Foster, Dean P.

28 publications

ALT 2023 Linear Reinforcement Learning with Ball Structure Action Space Zeyu Jia, Randy Jia, Dhruv Madeka, Dean P. Foster

NeurIPS 2022 A Few Expert Queries Suffices for Sample-Efficient RL with Resets and Linear Value Approximation Philip Amortila, Nan Jiang, Dhruv Madeka, Dean P. Foster

NeurIPS 2021 The Benefits of Implicit Regularization from SGD in Least Squares Problems Difan Zou, Jingfeng Wu, Vladimir Braverman, Quanquan Gu, Dean P. Foster, Sham Kakade

NeurIPS 2019 Dynamic Local Regret for Non-Convex Online Forecasting Sergul Aydore, Tianhao Zhu, Dean P. Foster

COLT 2016 Online Sparse Linear Regression Dean P. Foster, Satyen Kale, Howard J. Karloff

JMLR 2015 Eigenwords: Spectral Word Embeddings Paramveer S. Dhillon, Dean P. Foster, Lyle H. Ungar

COLT 2015 Variable Selection Is Hard Dean P. Foster, Howard J. Karloff, Justin Thaler

AISTATS 2014 A Level-Set Hit-and-Run Sampler for Quasi-Concave Distributions Shane T. Jensen, Dean P. Foster

UAI 2014 Adaptive Monotone Shrinkage for Regression Zhuang Ma, Dean P. Foster, Robert A. Stine

UAI 2014 Fast Ridge Regression with Randomized Principal Component Analysis and Gradient Descent Yichao Lu, Dean P. Foster

NeurIPS 2014 Large Scale Canonical Correlation Analysis with Iterative Least Squares Yichao Lu, Dean P. Foster

JMLR 2014 Spectral Learning of Latent-Variable PCFGs: Algorithms and Sample Complexity Shay B. Cohen, Karl Stratos, Michael Collins, Dean P. Foster, Lyle Ungar

JMLR 2013 A Risk Comparison of Ordinary Least Squares vs Ridge Regression Paramveer S. Dhillon, Dean P. Foster, Sham M. Kakade, Lyle H. Ungar

NeurIPS 2013 Faster Ridge Regression via the Subsampled Randomized Hadamard Transform Yichao Lu, Paramveer Dhillon, Dean P. Foster, Lyle Ungar

NeurIPS 2013 New Subsampling Algorithms for Fast Least Squares Regression Paramveer Dhillon, Yichao Lu, Dean P. Foster, Lyle Ungar

NeurIPS 2013 One-Shot Learning and Big Data with N=2 Lee H Dicker, Dean P. Foster

NeurIPS 2012 A Spectral Algorithm for Latent Dirichlet Allocation Anima Anandkumar, Dean P. Foster, Daniel J. Hsu, Sham M. Kakade, Yi-kai Liu

ICML 2012 Using CCA to Improve CCA: A New Spectral Method for Estimating Vector Models of Words Paramveer S. Dhillon, Jordan Rodu, Dean P. Foster, Lyle H. Ungar

COLT 2011 Complexity-Based Approach to Calibration with Checking Rules Dean P. Foster, Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari

NeurIPS 2011 Multi-View Learning of Word Embeddings via CCA Paramveer Dhillon, Dean P. Foster, Lyle H. Ungar

NeurIPS 2011 Stochastic Convex Optimization with Bandit Feedback Alekh Agarwal, Dean P. Foster, Daniel J. Hsu, Sham M. Kakade, Alexander Rakhlin

ECML-PKDD 2009 Multi-Task Feature Selection Using the Multiple Inclusion Criterion (MIC) Paramveer S. Dhillon, Brian Tomasik, Dean P. Foster, Lyle H. Ungar

COLT 2007 Multi-View Regression via Canonical Correlation Analysis Sham M. Kakade, Dean P. Foster

JMLR 2006 Streamwise Feature Selection Jing Zhou, Dean P. Foster, Robert A. Stine, Lyle H. Ungar

AISTATS 2005 Streaming Feature Selection Using IIC Lyle H. Ungar, Jing Zhou, Dean P. Foster, Bob A. Stine

NeurIPS 2005 Worst-Case Bounds for Gaussian Process Models Sham M. Kakade, Matthias W. Seeger, Dean P. Foster

COLT 2004 Deterministic Calibration and Nash Equilibrium Sham M. Kakade, Dean P. Foster

ICML 1997 Characterizing the Generalization Performance of Model Selection Strategies Dale Schuurmans, Lyle H. Ungar, Dean P. Foster