Sham M. Kakade
Identifiers
- name variant Sham M. Kakade 0.60 · backfill
Papers (50)
- Evaluating Relational Reasoning in LLMs with REL cs.AI · 2026 · author #4
- Calibration, Entropy Rates, and Memory in Language Models cs.CL · 2019 · author #3
- Online Control with Adversarial Disturbances cs.LG · 2019 · author #4
- Maximum Likelihood Estimation for Learning Populations of Parameters math.ST · 2019 · author #4
- A Short Note on Concentration Inequalities for Random Vectors with SubGaussian Norm math.PR · 2019 · author #4
- A Smoother Way to Train Structured Prediction Models stat.ML · 2019 · author #3
- Provably Efficient Maximum Entropy Exploration cs.LG · 2018 · author #2
- On the insufficiency of existing momentum schemes for Stochastic Optimization cs.LG · 2018 · author #4
- Global Convergence of Policy Gradient Methods for the Linear Quadratic Regulator cs.LG · 2018 · author #3
- Invariances and Data Augmentation for Supervised Music Transcription stat.ML · 2017 · author #4
- A Markov Chain Theory Approach to Characterizing the Minimax Optimality of Stochastic Gradient Descent (for Least Squares) stat.ML · 2017 · author #2
- Accelerating Stochastic Gradient Descent For Least Squares Regression stat.ML · 2017 · author #2
- How to Escape Saddle Points Efficiently cs.LG · 2017 · author #4
- Canonical Correlation Analysis for Analyzing Sequences of Medical Billing Codes stat.ML · 2016 · author #2
- Parallelizing Stochastic Gradient Descent for Least Squares Regression: mini-batching, averaging, and model misspecification stat.ML · 2016 · author #2
- Provable Efficient Online Matrix Completion via Non-convex Stochastic Gradient Descent cs.LG · 2016 · author #2
- Faster Eigenvector Computation via Shift-and-Invert Preconditioning cs.DS · 2016 · author #4
- Efficient Algorithms for Large-scale Generalized Eigenvector Computation and Canonical Correlation Analysis cs.LG · 2016 · author #3
- Streaming PCA: Matching Matrix Bernstein and Near-Optimal Finite Sample Guarantees for Oja's Algorithm cs.LG · 2016 · author #3
- Recovering Structured Probability Matrices cs.LG · 2016 · author #2
- Robust Shift-and-Invert Preconditioning: Faster and More Sample Efficient Algorithms for Eigenvector Computation cs.DS · 2015 · author #2
- Super-Resolution Off the Grid cs.LG · 2015 · author #2
- Global Convergence of Non-Convex Gradient Descent for Computing Matrix Squareroot math.NA · 2015 · author #3
- Un-regularizing: approximate proximal point and faster stochastic algorithms for empirical risk minimization stat.ML · 2015 · author #3
- Learning Mixtures of Gaussians in High Dimensions cs.LG · 2015 · author #3
- Competing with the Empirical Risk Minimizer in a Single Pass stat.ML · 2014 · author #3
- Least Squares Revisited: Scalable Approaches for Multi-class Prediction cs.LG · 2013 · author #2
- A Tensor Approach to Learning Mixed Membership Community Models cs.LG · 2013 · author #4
- Analysis of a randomized approximation scheme for matrix multiplication cs.DS · 2012 · author #2
- Tensor decompositions for learning latent variable models cs.LG · 2012 · author #4
- Learning Topic Models and Latent Bayesian Networks Under Expansion Constraints stat.ML · 2012 · author #4
- Planning in POMDPs Using Multiplicity Automata cs.AI · 2012 · author #2
- Learning mixtures of spherical Gaussians: moment methods and spectral decompositions cs.LG · 2012 · author #2
- Identifiability and Unmixing of Latent Parse Trees stat.ML · 2012 · author #2
- A Spectral Algorithm for Latent Dirichlet Allocation cs.LG · 2012 · author #4
- A Method of Moments for Mixture Models and Hidden Markov Models cs.LG · 2012 · author #3
- Towards minimax policies for online linear optimization with bandit feedback cs.LG · 2012 · author #3
- A tail inequality for quadratic forms of subgaussian random vectors math.PR · 2011 · author #2
- Stochastic convex optimization with bandit feedback math.OC · 2011 · author #4
- Spectral Methods for Learning Multivariate Latent Tree Structure cs.LG · 2011 · author #4
- Random design analysis of ridge regression math.ST · 2011 · author #2
- A Risk Comparison of Ordinary Least Squares vs Ridge Regression stat.ML · 2011 · author #3
- Dimension-free tail inequalities for sums of random matrices math.PR · 2011 · author #2
- Robust Matrix Decomposition with Outliers stat.ML · 2010 · author #2
- An Optimal Dynamic Mechanism for Multi-Armed Bandit Processes cs.GT · 2010 · author #1
- Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design cs.LG · 2009 · author #3
- Learning Exponential Families in High-Dimensions: Strong Convexity and Sparsity cs.LG · 2009 · author #1
- Regularization Techniques for Learning with Matrices cs.LG · 2009 · author #1
- Multi-Label Prediction via Compressed Sensing cs.LG · 2009 · author #2
- A Spectral Algorithm for Learning Hidden Markov Models cs.LG · 2008 · author #2
Mentions
- 1210.7559 #4 · backfill · confidence 0.70 Sham M. Kakade
- 1209.5350 #4 · backfill · confidence 0.70 Sham M. Kakade
- 1207.1388 #2 · backfill · confidence 0.70 Sham M. Kakade
- 1206.5766 #2 · backfill · confidence 0.70 Sham M. Kakade
- 1206.3137 #2 · backfill · confidence 0.70 Sham M. Kakade
- 1204.6703 #4 · backfill · confidence 0.70 Sham M. Kakade
- 1203.0683 #3 · backfill · confidence 0.70 Sham M. Kakade
- 1202.3079 #3 · backfill · confidence 0.70 Sham M. Kakade
- 1110.2842 #2 · backfill · confidence 0.70 Sham M. Kakade
- 1107.1744 #4 · backfill · confidence 0.70 Sham M. Kakade
- 1107.1283 #4 · backfill · confidence 0.70 Sham M. Kakade
- 1106.2363 #2 · backfill · confidence 0.70 Sham M. Kakade
- 1105.0875 #3 · backfill · confidence 0.70 Sham M. Kakade
- 1104.1672 #2 · backfill · confidence 0.70 Sham M. Kakade
- 1011.1518 #2 · backfill · confidence 0.70 Sham M. Kakade
- 1001.4598 #1 · backfill · confidence 0.70 Sham M. Kakade
- 0912.3995 #3 · backfill · confidence 0.70 Sham M. Kakade
- 0911.0054 #1 · backfill · confidence 0.70 Sham M. Kakade
- 0910.0610 #1 · backfill · confidence 0.70 Sham M. Kakade
- 0902.1284 #2 · backfill · confidence 0.70 Sham M. Kakade
- 0811.4413 #2 · backfill · confidence 0.70 Sham M. Kakade
Frequent Coauthors
- Daniel Hsu 16 shared papers
- Praneeth Netrapalli 12 shared papers
- Aaron Sidford 9 shared papers
- Rong Ge 9 shared papers
- Chi Jin 8 shared papers
- Tong Zhang 8 shared papers
- Prateek Jain 6 shared papers
- Animashree Anandkumar 4 shared papers
- Rahul Kidambi 4 shared papers
- Dean P. Foster 3 shared papers
- Elad Hazan 3 shared papers
- Gregory Valiant 3 shared papers
- Qingqing Huang 3 shared papers
- Alekh Agarwal 2 shared papers
- Ambuj Tewari 2 shared papers
- Anima Anandkumar 2 shared papers
- Cameron Musco 2 shared papers
- Karan Singh 2 shared papers
- Le Song 2 shared papers
- Michael I. Jordan 2 shared papers