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All publications by Daphne Koller
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Shifting Weights: Adapting Object Detectors from Image to Video
Kevin Tang, Vignesh Ramanathan, Li Fei-fei and Daphne Koller
Advances in Neural Information Processing Systems 25, 2012


Modeling Latent Variable Uncertainty for Loss-based Learning
M. P. Kumar, Ben Packer and Daphne Koller
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Max-Margin Min-Entropy Models
Kevin Miller, M. P. Kumar, Benjamin Packer, Danny Goodman and Daphne Koller
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS-12), 2012


Active Classification based on Value of Classifier
Tianshi Gao and Daphne Koller
Advances in Neural Information Processing Systems 24, 2011


Multiclass Boosting with Hinge Loss based on Output Coding
Tianshi Gao and Daphne Koller
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011


Convex envelopes of complexity controlling penalties: the case against premature envelopment
Vladimir Jojic, Suchi Saria and Daphne Koller
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS-11), 2011


Non-Local Contrastive Objectives
David Vickrey, Cliff C. Lin and Daphne Koller
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Accelerated dual decomposition for MAP inference
Vladimir Jojic, Stephen Gould and Daphne Koller
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Self-Paced Learning for Latent Variable Models
M. P. Kumar, Benjamin Packer and Daphne Koller
Advances in Neural Information Processing Systems 23, 2010


Learning a Small Mixture of Trees
M. P. Kumar and Daphne Koller
Advances in Neural Information Processing Systems 22, 2009


Region-based Segmentation and Object Detection
Stephen Gould, Tianshi Gao and Daphne Koller
Advances in Neural Information Processing Systems 22, 2009


Max-margin Classification of Data with Absent Features
Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbeel and Daphne Koller
Journal of Machine Learning Research, 2008


Shape-Based Object Localization for Descriptive Classification
Geremy Heitz, Gal Elidan, Benjamin Packer and Daphne Koller
Advances in Neural Information Processing Systems 21, 2008


Cascaded Classification Models: Combining Models for Holistic Scene Understanding
Geremy Heitz, Stephen Gould, Ashutosh Saxena and Daphne Koller
Advances in Neural Information Processing Systems 21, 2008


Learning a meta-level prior for feature relevance from multiple related tasks
Su-in Lee, Vassil Chatalbashev, David Vickrey and Daphne Koller
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Constructing informative priors using transfer learning
Rajat Raina, Andrew Y. Ng and Daphne Koller
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006


Using Combinatorial Optimization within Max-Product Belief Propagation
Daniel Tarlow, Gal Elidan, Daphne Koller and John C. Duchi
Advances in Neural Information Processing Systems 19, 2006


Efficient Structure Learning of Markov Networks using $L_1$-Regularization
Su-in Lee, Varun Ganapathi and Daphne Koller
Advances in Neural Information Processing Systems 19, 2006


Temporal and Cross-Subject Probabilistic Models for fMRI Prediction Tasks
Alexis Battle, Gal Chechik and Daphne Koller
Advances in Neural Information Processing Systems 19, 2006


Max-margin classification of incomplete data
Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbeel and Daphne Koller
Advances in Neural Information Processing Systems 19, 2006


Learning Factor Graphs in Polynomial Time and Sample Complexity
Pieter Abbeel, Daphne Koller and Andrew Y. Ng
Journal of Machine Learning Research, 2006


Learning structured prediction models: a large margin approach
Vassil Chatalbashev, Daphne Koller, Carlos Guestrin and Ben Taskar
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Learning Module Networks
Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller and Nir Friedman
Journal of Machine Learning Research, 2005


Learning associative Markov networks
Vassil Chatalbashev, Daphne Koller and Ben Taskar
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Identifying Protein-Protein Interaction Sites on a Genome-Wide Scale
Haidong Wang, Eran Segal, Asa Ben-hur, Daphne Koller and Douglas L. Brutlag
Advances in Neural Information Processing Systems 17, 2004


The Correlated Correspondence Algorithm for Unsupervised Registration of Nonrigid Surfaces
Dragomir Anguelov, Praveen Srinivasan, Hoi-cheung Pang, Daphne Koller, Sebastian Thrun and James Davis
Advances in Neural Information Processing Systems 17, 2004


Learning on the Test Data: Leveraging Unseen Features
Ming F. Wong, Daphne Koller and Ben Taskar
Proceedings of the 20th International Conference on Machine Learning (ICML-03), 2003


Link Prediction in Relational Data
Ben Taskar, Ming-fai Wong, Pieter Abbeel and Daphne Koller
Advances in Neural Information Processing Systems 16, 2003


Max-Margin Markov Networks
Ben Taskar, Carlos Guestrin and Daphne Koller
Advances in Neural Information Processing Systems 16, 2003


Learning Probabilistic Models of Link Structure
Lise Getoor, Nir Friedman, Daphne Koller and Benjamin Taskar
Journal of Machine Learning Research, 2002


Probabilistic Abstraction Hierarchies
Eran Segal, Daphne Koller and Dirk Ormoneit
Advances in Neural Information Processing Systems 14, 2001


Support Vector Machine Active Learning with Applications to Text Classification
Simon Tong and Daphne Koller
Journal of Machine Learning Research, 2001