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All publications by Cho-jui Hsieh
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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


Matrix Completion with Noisy Side Information
Kai-yang Chiang, Cho-jui Hsieh and Inderjit S. Dhillon
Advances in Neural Information Processing Systems 28, 2015


Sparse Linear Programming via Primal and Dual Augmented Coordinate Descent
Ian E. Yen, Kai Zhong, Cho-jui Hsieh, Pradeep K. Ravikumar and Inderjit S. Dhillon
Advances in Neural Information Processing Systems 28, 2015


Memory Efficient Kernel Approximation
Si Si, Cho-jui Hsieh and Inderjit Dhillon
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


Nuclear Norm Minimization via Active Subspace Selection
Cho-jui Hsieh and Peder Olsen
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


A Divide-and-Conquer Solver for Kernel Support Vector Machines
Cho-jui Hsieh, Si Si and Inderjit Dhillon
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


QUIC \& DIRTY: A Quadratic Approximation Approach for Dirty Statistical Models
Cho-jui Hsieh, Inderjit S. Dhillon, Pradeep K. Ravikumar, Stephen Becker and Peder A. Olsen
Advances in Neural Information Processing Systems 27, 2014


Fast Prediction for Large-Scale Kernel Machines
Cho-jui Hsieh, Si Si and Inderjit S. Dhillon
Advances in Neural Information Processing Systems 27, 2014


Constant Nullspace Strong Convexity and Fast Convergence of Proximal Methods under High-Dimensional Settings
En-hsu Yen, Cho-jui Hsieh, Pradeep K. Ravikumar and Inderjit S. Dhillon
Advances in Neural Information Processing Systems 27, 2014


Large Scale Distributed Sparse Precision Estimation
Huahua Wang, Arindam Banerjee, Cho-jui Hsieh, Pradeep Ravikumar and Inderjit Dhillon
Advances in Neural Information Processing Systems 26, 2013


BIG \& QUIC: Sparse Inverse Covariance Estimation for a Million Variables
Cho-jui Hsieh, Matyas A. Sustik, Inderjit Dhillon, Pradeep Ravikumar and Russell Poldrack
Advances in Neural Information Processing Systems 26, 2013


A Divide-and-Conquer Method for Sparse Inverse Covariance Estimation
Cho-jui Hsieh, Arindam Banerjee, Inderjit S. Dhillon and Pradeep K. Ravikumar
Advances in Neural Information Processing Systems 25, 2012


Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation
Cho-jui Hsieh, Inderjit S. Dhillon, Pradeep K. Ravikumar and Mátyás A. Sustik
Advances in Neural Information Processing Systems 24, 2011


A dual coordinate descent method for large-scale linear SVM
Cho-jui Hsieh, Kai-wei Chang, Chih-jen Lin, S. S. Keerthi and S. Sundararajan
Proceedings of the 25th International Conference on Machine Learning (ICML-08), 2008


LIBLINEAR: A Library for Large Linear Classification
Rong-en Fan, Kai-wei Chang, Cho-jui Hsieh, Xiang-rui Wang and Chih-jen Lin
Journal of Machine Learning Research, 2008


Coordinate Descent Method for Large-scale L2-loss Linear Support Vector Machines
Kai-wei Chang, Cho-jui Hsieh and Chih-jen Lin
Journal of Machine Learning Research, 2008