodular Models
Josip Djolonga and Andreas Krause
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Yinyang K-Means: A Drop-In Replacement of the Classic K-Means with Consistent Speedup
Yufei Ding, Yue Zhao, Xipeng Shen, Madanlal Musuvathi and Todd Mytkowicz
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Distributed Gaussian Processes
Marc Deisenroth and Jun W. Ng
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Ordered Stick-Breaking Prior for Sequential MCMC Inference of Bayesian Nonparametric Models
Mrinal Das, Trapit Bansal and Chiranjib Bhattacharyya
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Strongly Adaptive Online Learning
Amit Daniely, Alon Gonen and Shai Shalev-shwartz
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Stochastic Dual Coordinate Ascent with Adaptive Probabilities
Dominik Csiba, Zheng Qu and Peter Richtarik
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Structural Maxent Models
Corinna Cortes, Vitaly Kuznetsov, Mehryar Mohri and Umar Syed
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Harmonic Exponential Families on Manifolds
Taco Cohen and Max Welling
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Following the Perturbed Leader for Online Structured Learning
Alon Cohen and Tamir Hazan
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Training Deep Convolutional Neural Networks to Play Go
Christopher Clark and Amos Storkey
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Convex Learning of Multiple Tasks and their Structure
Carlo Ciliberto, Youssef Mroueh, Tomaso Poggio and Lorenzo Rosasco
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Gated Feedback Recurrent Neural Networks
Junyoung Chung, Caglar Gulcehre, Kyunghyun Cho and Yoshua Bengio
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Compressing Neural Networks with the Hashing Trick
Wenlin Chen, James Wilson, Stephen Tyree, Kilian Q. Weinberger and Yixin Chen
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Learning Deep Structured Models
Liang-chieh Chen, Alexander Schwing, Alan Yuille and Raquel Urtasun
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Spectral MLE: Top-K Rank Aggregation from Pairwise Comparisons
Yuxin Chen and Changho Suh
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Subsampling Methods for Persistent Homology
Frederic Chazal, Brittany Fasy, Fabrizio Lecci, Bertrand Michel, Alessandro Rinaldo and Larry Wasserman
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Exponential Integration for Hamiltonian Monte Carlo
Wei-lun Chao, Justin Solomon, Dominik Michels and Fei Sha
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Learning to Search Better than Your Teacher
Kai-wei Chang, Akshay Krishnamurthy, Alekh Agarwal, Hal Daume and John Langford
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Complex Event Detection using Semantic Saliency and Nearly-Isotonic SVM
Xiaojun Chang, Yi Yang, Eric Xing and Yaoliang Yu
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Simple regret for infinitely many armed bandits
Alexandra Carpentier and Michal Valko
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Spectral Clustering via the Power Method - Provably
Christos Boutsidis, Prabhanjan Kambadur and Alex Gittens
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


A low variance consistent test of relative dependency
Wacha Bounliphone, Arthur Gretton, Arthur Tenenhaus and Matthew Blaschko
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Weight Uncertainty in Neural Network
Charles Blundell, Julien Cornebise, Koray Kavukcuoglu and Daan Wierstra
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


The Ladder: A Reliable Leaderboard for Machine Learning Competitions
Avrim Blum and Moritz Hardt
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Tracking Approximate Solutions of Parameterized Optimization Problems over Multi-Dimensional (Hyper-)Parameter Domains
Katharina Blechschmidt, Joachim Giesen and Soeren Laue
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Optimal and Adaptive Algorithms for Online Boosting
Alina Beygelzimer, Satyen Kale and Haipeng Luo
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


The Fundamental Incompatibility of Scalable Hamiltonian Monte Carlo and Naive Data Subsampling
Michael Betancourt
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Active Nearest Neighbors in Changing Environments
Christopher Berlind and Ruth Urner
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


A Bayesian nonparametric procedure for comparing algorithms
Alessio Benavoli, Giorgio Corani, Francesca Mangili and Marco Zaffalon
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


A Linear Dynamical System Model for Text
David Belanger and Sham Kakade
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


The Power of Randomization: Distributed Submodular Maximization on Massive Datasets
Rafael Barbosa, Alina Ene, Huy Nguyen and Justin Ward
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


An Aligned Subtree Kernel for Weighted Graphs
Lu Bai, Luca Rossi, Zhihong Zhang and Edwin Hancock
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Functional Subspace Clustering with Application to Time Series
Mohammad T. Bahadori, David Kale, Yingying Fan and Yan Liu
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Variational Generative Stochastic Networks with Collaborative Shaping
Philip Bachman and Doina Precup
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Coresets for Nonparametric Estimation - the Case of DP-Means
Olivier Bachem, Mario Lucic and Andreas Krause
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs
Stephen Bach, Bert Huang, Jordan Boyd-graber and Lise Getoor
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


An Asynchronous Distributed Proximal Gradient Method for Composite Convex Optimization
Necdet Aybat, Zi Wang and Garud Iyengar
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Community Detection Using Time-Dependent Personalized PageRank
Haim Avron and Lior Horesh
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Stay on path: PCA along graph paths
Megasthenis Asteris, Anastasios Kyrillidis, Alex Dimakis, Han-gyol Yi and Bharath Chandrasekaran
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Online Time Series Prediction with Missing Data
Oren Anava, Elad Hazan and Assaf Zeevi
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


How Can Deep Rectifier Networks Achieve Linear Separability and Preserve Distances?
Senjian An, Farid Boussaid and Mohammed Bennamoun
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Safe Policy Search for Lifelong Reinforcement Learning with Sublinear Regret
Haitham B. Ammar, Rasul Tutunov and Eric Eaton
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Multiview Triplet Embedding: Learning Attributes in Multiple Maps
Ehsan Amid and Antti Ukkonen
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Bimodal Modelling of Source Code and Natural Language
Miltos Allamanis, Daniel Tarlow, Andrew Gordon and Yi Wei
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Correlation Clustering in Data Streams
Kookjin Ahn, Graham Cormode, Sudipto Guha, Andrew Mcgregor and Anthony Wirth
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


A Lower Bound for the Optimization of Finite Sums
Alekh Agarwal and Leon Bottou
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015