Probabilistic Analysis of a Heuristics for the Dual Bin Packing Problem. - Dean P. Foster; Rakesh Vohra (Inf. Process. Lett., 1989)

A Randomization Rule for Selecting Forecasts. - Dean P. Foster; Rakesh V. Vohra (Oper. Res., 1993)

Reply to Professor Clemen. - Dean P. Foster; Rakesh V. Vohra (Oper. Res., 1993)

Characterizing the generalization performance of model selection strategies. - Dale Schuurmans; Lyle H. Ungar; Dean P. Foster (ICML, 1997)

Business Analysis Using Regression - A Casebook. - Dean P. Foster; Robert A. Stine; Richard P. Waterman (Springer, 1998)

Basic Business Statistics - A Casebook. - Dean P. Foster; Robert A. Stine; Richard P. Waterman (Springer, 1998)

Accounting for Cognitive Costs in On-Line Auction Design. - David C. Parkes; Lyle H. Ungar; Dean P. Foster (AMET, 1998)

An Axiomatic Characterization of a Class of Locations in Tree Networks. - Dean P. Foster; Rakesh V. Vohra (Oper. Res., 1998)

Competitive Algorithms for Layered Graph Traversal. - Amos Fiat; Dean P. Foster; Howard J. Karloff; Yuval Rabani; Yiftach Ravid; Sundar Vishwanathan (SIAM J. Comput., 1998)

Local Asymptotic Coding and the Minimum Description Length. - Dean P. Foster; Robert A. Stine (IEEE Trans. Inf. Theory, 1999)

Universal codes for finite sequences of integers drawn from a monotone distribution. - Dean P. Foster; Robert A. Stine; Abraham J. Wyner (IEEE Trans. Inf. Theory, 2002)

Learning, hypothesis testing, and Nash equilibrium. - Dean P. Foster; H. Peyton Young (Games Econ. Behav., 2003)

Streaming Feature Selection using IIC. - Lyle H. Ungar; Jing Zhou; Dean P. Foster; Bob A. Stine (AISTATS, 2005)

Streaming feature selection using alpha-investing. - Jing Zhou; Dean P. Foster; Robert A. Stine; Lyle H. Ungar (KDD, 2005)

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

Calibration via Regression. - Dean P. Foster; Sham M. Kakade (ITW, 2006)

Streamwise Feature Selection. - Jing Zhou; Dean P. Foster; Robert A. Stine; Lyle H. Ungar (J. Mach. Learn. Res., 2006)

Multi-view Regression Via Canonical Correlation Analysis. - Sham M. Kakade; Dean P. Foster (COLT, 2007)

Efficient Feature Selection in the Presence of Multiple Feature Classes. - Paramveer S. Dhillon; Dean P. Foster; Lyle H. Ungar (ICDM, 2008)

Deterministic calibration and Nash equilibrium. - Sham M. Kakade; Dean P. Foster (J. Comput. Syst. Sci., 2008)

Information Consistency of Nonparametric Gaussian Process Methods. - Matthias W. Seeger; Sham M. Kakade; Dean P. Foster (IEEE Trans. Inf. Theory, 2008)

VIF Regression: A Fast Regression Algorithm for Large Data. - Dongyu Lin; Dean P. Foster (ICDM, 2009)

Multi-task Feature Selection Using the Multiple Inclusion Criterion (MIC). - Paramveer S. Dhillon; Brian Tomasik; Dean P. Foster; Lyle H. Ungar (ECML/PKDD (1), 2009)

Transfer Learning Using Feature Selection - Paramveer S. Dhillon; Dean P. Foster; Lyle H. Ungar (CoRR, 2009)

Brain Imaging and Brain Privacy: A Realistic Concern? - Martha J. Farah; M. Elizabeth Smith; Cyrena Gawuga; Dennis Lindsell; Dean P. Foster (J. Cogn. Neurosci., 2009)

A New Approach to Lexical Disambiguation of Arabic Text. - Rushin Shah; Paramveer S. Dhillon; Mark Y. Liberman; Dean P. Foster; Mohamed Maamouri; Lyle H. Ungar (EMNLP, 2010)

Feature Selection using Multiple Streams. - Paramveer S. Dhillon; Dean P. Foster; Lyle H. Ungar (AISTATS, 2010)

Multi-View Learning of Word Embeddings via CCA. - Paramveer S. Dhillon; Dean P. Foster; Lyle H. Ungar (NIPS, 2011)

Domain Adaptation: Overfitting and Small Sample Statistics - Dean P. Foster; Sham M. Kakade; Ruslan Salakhutdinov (CoRR, 2011)

Domain Adaptation with Coupled Subspaces. - John Blitzer; Sham M. Kakade; Dean P. Foster (AISTATS, 2011)

Minimum Description Length Penalization for Group and Multi-Task Sparse Learning. - Paramveer S. Dhillon; Dean P. Foster; Lyle H. Ungar (J. Mach. Learn. Res., 2011)

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

Spectral Learning of Latent-Variable PCFGs. - Shay B. Cohen; Karl Stratos; Michael Collins 001; Dean P. Foster; Lyle H. Ungar (ACL (1), 2012)

New Insights from Coarse Word Sense Disambiguation in the Crowd. - Adam Kapelner; Krishna Kaliannan; Hansen Andrew Schwartz; Lyle H. Ungar; Dean P. Foster (COLING (Posters), 2012)

Spectral Dependency Parsing with Latent Variables. - Paramveer S. Dhillon; Jordan Rodu; Michael Collins 001; Dean P. Foster; Lyle H. Ungar (EMNLP-CoNLL, 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 (ICML, 2012)

Spectral dimensionality reduction for HMMs - Dean P. Foster; Jordan Rodu; Lyle H. Ungar (CoRR, 2012)

Two SVDs Suffice: Spectral decompositions for probabilistic topic modeling and latent Dirichlet allocation - Animashree Anandkumar; Dean P. Foster; Daniel J. Hsu; Sham M. Kakade; Yi-Kai Liu 001 (CoRR, 2012)

Optimal Weighting of Multi-View Data with Low Dimensional Hidden States - Yichao Lu; Dean P. Foster (CoRR, 2012)

No Internal Regret via Neighborhood Watch. - Dean P. Foster; Alexander Rakhlin (AISTATS, 2012)

Domain Adaptation: A Small Sample Statistical Approach. - Ruslan Salakhutdinov; Sham M. Kakade; Dean P. Foster (AISTATS, 2012)

Spectral Learning Algorithms for Natural Language Processing. - Shay B. Cohen; Michael Collins 001; Dean P. Foster; Karl Stratos; Lyle H. Ungar (HLT-NAACL, 2013)

Experiments with Spectral Learning of Latent-Variable PCFGs. - Shay B. Cohen; Karl Stratos; Michael Collins 001; Dean P. Foster; Lyle H. Ungar (HLT-NAACL, 2013)

New Subsampling Algorithms for Fast Least Squares Regression. - Paramveer S. Dhillon; Yichao Lu; Dean P. Foster; Lyle H. Ungar (NIPS, 2013)

One-shot learning and big data with n=2. - Lee H. Dicker; Dean P. Foster (NIPS, 2013)

Faster Ridge Regression via the Subsampled Randomized Hadamard Transform. - Yichao Lu; Paramveer S. Dhillon; Dean P. Foster; Lyle H. Ungar (NIPS, 2013)

Using Regression for Spectral Estimation of HMMs. - Jordan Rodu; Dean P. Foster; Weichen Wu; Lyle H. Ungar (SLSP, 2013)

A risk comparison of ordinary least squares vs ridge regression. - Paramveer S. Dhillon; Dean P. Foster; Sham M. Kakade; Lyle H. Ungar (J. Mach. Learn. Res., 2013)

Stochastic Convex Optimization with Bandit Feedback. - Alekh Agarwal; Dean P. Foster; Daniel J. Hsu; Sham M. Kakade; Alexander Rakhlin (SIAM J. Optim., 2013)

A Level-set Hit-and-run Sampler for Quasi-Concave Distributions. - Shane T. Jensen; Dean P. Foster (AISTATS, 2014)

large scale canonical correlation analysis with iterative least squares. - Yichao Lu; Dean P. Foster (NIPS, 2014)

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

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

On Optimal Retirement. - Philip A. Ernst; Dean P. Foster; Larry A. Shepp (J. Appl. Probab., 2014)

Spectral learning of latent-variable PCFGs: algorithms and sample complexity. - Shay B. Cohen; Karl Stratos; Michael Collins 001; Dean P. Foster; Lyle H. Ungar (J. Mach. Learn. Res., 2014)

Partial Monitoring - Classification, Regret Bounds, and Algorithms. - Gábor Bartók; Dean P. Foster; Dávid Pál; Alexander Rakhlin; Csaba Szepesvári (Math. Oper. Res., 2014)

Variable Selection is Hard. - Dean P. Foster; Howard J. Karloff; Justin Thaler (COLT, 2015)

Finding Linear Structure in Large Datasets with Scalable Canonical Correlation Analysis. - Zhuang Ma; Yichao Lu; Dean P. Foster (ICML, 2015)

A Spectral Algorithm for Latent Dirichlet Allocation. - Anima Anandkumar; Dean P. Foster; Daniel J. Hsu; Sham M. Kakade; Yi-Kai Liu 001 (Algorithmica, 2015)

Eigenwords: spectral word embeddings. - Paramveer S. Dhillon; Dean P. Foster; Lyle H. Ungar (J. Mach. Learn. Res., 2015)

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

Semantic Word Clusters Using Signed Normalized Graph Cuts. - João Sedoc; Jean Gallier; Lyle H. Ungar; Dean P. Foster (CoRR, 2016)

Semantic Word Clusters Using Signed Spectral Clustering. - João Sedoc; Jean Gallier; Dean P. Foster; Lyle H. Ungar (ACL (1), 2017)

Invariances and Data Augmentation for Supervised Music Transcription. - John Thickstun; Zaïd Harchaoui; Dean P. Foster; Sham M. Kakade (ICASSP, 2018)

A Local Regret in Nonconvex Online Learning. - Sergül Aydöre; Lee H. Dicker; Dean P. Foster (CoRR, 2018)

Smooth calibration, leaky forecasts, finite recall, and Nash dynamics. - Dean P. Foster; Sergiu Hart (Games Econ. Behav., 2018)

Deep Factors for Forecasting. - Yuyang Wang 001; Alex Smola; Danielle C. Maddix; Jan Gasthaus; Dean P. Foster; Tim Januschowski (ICML, 2019)

Coupled Recurrent Models for Polyphonic Music Composition. - John Thickstun; Zaïd Harchaoui; Dean P. Foster; Sham M. Kakade (ISMIR, 2019)

Dynamic Local Regret for Non-convex Online Forecasting. - Sergül Aydöre; Tianhao Zhu; Dean P. Foster (NeurIPS, 2019)

Interactive Visualization of Painting Data with Augmented Reality. - Kyungjin Yoo; Dean P. Foster (VRST, 2019)

PACT: Privacy Sensitive Protocols and Mechanisms for Mobile Contact Tracing. - Justin Chan; Dean P. Foster; Shyam Gollakota; Eric Horvitz; Joseph Jaeger; Sham M. Kakade; Tadayoshi Kohno; John Langford 001; Jonathan Larson; Sudheesh Singanamalla; Jacob E. Sunshine; Stefano Tessaro (CoRR, 2020)

PACT: Privacy-Sensitive Protocols And Mechanisms for Mobile Contact Tracing. - Justin Chan; Landon P. Cox; Dean P. Foster; Shyam Gollakota; Eric Horvitz; Joseph Jaeger; Sham M. Kakade; Tadayoshi Kohno; John Langford 001; Jonathan Larson; Puneet Sharma; Sudheesh Singanamalla; et al. (IEEE Data Eng. Bull., 2020)

What are the Statistical Limits of Offline RL with Linear Function Approximation? - Ruosong Wang; Dean P. Foster; Sham M. Kakade (ICLR, 2021)

Variance Reduced Training with Stratified Sampling for Forecasting Models. - Yucheng Lu; Youngsuk Park; Lifan Chen; Yuyang Wang 001; Christopher De Sa; Dean P. Foster (ICML, 2021)

Top-k eXtreme Contextual Bandits with Arm Hierarchy. - Rajat Sen; Alexander Rakhlin; Lexing Ying; Rahul Kidambi; Dean P. Foster; Daniel N. Hill; Inderjit S. Dhillon (ICML, 2021)

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

Variance Reduction in Training Forecasting Models with Subgroup Sampling. - Yucheng Lu; Youngsuk Park; Lifan Chen; Yuyang Wang 001; Christopher De Sa; Dean P. Foster (CoRR, 2021)

Threshold Martingales and the Evolution of Forecasts. - Dean P. Foster; Robert A. Stine (CoRR, 2021)

On Submodular Contextual Bandits. - Dean P. Foster; Alexander Rakhlin (CoRR, 2021)

Single-Index Models in the High Signal Regime. - Ashwin Pananjady; Dean P. Foster (IEEE Trans. Inf. Theory, 2021)

Impartial Predictive Modeling and the Use of Proxy Variables. - Kory D. Johnson; Dean P. Foster; Robert A. Stine (iConference (1), 2022)

A Few Expert Queries Suffices for Sample-Efficient RL with Resets and Linear Value Approximation. - Philip Amortila; Nan Jiang 008; Dhruv Madeka; Dean P. Foster (NeurIPS, 2022)

"Calibeating": Beating Forecasters at Their Own Game. - Dean P. Foster; Sergiu Hart (CoRR, 2022)

Deep Inventory Management. - Dhruv Madeka; Kari Torkkola; Carson Eisenach; Dean P. Foster; Anna Luo (CoRR, 2022)

Forecast Hedging and Calibration. - Dean P. Foster; Sergiu Hart (CoRR, 2022)

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

On the Complexity of Multi-Agent Decision Making: From Learning in Games to Partial Monitoring. - Dean P. Foster; Dylan J. Foster; Noah Golowich; Alexander Rakhlin (COLT, 2023)

Scaling Laws for Imitation Learning in NetHack. - Jens Tuyls; Dhruv Madeka; Kari Torkkola; Dean P. Foster; Karthik Narasimhan; Sham M. Kakade (CoRR, 2023)

Contextual Bandits for Evaluating and Improving Inventory Control Policies. - Dean P. Foster; Randy Jia; Dhruv Madeka (CoRR, 2023)

Learning an Inventory Control Policy with General Inventory Arrival Dynamics. - Sohrab Andaz; Carson Eisenach; Dhruv Madeka; Kari Torkkola; Randy Jia; Dean P. Foster; Sham M. Kakade (CoRR, 2023)

AI safety by debate via regret minimization. - Xinyi Chen 001; Angelica Chen; Dean P. Foster; Elad Hazan (CoRR, 2023)

A Study on the Calibration of In-context Learning. - Hanlin Zhang 002; Yifan Zhang 004; Yaodong Yu; Dhruv Madeka; Dean P. Foster; Eric P. Xing; Himabindu Lakkaraju; Sham M. Kakade (NAACL-HLT, 2024)

Neural Coordination and Capacity Control for Inventory Management. - Carson Eisenach; Udaya Ghai; Dhruv Madeka; Kari Torkkola; Dean P. Foster; Sham M. Kakade (CoRR, 2024)

Large Deviations Inequalities for Unequal Probability Sampling Without Replacement. - Dean P. Foster; Sergiu Hart (CoRR, 2024)

Scaling Laws for Imitation Learning in Single-Agent Games. - Jens Tuyls; Dhruv Madeka; Kari Torkkola; Dean P. Foster; Karthik R. Narasimhan; Sham M. Kakade (Trans. Mach. Learn. Res., 2024)

Mind the Gap: Examining the Self-Improvement Capabilities of Large Language Models. - Yuda Song 001; Hanlin Zhang 002; Carson Eisenach; Sham M. Kakade; Dean P. Foster; Udaya Ghai (ICLR, 2025)

How Does Critical Batch Size Scale in Pre-training? - Hanlin Zhang 002; Depen Morwani; Nikhil Vyas 001; Jingfeng Wu; Difan Zou; Udaya Ghai; Dean P. Foster; Sham M. Kakade (ICLR, 2025)

The Role of the Marketplace Operator in Inducing Competition. - Tiffany Ding; Dominique Perrault-Joncas; Orit Ronen; Michael I. Jordan; Dirk Bergemann; Dean P. Foster; Omer Gottesman (CoRR, 2025)

Outbound Modeling for Inventory Management. - Riccardo Savorgnan; Udaya Ghai; Carson Eisenach; Dean P. Foster (CoRR, 2025)

Efficient RL for optimizing conversation level outcomes with an LLM-based tutor. - Hyunji Nam; Omer Gottesman; Amy Zhang; Dean P. Foster; Emma Brunskill; Lyle H. Ungar (CoRR, 2025)

Structure-Informed Deep Reinforcement Learning for Inventory Management. - Alvaro Maggiar; Sohrab Andaz; Akhil Bagaria; Carson Eisenach; Dean P. Foster; Omer Gottesman; Dominique Perrault-Joncas (CoRR, 2025)