Dean P. Foster

According to our database, Dean P. Foster authored at least 94 papers between 1989 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

How Does Critical Batch Size Scale in Pre-training?

Hanlin Zhang, Depen Morwani, Nikhil Vyas, Jingfeng Wu, Difan Zou, Udaya Ghai, Dean P. Foster, Sham M. Kakade

CoRR, 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

A Study on the Calibration of In-context Learning.

Hanlin Zhang, Yifan Zhang, Yaodong Yu, Dhruv Madeka, Dean P. Foster, Eric P. Xing, Himabindu Lakkaraju, Sham M. Kakade

Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

2023

AI safety by debate via regret minimization.

Xinyi Chen, Angelica Chen, Dean P. Foster, Elad Hazan

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

Contextual Bandits for Evaluating and Improving Inventory Control Policies.

Dean P. Foster, Randy Jia, Dhruv Madeka

CoRR, 2023

Scaling Laws for Imitation Learning in NetHack.

Jens Tuyls, Dhruv Madeka, Kari Torkkola, Dean P. Foster, Karthik Narasimhan, Sham M. Kakade

CoRR, 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

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

Linear Reinforcement Learning with Ball Structure Action Space.

Zeyu Jia, Randy Jia, Dhruv Madeka, Dean P. Foster

Proceedings of the International Conference on Algorithmic Learning Theory, 2023

2022

Forecast Hedging and Calibration.

Dean P. Foster, Sergiu Hart

CoRR, 2022

Deep Inventory Management.

Dhruv Madeka, Kari Torkkola, Carson Eisenach, Dean P. Foster, Anna Luo

CoRR, 2022

"Calibeating": Beating Forecasters at Their Own Game.

Dean P. Foster, Sergiu Hart

CoRR, 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

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Impartial Predictive Modeling and the Use of Proxy Variables.

Kory D. Johnson, Dean P. Foster, Robert A. Stine

Proceedings of the Information for a Better World: Shaping the Global Future - 17th International Conference, iConference 2022, Virtual Event, February 28, 2022

2021

Single-Index Models in the High Signal Regime.

Ashwin Pananjady, Dean P. Foster

IEEE Trans. Inf. Theory, 2021

On Submodular Contextual Bandits.

Dean P. Foster, Alexander Rakhlin

CoRR, 2021

Threshold Martingales and the Evolution of Forecasts.

Dean P. Foster, Robert A. Stine

CoRR, 2021

Variance Reduction in Training Forecasting Models with Subgroup Sampling.

Yucheng Lu, Youngsuk Park, Lifan Chen, Yuyang Wang, Christopher De Sa, Dean P. Foster

CoRR, 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

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 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

Proceedings of the 38th International Conference on Machine Learning, 2021

Variance Reduced Training with Stratified Sampling for Forecasting Models.

Yucheng Lu, Youngsuk Park, Lifan Chen, Yuyang Wang, Christopher De Sa, Dean P. Foster

Proceedings of the 38th International Conference on Machine Learning, 2021

What are the Statistical Limits of Offline RL with Linear Function Approximation?

Ruosong Wang, Dean P. Foster, Sham M. Kakade

Proceedings of the 9th International Conference on Learning Representations, 2021

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, Jonathan Larson, Puneet Sharma, Sudheesh Singanamalla, Jacob E. Sunshine, Stefano Tessaro

IEEE Data Eng. Bull., 2020

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, Jonathan Larson, Sudheesh Singanamalla, Jacob E. Sunshine, Stefano Tessaro

CoRR, 2020

2019

Interactive Visualization of Painting Data with Augmented Reality.

Kyungjin Yoo, Dean P. Foster

Proceedings of the 25th ACM Symposium on Virtual Reality Software and Technology, 2019

Dynamic Local Regret for Non-convex Online Forecasting.

Sergül Aydöre, Tianhao Zhu, Dean P. Foster

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Coupled Recurrent Models for Polyphonic Music Composition.

John Thickstun, Zaïd Harchaoui, Dean P. Foster, Sham M. Kakade

Proceedings of the 20th International Society for Music Information Retrieval Conference, 2019

Deep Factors for Forecasting.

Yuyang Wang, Alex Smola, Danielle C. Maddix, Jan Gasthaus, Dean P. Foster, Tim Januschowski

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Smooth calibration, leaky forecasts, finite recall, and Nash dynamics.

Dean P. Foster, Sergiu Hart

Games Econ. Behav., 2018

A Local Regret in Nonconvex Online Learning.

Sergül Aydöre, Lee H. Dicker, Dean P. Foster

CoRR, 2018

Invariances and Data Augmentation for Supervised Music Transcription.

John Thickstun, Zaïd Harchaoui, Dean P. Foster, Sham M. Kakade

Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

2017

Semantic Word Clusters Using Signed Spectral Clustering.

João Sedoc, Jean Gallier, Dean P. Foster, Lyle H. Ungar

Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, 2017

2016

Semantic Word Clusters Using Signed Normalized Graph Cuts.

João Sedoc, Jean Gallier, Lyle H. Ungar, Dean P. Foster

CoRR, 2016

Online Sparse Linear Regression.

Dean P. Foster, Satyen Kale, Howard J. Karloff

Proceedings of the 29th Conference on Learning Theory, 2016

2015

Eigenwords: spectral word embeddings.

Paramveer S. Dhillon, Dean P. Foster, Lyle H. Ungar

J. Mach. Learn. Res., 2015

A Spectral Algorithm for Latent Dirichlet Allocation.

Anima Anandkumar, Dean P. Foster, Daniel J. Hsu, Sham M. Kakade, Yi-Kai Liu

Algorithmica, 2015

Finding Linear Structure in Large Datasets with Scalable Canonical Correlation Analysis.

Zhuang Ma, Yichao Lu, Dean P. Foster

Proceedings of the 32nd International Conference on Machine Learning, 2015

Variable Selection is Hard.

Dean P. Foster, Howard J. Karloff, Justin Thaler

Proceedings of The 28th Conference on Learning Theory, 2015

2014

Partial Monitoring - Classification, Regret Bounds, and Algorithms.

Gábor Bartók, Dean P. Foster, Dávid Pál, Alexander Rakhlin, Csaba Szepesvári

Math. Oper. Res., 2014

Spectral learning of latent-variable PCFGs: algorithms and sample complexity.

Shay B. Cohen, Karl Stratos, Michael Collins, Dean P. Foster, Lyle H. Ungar

J. Mach. Learn. Res., 2014

On Optimal Retirement.

Philip A. Ernst, Dean P. Foster, Larry A. Shepp

J. Appl. Probab., 2014

Adaptive Monotone Shrinkage for Regression.

Zhuang Ma, Dean P. Foster, Robert A. Stine

Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

Fast Ridge Regression with Randomized Principal Component Analysis and Gradient Descent.

Yichao Lu, Dean P. Foster

Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

large scale canonical correlation analysis with iterative least squares.

Yichao Lu, Dean P. Foster

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

A Level-set Hit-and-run Sampler for Quasi-Concave Distributions.

Shane T. Jensen, Dean P. Foster

Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

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 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

Using Regression for Spectral Estimation of HMMs.

Jordan Rodu, Dean P. Foster, Weichen Wu, Lyle H. Ungar

Proceedings of the Statistical Language and Speech Processing, 2013

Faster Ridge Regression via the Subsampled Randomized Hadamard Transform.

Yichao Lu, Paramveer S. Dhillon, Dean P. Foster, Lyle H. Ungar

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 5-8, 2013

One-shot learning and big data with n=2.

Lee H. Dicker, Dean P. Foster

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 5-8, 2013

New Subsampling Algorithms for Fast Least Squares Regression.

Paramveer S. Dhillon, Yichao Lu, Dean P. Foster, Lyle H. Ungar

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 5-8, 2013

Experiments with Spectral Learning of Latent-Variable PCFGs.

Shay B. Cohen, Karl Stratos, Michael Collins, Dean P. Foster, Lyle H. Ungar

Proceedings of the Human Language Technologies: Conference of the North American Chapter of the Association of Computational Linguistics, 2013

Spectral Learning Algorithms for Natural Language Processing.

Shay B. Cohen, Michael Collins, Dean P. Foster, Karl Stratos, Lyle H. Ungar

Proceedings of the Human Language Technologies: Conference of the North American Chapter of the Association of Computational Linguistics, 2013

2012

Domain Adaptation: A Small Sample Statistical Approach.

Ruslan Salakhutdinov, Sham M. Kakade, Dean P. Foster

Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

No Internal Regret via Neighborhood Watch.

Dean P. Foster, Alexander Rakhlin

Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Optimal Weighting of Multi-View Data with Low Dimensional Hidden States

Yichao Lu, Dean P. Foster

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

CoRR, 2012

Spectral dimensionality reduction for HMMs

Dean P. Foster, Jordan Rodu, Lyle H. Ungar

CoRR, 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

Proceedings of the 29th International Conference on Machine Learning, 2012

Spectral Dependency Parsing with Latent Variables.

Paramveer S. Dhillon, Jordan Rodu, Michael Collins, Dean P. Foster, Lyle H. Ungar

Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, 2012

New Insights from Coarse Word Sense Disambiguation in the Crowd.

Adam Kapelner, Krishna Kaliannan, Hansen Andrew Schwartz, Lyle H. Ungar, Dean P. Foster

Proceedings of the COLING 2012, 2012

Spectral Learning of Latent-Variable PCFGs.

Shay B. Cohen, Karl Stratos, Michael Collins, Dean P. Foster, Lyle H. Ungar

Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference, July 8-14, 2012, Jeju Island, Korea, 2012

2011

Complexity-Based Approach to Calibration with Checking Rules.

Dean P. Foster, Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari

Proceedings of the COLT 2011, 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

Domain Adaptation with Coupled Subspaces.

John Blitzer, Sham M. Kakade, Dean P. Foster

Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Domain Adaptation: Overfitting and Small Sample Statistics

Dean P. Foster, Sham M. Kakade, Ruslan Salakhutdinov

CoRR, 2011

Multi-View Learning of Word Embeddings via CCA.

Paramveer S. Dhillon, Dean P. Foster, Lyle H. Ungar

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

2010

Feature Selection using Multiple Streams.

Paramveer S. Dhillon, Dean P. Foster, Lyle H. Ungar

Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

A New Approach to Lexical Disambiguation of Arabic Text.

Rushin Shah, Paramveer S. Dhillon, Mark Liberman, Dean P. Foster, Mohamed Maamouri, Lyle H. Ungar

Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing, 2010

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

Transfer Learning Using Feature Selection

Paramveer S. Dhillon, Dean P. Foster, Lyle H. Ungar

CoRR, 2009

Multi-task Feature Selection Using the Multiple Inclusion Criterion (MIC).

Paramveer S. Dhillon, Brian Tomasik, Dean P. Foster, Lyle H. Ungar

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2009

VIF Regression: A Fast Regression Algorithm for Large Data.

Dongyu Lin, Dean P. Foster

Proceedings of the ICDM 2009, 2009

2008

Information Consistency of Nonparametric Gaussian Process Methods.

Matthias W. Seeger, Sham M. Kakade, Dean P. Foster

IEEE Trans. Inf. Theory, 2008

Deterministic calibration and Nash equilibrium.

Sham M. Kakade, Dean P. Foster

J. Comput. Syst. Sci., 2008

Efficient Feature Selection in the Presence of Multiple Feature Classes.

Paramveer S. Dhillon, Dean P. Foster, Lyle H. Ungar

Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), 2008

2007

Multi-view Regression Via Canonical Correlation Analysis.

Sham M. Kakade, Dean P. Foster

Proceedings of the Learning Theory, 20th Annual Conference on Learning Theory, 2007

2006

Streamwise Feature Selection.

Jing Zhou, Dean P. Foster, Robert A. Stine, Lyle H. Ungar

J. Mach. Learn. Res., 2006

Calibration via Regression.

Dean P. Foster, Sham M. Kakade

Proceedings of the 2006 IEEE Information Theory Workshop, 2006

2005

Worst-Case Bounds for Gaussian Process Models.

Sham M. Kakade, Matthias W. Seeger, Dean P. Foster

Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

Streaming feature selection using alpha-investing.

Jing Zhou, Dean P. Foster, Robert A. Stine, Lyle H. Ungar

Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2005

Streaming Feature Selection using IIC.

Lyle H. Ungar, Jing Zhou, Dean P. Foster, Bob A. Stine

Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005

2003

Learning, hypothesis testing, and Nash equilibrium.

Dean P. Foster, H. Peyton Young

Games Econ. Behav., 2003

2002

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

1999

Local Asymptotic Coding and the Minimum Description Length.

Dean P. Foster, Robert A. Stine

IEEE Trans. Inf. Theory, 1999

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

An Axiomatic Characterization of a Class of Locations in Tree Networks.

Dean P. Foster, Rakesh V. Vohra

Oper. Res., 1998

Accounting for Cognitive Costs in On-Line Auction Design.

David C. Parkes, Lyle H. Ungar, Dean P. Foster

Proceedings of the Agent Mediated Electronic Commerce, 1998

Basic Business Statistics - A Casebook.

Dean P. Foster, Robert A. Stine, Richard P. Waterman

Springer, ISBN: 978-0-387-98354-7, 1998

Business Analysis Using Regression - A Casebook.

Dean P. Foster, Robert A. Stine, Richard P. Waterman

Springer, ISBN: 978-0-387-98356-1, 1998

1997

Characterizing the generalization performance of model selection strategies.

Dale Schuurmans, Lyle H. Ungar, Dean P. Foster

Proceedings of the Fourteenth International Conference on Machine Learning (ICML 1997), 1997

1993

Reply to Professor Clemen.

Dean P. Foster, Rakesh V. Vohra

Oper. Res., 1993

A Randomization Rule for Selecting Forecasts.

Dean P. Foster, Rakesh V. Vohra

Oper. Res., 1993

1989

Probabilistic Analysis of a Heuristics for the Dual Bin Packing Problem.

Dean P. Foster, Rakesh Vohra

Inf. Process. Lett., 1989