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• 2008 Spotlight: Efficient Inference in Phylogenetic InDel Trees »
  Tue. Dec 9th 04:32 -- 04:33 AM Room

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• 2021 : Optimization with Adaptive Step Size Selection from a Dynamical Systems Perspective »
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• 2021 : Last-Iterate Convergence of Saddle Point Optimizers via High-Resolution Differential Equations »
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• 2021 : Language, Context, and Action: A Semantic Machines View of Conversational AI »
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• 2021 Poster: Wasserstein Flow Meets Replicator Dynamics: A Mean-Field Analysis of Representation Learning in Actor-Critic »
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• 2021 Poster: Tactical Optimism and Pessimism for Deep Reinforcement Learning »
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• 2021 Poster: Learning Space Partitions for Path Planning »
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• 2020 : Contributed Talk 6: Do Offline Metrics Predict Online Performance in Recommender Systems? »
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• 2020 Poster: Projection Robust Wasserstein Distance and Riemannian Optimization »
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• 2020 Poster: Fixed-Support Wasserstein Barycenters: Computational Hardness and Fast Algorithm »
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• 2020 Spotlight: Projection Robust Wasserstein Distance and Riemannian Optimization »
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• 2020 Poster: Decision-Making with Auto-Encoding Variational Bayes »
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• 2020 Poster: Transferable Calibration with Lower Bias and Variance in Domain Adaptation »
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• 2020 Poster: Robust Optimization for Fairness with Noisy Protected Groups »
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• 2020 Poster: On the Theory of Transfer Learning: The Importance of Task Diversity »
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• 2020 Poster: On Function Approximation in Reinforcement Learning: Optimism in the Face of Large State Spaces »
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• 2019 : Poster and Coffee Break 2 »
  Karol Hausman · Kefan Dong · Ken Goldberg · Lihong Li · Lin Yang · Lingxiao Wang · Lior Shani · Liwei Wang · Loren Amdahl-Culleton · Lucas Cassano · Marc Dymetman · Marc Bellemare · Marcin Tomczak · Margarita Castro · Marius Kloft · Marius-Constantin Dinu · Markus Holzleitner · Martha White · Mengdi Wang · Michael Jordan · Mihailo Jovanovic · Ming Yu · Minshuo Chen · Moonkyung Ryu · Muhammad Zaheer · Naman Agarwal · Nan Jiang · Niao He · Nikolaus Yasui · Nikos Karampatziakis · Nino Vieillard · Ofir Nachum · Olivier Pietquin · Ozan Sener · Pan Xu · Parameswaran Kamalaruban · Paul Mineiro · Paul Rolland · Philip Amortila · Pierre-Luc Bacon · Prakash Panangaden · Qi Cai · Qiang Liu · Quanquan Gu · Raihan Seraj · Richard Sutton · Rick Valenzano · Robert Dadashi · Rodrigo Toro Icarte · Roshan Shariff · Roy Fox · Ruosong Wang · Saeed Ghadimi · Samuel Sokota · Sean Sinclair · Sepp Hochreiter · Sergey Levine · Sergio Valcarcel Macua · Sham Kakade · Shangtong Zhang · Sheila McIlraith · Shie Mannor · Shimon Whiteson · Shuai Li · Shuang Qiu · Wai Lok Li · Siddhartha Banerjee · Sitao Luan · Tamer Basar · Thinh Doan · Tianhe Yu · Tianyi Liu · Tom Zahavy · Toryn Klassen · Tuo Zhao · Vicenç Gómez · Vincent Liu · Volkan Cevher · Wesley Suttle · Xiao-Wen Chang · Xiaohan Wei · Xiaotong Liu · Xingguo Li · Xinyi Chen · Xingyou Song · Yao Liu · YiDing Jiang · Yihao Feng · Yilun Du · Yinlam Chow · Yinyu Ye · Yishay Mansour · · Yonathan Efroni · Yongxin Chen · Yuanhao Wang · Bo Dai · Chen-Yu Wei · Harsh Shrivastava · Hongyang Zhang · Qinqing Zheng · SIDDHARTHA SATPATHI · Xueqing Liu · Andreu Vall
• 2019 Poster: Transferable Normalization: Towards Improving Transferability of Deep Neural Networks »
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• 2019 Poster: Acceleration via Symplectic Discretization of High-Resolution Differential Equations »
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• 2018 Poster: Gen-Oja: Simple & Efficient Algorithm for Streaming Generalized Eigenvector Computation »
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• 2018 Poster: Theoretical guarantees for EM under misspecified Gaussian mixture models »
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• 2018 Poster: Stochastic Cubic Regularization for Fast Nonconvex Optimization »
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• 2018 Poster: On the Local Minima of the Empirical Risk »
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• 2018 Spotlight: On the Local Minima of the Empirical Risk »
  Chi Jin · Lydia T. Liu · Rong Ge · Michael Jordan
• 2018 Oral: Stochastic Cubic Regularization for Fast Nonconvex Optimization »
  Nilesh Tripuraneni · Mitchell Stern · Chi Jin · Jeffrey Regier · Michael Jordan
• 2018 Poster: Is Q-Learning Provably Efficient? »
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• 2018 Poster: Speaker-Follower Models for Vision-and-Language Navigation »
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• 2018 Poster: Information Constraints on Auto-Encoding Variational Bayes »
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• 2018 Poster: Conditional Adversarial Domain Adaptation »
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• 2018 Poster: Generalized Zero-Shot Learning with Deep Calibration Network »
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• 2017 Poster: Fast Black-box Variational Inference through Stochastic Trust-Region Optimization »
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• 2017 Poster: Online control of the false discovery rate with decaying memory »
  Aaditya Ramdas · Fanny Yang · Martin Wainwright · Michael Jordan
• 2017 Spotlight: Fast Black-box Variational Inference through Stochastic Trust-Region Optimization »
  Jeffrey Regier · Michael Jordan · Jon McAuliffe
• 2017 Oral: Online control of the false discovery rate with decaying memory »
  Aaditya Ramdas · Fanny Yang · Martin Wainwright · Michael Jordan
• 2017 Poster: Gradient Descent Can Take Exponential Time to Escape Saddle Points »
  Simon Du · Chi Jin · Jason D Lee · Michael Jordan · Aarti Singh · Barnabas Poczos
• 2017 Spotlight: Gradient Descent Can Take Exponential Time to Escape Saddle Points »
  Simon Du · Chi Jin · Jason D Lee · Michael Jordan · Aarti Singh · Barnabas Poczos
• 2017 Poster: Non-convex Finite-Sum Optimization Via SCSG Methods »
  Lihua Lei · Cheng Ju · Jianbo Chen · Michael Jordan
• 2017 Poster: Kernel Feature Selection via Conditional Covariance Minimization »
  Jianbo Chen · Mitchell Stern · Martin J Wainwright · Michael Jordan
• 2016 Workshop: Advances in Approximate Bayesian Inference »
  Tamara Broderick · Stephan Mandt · James McInerney · Dustin Tran · David Blei · Kevin Murphy · Andrew Gelman · Michael I Jordan
• 2016 Poster: Cyclades: Conflict-free Asynchronous Machine Learning »
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• 2016 Poster: Unsupervised Domain Adaptation with Residual Transfer Networks »
  Mingsheng Long · Han Zhu · Jianmin Wang · Michael Jordan
• 2016 Poster: Local Maxima in the Likelihood of Gaussian Mixture Models: Structural Results and Algorithmic Consequences »
  Chi Jin · Yuchen Zhang · Sivaraman Balakrishnan · Martin J Wainwright · Michael Jordan
• 2015 Poster: Variational Consensus Monte Carlo »
  Maxim Rabinovich · Elaine Angelino · Michael Jordan
• 2015 Poster: On the Accuracy of Self-Normalized Log-Linear Models »
  Jacob Andreas · Maxim Rabinovich · Michael Jordan · Dan Klein
• 2015 Poster: Linear Response Methods for Accurate Covariance Estimates from Mean Field Variational Bayes »
  Ryan Giordano · Tamara Broderick · Michael Jordan
• 2015 Spotlight: Linear Response Methods for Accurate Covariance Estimates from Mean Field Variational Bayes »
  Ryan Giordano · Tamara Broderick · Michael Jordan
• 2014 Workshop: Advances in Variational Inference »
  David Blei · Shakir Mohamed · Michael Jordan · Charles Blundell · Tamara Broderick · Matthew D. Hoffman
• 2014 Poster: Communication-Efficient Distributed Dual Coordinate Ascent »
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• 2014 Poster: Spectral Methods meet EM: A Provably Optimal Algorithm for Crowdsourcing »
  Yuchen Zhang · Xi Chen · Denny Zhou · Michael Jordan
• 2014 Poster: Unsupervised Transcription of Piano Music »
  Taylor Berg-Kirkpatrick · Jacob Andreas · Dan Klein
• 2014 Poster: Parallel Double Greedy Submodular Maximization »
  Xinghao Pan · Stefanie Jegelka · Joseph Gonzalez · Joseph K Bradley · Michael Jordan
• 2014 Demonstration: Unsupervised Transcription of Piano Music »
  Taylor Berg-Kirkpatrick · Jacob Andreas · Dan Klein
• 2014 Spotlight: Spectral Methods meet EM: A Provably Optimal Algorithm for Crowdsourcing »
  Yuchen Zhang · Xi Chen · Denny Zhou · Michael Jordan
• 2014 Spotlight: Unsupervised Transcription of Piano Music »
  Taylor Berg-Kirkpatrick · Jacob Andreas · Dan Klein
• 2014 Poster: On the Convergence Rate of Decomposable Submodular Function Minimization »
  Robert Nishihara · Stefanie Jegelka · Michael Jordan
• 2013 Workshop: Big Learning : Advances in Algorithms and Data Management »
  Xinghao Pan · Haijie Gu · Joseph Gonzalez · Sameer Singh · Yucheng Low · Joseph Hellerstein · Derek G Murray · Raghu Ramakrishnan · Michael Jordan · Christopher Ré
• 2013 Workshop: Discrete Optimization in Machine Learning: Connecting Theory and Practice »
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• 2013 Session: Oral Session 10 »
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• 2013 Poster: A Comparative Framework for Preconditioned Lasso Algorithms »
  Fabian L Wauthier · Nebojsa Jojic · Michael Jordan
• 2013 Poster: Information-theoretic lower bounds for distributed statistical estimation with communication constraints »
  Yuchen Zhang · John Duchi · Michael Jordan · Martin J Wainwright
• 2013 Oral: Information-theoretic lower bounds for distributed statistical estimation with communication constraints »
  Yuchen Zhang · John Duchi · Michael Jordan · Martin J Wainwright
• 2013 Poster: Optimistic Concurrency Control for Distributed Unsupervised Learning »
  Xinghao Pan · Joseph Gonzalez · Stefanie Jegelka · Tamara Broderick · Michael Jordan
• 2013 Poster: Local Privacy and Minimax Bounds: Sharp Rates for Probability Estimation »
  John Duchi · Martin J Wainwright · Michael Jordan
• 2013 Poster: Streaming Variational Bayes »
  Tamara Broderick · Nicholas Boyd · Andre Wibisono · Ashia C Wilson · Michael Jordan
• 2013 Poster: Estimation, Optimization, and Parallelism when Data is Sparse »
  John Duchi · Michael Jordan · Brendan McMahan
• 2012 Workshop: Bayesian Nonparametric Models For Reliable Planning And Decision-Making Under Uncertainty »
  Jonathan How · Lawrence Carin · John Fisher III · Michael Jordan · Alborz Geramifard
• 2012 Poster: Privacy Aware Learning »
  John Duchi · Michael Jordan · Martin J Wainwright
• 2012 Poster: Ancestor Sampling for Particle Gibbs »
  Fredrik Lindsten · Michael Jordan · Thomas Schön
• 2012 Poster: Bayesian Pedigree Analysis using Measure Factorization »
  Bonnie Kirkpatrick · Alexandre Bouchard-Côté
• 2012 Oral: Privacy Aware Learning »
  John Duchi · Michael Jordan · Martin J Wainwright
• 2012 Poster: Finite Sample Convergence Rates of Zero-Order Stochastic Optimization Methods »
  John Duchi · Michael Jordan · Martin J Wainwright · Andre Wibisono
• 2012 Poster: Entangled Monte Carlo »
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• 2012 Poster: Small-Variance Asymptotics for Exponential Family Dirichlet Process Mixture Models »
  Ke Jiang · Brian Kulis · Michael Jordan
• 2012 Spotlight: Entangled Monte Carlo »
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• 2011 Workshop: Big Learning: Algorithms, Systems, and Tools for Learning at Scale »
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• 2011 Poster: Bayesian Bias Mitigation for Crowdsourcing »
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• 2011 Poster: Divide-and-Conquer Matrix Factorization »
  Lester W Mackey · Ameet S Talwalkar · Michael Jordan
• 2011 Poster: Priors over Recurrent Continuous Time Processes »
  Ardavan Saeedi · Alexandre Bouchard-Côté
• 2011 Oral: Priors over Recurrent Continuous Time Processes »
  Ardavan Saeedi · Alexandre Bouchard-Côté
• 2010 Oral: Tree-Structured Stick Breaking for Hierarchical Data »
  Ryan Adams · Zoubin Ghahramani · Michael Jordan
• 2010 Invited Talk: Statistical Inference of Protein Structure and Function »
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• 2010 Poster: Tree-Structured Stick Breaking for Hierarchical Data »
  Ryan Adams · Zoubin Ghahramani · Michael Jordan
• 2010 Spotlight: Variational Inference over Combinatorial Spaces »
  Alexandre Bouchard-Côté · Michael Jordan
• 2010 Poster: Variational Inference over Combinatorial Spaces »
  Alexandre Bouchard-Côté · Michael Jordan
• 2010 Poster: Unsupervised Kernel Dimension Reduction »
  Meihong Wang · Fei Sha · Michael Jordan
• 2010 Poster: Heavy-Tailed Process Priors for Selective Shrinkage »
  Fabian L Wauthier · Michael Jordan
• 2010 Poster: Random Conic Pursuit for Semidefinite Programming »
  Ariel Kleiner · ali rahimi · Michael Jordan
• 2009 Workshop: Nonparametric Bayes »
  Dilan Gorur · Francois Caron · Yee Whye Teh · David B Dunson · Zoubin Ghahramani · Michael Jordan
• 2009 Poster: Sharing Features among Dynamical Systems with Beta Processes »
  Emily Fox · Erik Sudderth · Michael Jordan · Alan S Willsky
• 2009 Oral: Sharing Features among Dynamical Systems with Beta Processes »
  Emily Fox · Erik Sudderth · Michael Jordan · Alan S Willsky
• 2009 Poster: Randomized Pruning: Efficiently Calculating Expectations in Large Dynamic Programs »
  Alexandre Bouchard-Côté · Slav Petrov · Dan Klein
• 2009 Spotlight: Randomized Pruning: Efficiently Calculating Expectations in Large Dynamic Programs »
  Alexandre Bouchard-Côté · Slav Petrov · Dan Klein
• 2009 Poster: Asymptotically Optimal Regularization in Smooth Parametric Models »
  Percy Liang · Francis Bach · Guillaume Bouchard · Michael Jordan
• 2009 Poster: Nonparametric Latent Feature Models for Link Prediction »
  Kurt T Miller · Tom Griffiths · Michael Jordan
• 2009 Spotlight: Nonparametric Latent Feature Models for Link Prediction »
  Kurt T Miller · Tom Griffiths · Michael Jordan
• 2008 Workshop: Speech and Language: Unsupervised Latent-Variable Models »
  Slav Petrov · Aria Haghighi · Percy Liang · Dan Klein
• 2008 Oral: Shared Segmentation of Natural Scenes Using Dependent Pitman-Yor Processes »
  Erik Sudderth · Michael Jordan
• 2008 Poster: Nonparametric Bayesian Learning of Switching Linear Dynamical Systems »
  Emily Fox · Erik Sudderth · Michael Jordan · Alan S Willsky
• 2008 Poster: High-dimensional union support recovery in multivariate regression »
  Guillaume R Obozinski · Martin J Wainwright · Michael Jordan
• 2008 Poster: Shared Segmentation of Natural Scenes Using Dependent Pitman-Yor Processes »
  Erik Sudderth · Michael Jordan
• 2008 Spotlight: High-dimensional union support recovery in multivariate regression »
  Guillaume R Obozinski · Martin J Wainwright · Michael Jordan
• 2008 Spotlight: Nonparametric Bayesian Learning of Switching Linear Dynamical Systems »
  Emily Fox · Erik Sudderth · Michael Jordan · Alan S Willsky
• 2008 Poster: Posterior Consistency of the Silverman g-prior in Bayesian Model Choice »
  Zhihua Zhang · Michael Jordan · Dit-Yan Yeung
• 2008 Poster: DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification »
  Simon Lacoste-Julien · Fei Sha · Michael Jordan
• 2008 Spotlight: Posterior Consistency of the Silverman g-prior in Bayesian Model Choice »
  Zhihua Zhang · Michael Jordan · Dit-Yan Yeung
• 2008 Poster: Spectral Clustering with Perturbed Data »
  Ling Huang · Donghui Yan · Michael Jordan · Nina Taft
• 2008 Spotlight: Spectral Clustering with Perturbed Data »
  Ling Huang · Donghui Yan · Michael Jordan · Nina Taft
• 2007 Poster: Agreement-Based Learning »
  Percy Liang · Dan Klein · Michael Jordan
• 2007 Spotlight: Agreement-Based Learning »
  Percy Liang · Dan Klein · Michael Jordan
• 2007 Session: Spotlights »
  Dan Klein
• 2007 Session: Spotlights »
  Dan Klein
• 2007 Spotlight: Discriminative Log-Linear Grammars with Latent Variables »
  Slav Petrov · Dan Klein
• 2007 Spotlight: Resampling Methods for Protein Structure Prediction with Rosetta »
  Ben Blum · David Baker · Michael Jordan · Philip Bradley · Rhiju Das · David Kim
• 2007 Spotlight: Estimating divergence functionals and the likelihood ratio by penalized convex risk minimization »
  XuanLong Nguyen · Martin J Wainwright · Michael Jordan
• 2007 Poster: Discriminative Log-Linear Grammars with Latent Variables »
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• 2007 Poster: Resampling Methods for Protein Structure Prediction with Rosetta »
  Ben Blum · David Baker · Michael Jordan · Philip Bradley · Rhiju Das · David Kim
• 2007 Poster: Estimating divergence functionals and the likelihood ratio by penalized convex risk minimization »
  XuanLong Nguyen · Martin J Wainwright · Michael Jordan
• 2007 Poster: A Probabilistic Approach to Language Change »
  Alexandre Bouchard-Côté · Percy Liang · Tom Griffiths · Dan Klein
• 2006 Poster: Distributed PCA and Network Anomaly Detection »
  Ling Huang · XuanLong Nguyen · Minos Garofalakis · Michael Jordan · Anthony D Joseph · Nina Taft