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All publications by Michael Jordan
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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


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


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


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


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


Efficient Ranking from Pairwise Comparisons
Fabian Wauthier, Michael Jordan and Nebojsa Jojic
Proceedings of the 30th International Conference on Machine Learning (ICML-13), 2013


MAD-Bayes: MAP-based Asymptotic Derivations from Bayes
Tamara Broderick, Brian Kulis and Michael Jordan
Proceedings of the 30th International Conference on Machine Learning (ICML-13), 2013


A Comparative Framework for Preconditioned Lasso Algorithms
Fabian L. Wauthier, Nebojsa Jojic and Michael Jordan
Advances in Neural Information Processing Systems 26, 2013


Optimistic Concurrency Control for Distributed Unsupervised Learning
Xinghao Pan, Joseph E. Gonzalez, Stefanie Jegelka, Tamara Broderick and Michael Jordan
Advances in Neural Information Processing Systems 26, 2013


Local Privacy and Minimax Bounds: Sharp Rates for Probability Estimation
John Duchi, Martin J. Wainwright and Michael Jordan
Advances in Neural Information Processing Systems 26, 2013


Streaming Variational Bayes
Tamara Broderick, Nicholas Boyd, Andre Wibisono, Ashia C. Wilson and Michael Jordan
Advances in Neural Information Processing Systems 26, 2013


Estimation, Optimization, and Parallelism when Data is Sparse
John Duchi, Michael Jordan and Brendan Mcmahan
Advances in Neural Information Processing Systems 26, 2013


Information-theoretic lower bounds for distributed statistical estimation with communication constraints
Yuchen Zhang, John Duchi, Michael Jordan and Martin J. Wainwright
Advances in Neural Information Processing Systems 26, 2013