Sham M. Kakade
According to our database^{1},
Sham M. Kakade
authored at least 113 papers
between 1999 and 2019.
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Bibliography
2019
The Illusion of Change: Correcting for Biases in Change Inference for Sparse, SocietalScale Data.
Proceedings of the World Wide Web Conference, 2019
Maximum Likelihood Estimation for Learning Populations of Parameters.
Proceedings of the 36th International Conference on Machine Learning, 2019
Provably Efficient Maximum Entropy Exploration.
Proceedings of the 36th International Conference on Machine Learning, 2019
Online MetaLearning.
Proceedings of the 36th International Conference on Machine Learning, 2019
Online Control with Adversarial Disturbances.
Proceedings of the 36th International Conference on Machine Learning, 2019
Plan Online, Learn Offline: Efficient Learning and Exploration via ModelBased Control.
Proceedings of the 7th International Conference on Learning Representations, 2019
Open Problem: Do Good Algorithms Necessarily Query Bad Points?
Proceedings of the Conference on Learning Theory, 2019
2018
Prediction with a short memory.
Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing, 2018
A Smoother Way to Train Structured Prediction Models.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Provably Correct Automatic SubDifferentiation for Qualified Programs.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
On the Insufficiency of Existing Momentum Schemes for Stochastic Optimization.
Proceedings of the 2018 Information Theory and Applications Workshop, 2018
Recovering Structured Probability Matrices.
Proceedings of the 9th Innovations in Theoretical Computer Science Conference, 2018
Global Convergence of Policy Gradient Methods for the Linear Quadratic Regulator.
Proceedings of the 35th International Conference on Machine Learning, 2018
Variance Reduction for Policy Gradient with ActionDependent Factorized Baselines.
Proceedings of the 6th International Conference on Learning Representations, 2018
On the insufficiency of existing momentum schemes for Stochastic Optimization.
Proceedings of the 6th International Conference on Learning Representations, 2018
Invariances and Data Augmentation for Supervised Music Transcription.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018
Accelerating Stochastic Gradient Descent for Least Squares Regression.
Proceedings of the Conference On Learning Theory, 2018
2017
Parallelizing Stochastic Gradient Descent for Least Squares Regression: Minibatching, Averaging, and Model Misspecification.
J. Mach. Learn. Res., 2017
Learning Overcomplete HMMs.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
Towards Generalization and Simplicity in Continuous Control.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
How to Escape Saddle Points Efficiently.
Proceedings of the 34th International Conference on Machine Learning, 2017
Learning Features of Music From Scratch.
Proceedings of the 5th International Conference on Learning Representations, 2017
A Markov Chain Theory Approach to Characterizing the Minimax Optimality of Stochastic Gradient Descent (for Least Squares).
Proceedings of the 37th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science, 2017
Global Convergence of NonConvex Gradient Descent for Computing Matrix Squareroot.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017
2016
Minimal Realization Problems for Hidden Markov Models.
IEEE Trans. Signal Processing, 2016
Provable Efficient Online Matrix Completion via Nonconvex Stochastic Gradient Descent.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016
Efficient Algorithms for Largescale Generalized Eigenvector Computation and Canonical Correlation Analysis.
Proceedings of the 33nd International Conference on Machine Learning, 2016
Faster Eigenvector Computation via ShiftandInvert Preconditioning.
Proceedings of the 33nd International Conference on Machine Learning, 2016
Streaming PCA: Matching Matrix Bernstein and NearOptimal Finite Sample Guarantees for Oja's Algorithm.
Proceedings of the 29th Conference on Learning Theory, 2016
2015
Learning Mixtures of Gaussians in High Dimensions.
Proceedings of the FortySeventh Annual ACM on Symposium on Theory of Computing, 2015
SuperResolution Off the Grid.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015
Convergence Rates of Active Learning for Maximum Likelihood Estimation.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015
Unregularizing: approximate proximal point and faster stochastic algorithms for empirical risk minimization.
Proceedings of the 32nd International Conference on Machine Learning, 2015
A Linear Dynamical System Model for Text.
Proceedings of the 32nd International Conference on Machine Learning, 2015
Competing with the Empirical Risk Minimizer in a Single Pass.
Proceedings of The 28th Conference on Learning Theory, 2015
Tensor Decompositions for Learning Latent Variable Models (A Survey for ALT).
Proceedings of the Algorithmic Learning Theory  26th International Conference, 2015
2014
Tensor decompositions for learning latent variable models.
J. Mach. Learn. Res., 2014
A tensor approach to learning mixed membership community models.
J. Mach. Learn. Res., 2014
Least Squares Revisited: Scalable Approaches for Multiclass Prediction.
Proceedings of the 31th International Conference on Machine Learning, 2014
Minimal realization problem for Hidden Markov Models.
Proceedings of the 52nd Annual Allerton Conference on Communication, 2014
2013
A risk comparison of ordinary least squares vs ridge regression.
J. Mach. Learn. Res., 2013
Optimal Dynamic Mechanism Design and the VirtualPivot Mechanism.
Operations Research, 2013
When are Overcomplete Topic Models Identifiable? Uniqueness of Tensor Tucker Decompositions with Structured Sparsity.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 58, 2013
Learning mixtures of spherical gaussians: moment methods and spectral decompositions.
Proceedings of the Innovations in Theoretical Computer Science, 2013
Learning Linear Bayesian Networks with Latent Variables.
Proceedings of the 30th International Conference on Machine Learning, 2013
A Tensor Spectral Approach to Learning Mixed Membership Community Models.
Proceedings of the COLT 2013, 2013
2012
InformationTheoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting.
IEEE Trans. Information Theory, 2012
Domain Adaptation: A Small Sample Statistical Approach.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012
Regularization Techniques for Learning with Matrices.
J. Mach. Learn. Res., 2012
Random Design Analysis of Ridge Regression.
Proceedings of the COLT 2012, 2012
(weak) Calibration is Computationally Hard.
Proceedings of the COLT 2012, 2012
Towards Minimax Policies for Online Linear Optimization with Bandit Feedback.
Proceedings of the COLT 2012, 2012
A Method of Moments for Mixture Models and Hidden Markov Models.
Proceedings of the COLT 2012, 2012
Identifiability and Unmixing of Latent Parse Trees.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 36, 2012
Learning Mixtures of Tree Graphical Models.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 36, 2012
A Spectral Algorithm for Latent Dirichlet Allocation.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 36, 2012
2011
Robust Matrix Decomposition With Sparse Corruptions.
IEEE Trans. Information Theory, 2011
Optimal dynamic mechanism design via a virtual VCG mechanism.
SIGecom Exchanges, 2011
Preface.
Proceedings of the COLT 2011, 2011
Domain Adaptation with Coupled Subspaces.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011
Efficient Learning of Generalized Linear and Single Index Models with Isotonic Regression.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 1214 December 2011, 2011
Spectral Methods for Learning Multivariate Latent Tree Structure.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 1214 December 2011, 2011
Stochastic convex optimization with bandit feedback.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 1214 December 2011, 2011
2010
Guest editorial: special issue on learning theory.
Machine Learning, 2010
Learning Exponential Families in HighDimensions: Strong Convexity and Sparsity.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010
Learning from Logged Implicit Exploration Data.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 69 December 2010, 2010
Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design.
Proceedings of the 27th International Conference on Machine Learning (ICML10), 2010
2009
Online Markov Decision Processes.
Math. Oper. Res., 2009
The price of truthfulness for payperclick auctions.
Proceedings of the Proceedings 10th ACM Conference on Electronic Commerce (EC2009), 2009
MultiLabel Prediction via Compressed Sensing.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 710 December 2009, 2009
Multiview clustering via canonical correlation analysis.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009
A Spectral Algorithm for Learning Hidden Markov Models.
Proceedings of the COLT 2009, 2009
2008
Information Consistency of Nonparametric Gaussian Process Methods.
IEEE Trans. Information Theory, 2008
Mind the Duality Gap: Logarithmic regret algorithms for online optimization.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008
On the Generalization Ability of Online Strongly Convex Programming Algorithms.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008
On the Complexity of Linear Prediction: Risk Bounds, Margin Bounds, and Regularization.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008
Efficient bandit algorithms for online multiclass prediction.
Proceedings of the Machine Learning, 2008
An Information Theoretic Framework for Multiview Learning.
Proceedings of the 21st Annual Conference on Learning Theory, 2008
Stochastic Linear Optimization under Bandit Feedback.
Proceedings of the 21st Annual Conference on Learning Theory, 2008
HighProbability Regret Bounds for Bandit Online Linear Optimization.
Proceedings of the 21st Annual Conference on Learning Theory, 2008
2007
Maximum Entropy Correlated Equilibria.
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007
Playing games with approximation algorithms.
Proceedings of the 39th Annual ACM Symposium on Theory of Computing, 2007
The Price of Bandit Information for Online Optimization.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007
The Value of Observation for Monitoring Dynamic Systems.
Proceedings of the IJCAI 2007, 2007
Leveragingarchivalvideo for building face datasets.
Proceedings of the IEEE 11th International Conference on Computer Vision, 2007
Multiview Regression Via Canonical Correlation Analysis.
Proceedings of the Learning Theory, 20th Annual Conference on Learning Theory, 2007
2006
(In)Stability properties of limit order dynamics.
Proceedings of the Proceedings 7th ACM Conference on Electronic Commerce (EC2006), 2006
Calibration via Regression.
Proceedings of the 2006 IEEE Information Theory Workshop, 2006
Cover trees for nearest neighbor.
Proceedings of the Machine Learning, 2006
2005
Planning in POMDPs Using Multiplicity Automata.
Proceedings of the UAI '05, 2005
WorstCase Bounds for Gaussian Process Models.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005
From Batch to Transductive Online Learning.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005
Reinforcement Learning in POMDPs Without Resets.
Proceedings of the IJCAI05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30, 2005
Trading in Markovian Price Models.
Proceedings of the Learning Theory, 18th Annual Conference on Learning Theory, 2005
2004
Competitive algorithms for VWAP and limit order trading.
Proceedings of the Proceedings 5th ACM Conference on Electronic Commerce (EC2004), 2004
Online Bounds for Bayesian Algorithms.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004
Economic Properties of Social Networks.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004
Experts in a Markov Decision Process.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004
Graphical Economics.
Proceedings of the Learning Theory, 17th Annual Conference on Learning Theory, 2004
Deterministic Calibration and Nash Equilibrium.
Proceedings of the Learning Theory, 17th Annual Conference on Learning Theory, 2004
2003
Correlated equilibria in graphical games.
Proceedings of the Proceedings 4th ACM Conference on Electronic Commerce (EC2003), 2003
Policy Search by Dynamic Programming.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003
Exploration in Metric State Spaces.
Proceedings of the Machine Learning, 2003
2002
Dopamine: generalization and bonuses.
Neural Networks, 2002
Opponent interactions between serotonin and dopamine.
Neural Networks, 2002
Competitive Analysis of the Explore/Exploit Tradeoff.
Proceedings of the Machine Learning, 2002
An Alternate Objective Function for Markovian Fields.
Proceedings of the Machine Learning, 2002
Approximately Optimal Approximate Reinforcement Learning.
Proceedings of the Machine Learning, 2002
2001
A Natural Policy Gradient.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001
Optimizing Average Reward Using Discounted Rewards.
Proceedings of the Computational Learning Theory, 2001
2000
Dopamine Bonuses.
Proceedings of the Advances in Neural Information Processing Systems 13, 2000
Explaining Away in Weight Space.
Proceedings of the Advances in Neural Information Processing Systems 13, 2000
1999
Acquisition in Autoshaping.
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999