Peter L. Bartlett
Orcid: 0000-0002-8760-3140Affiliations:
- University of California at Berkeley, Department of Statistics, CA, USA
According to our database1,
Peter L. Bartlett
authored at least 225 papers
between 1991 and 2024.
Collaborative distances:
Collaborative distances:
Awards
ACM Fellow
ACM Fellow 2018, "For contributions to the theory of machine learning".
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
Online presence:
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on zbmath.org
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on orcid.org
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on id.loc.gov
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on d-nb.info
On csauthors.net:
Bibliography
2024
Corrigendum to "Prediction, learning, uniform convergence, and scale-sensitive dimensions" [J. Comput. Syst. Sci. 56 (2) (1998) 174-190].
J. Comput. Syst. Sci., March, 2024
Large Stepsize Gradient Descent for Logistic Loss: Non-Monotonicity of the Loss Improves Optimization Efficiency.
CoRR, 2024
A Statistical Analysis of Wasserstein Autoencoders for Intrinsically Low-dimensional Data.
CoRR, 2024
In-Context Learning of a Linear Transformer Block: Benefits of the MLP Component and One-Step GD Initialization.
CoRR, 2024
On the Statistical Properties of Generative Adversarial Models for Low Intrinsic Data Dimension.
CoRR, 2024
2023
CoRR, 2023
The Double-Edged Sword of Implicit Bias: Generalization vs. Robustness in ReLU Networks.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Benign Overfitting in Linear Classifiers and Leaky ReLU Networks from KKT Conditions for Margin Maximization.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023
Proceedings of the International Conference on Algorithmic Learning Theory, 2023
2022
J. Mach. Learn. Res., 2022
The Interplay Between Implicit Bias and Benign Overfitting in Two-Layer Linear Networks.
J. Mach. Learn. Res., 2022
The Dynamics of Sharpness-Aware Minimization: Bouncing Across Ravines and Drifting Towards Wide Minima.
CoRR, 2022
Off-policy estimation of linear functionals: Non-asymptotic theory for semi-parametric efficiency.
CoRR, 2022
CoRR, 2022
Random Feature Amplification: Feature Learning and Generalization in Neural Networks.
CoRR, 2022
Optimal and instance-dependent guarantees for Markovian linear stochastic approximation.
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022
Benign Overfitting without Linearity: Neural Network Classifiers Trained by Gradient Descent for Noisy Linear Data.
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022
2021
J. Mach. Learn. Res., 2021
J. Mach. Learn. Res., 2021
J. Mach. Learn. Res., 2021
Infinite-Horizon Offline Reinforcement Learning with Linear Function Approximation: Curse of Dimensionality and Algorithm.
CoRR, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the 12th Innovations in Theoretical Computer Science Conference, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the Conference on Learning Theory, 2021
When does gradient descent with logistic loss interpolate using deep networks with smoothed ReLU activations?
Proceedings of the Conference on Learning Theory, 2021
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021
2020
Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems.
J. Mach. Learn. Res., 2020
CoRR, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
On Linear Stochastic Approximation: Fine-grained Polyak-Ruppert and Non-Asymptotic Concentration.
Proceedings of the Conference on Learning Theory, 2020
OSOM: A simultaneously optimal algorithm for multi-armed and linear contextual bandits.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
2019
Gradient Descent with Identity Initialization Efficiently Learns Positive-Definite Linear Transformations by Deep Residual Networks.
Neural Comput., 2019
Nearly-tight VC-dimension and Pseudodimension Bounds for Piecewise Linear Neural Networks.
J. Mach. Learn. Res., 2019
Learning Near-optimal Convex Combinations of Basis Models with Generalization Guarantees.
CoRR, 2019
Quantitative W<sub>1</sub> Convergence of Langevin-Like Stochastic Processes with Non-Convex Potential State-Dependent Noise.
CoRR, 2019
Proceedings of the 36th International Conference on Machine Learning, 2019
Proceedings of the 36th International Conference on Machine Learning, 2019
Proceedings of the 36th International Conference on Machine Learning, 2019
Proceedings of the 36th International Conference on Machine Learning, 2019
Proceedings of the Conference on Learning Theory, 2019
Proceedings of the Conference on Learning Theory, 2019
A simple parameter-free and adaptive approach to optimization under a minimal local smoothness assumption.
Proceedings of the Algorithmic Learning Theory, 2019
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019
2018
Gen-Oja: A Simple and Efficient Algorithm for Streaming Generalized Eigenvector Computation.
CoRR, 2018
Representing smooth functions as compositions of near-identity functions with implications for deep network optimization.
CoRR, 2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Gen-Oja: Simple & Efficient Algorithm for Streaming Generalized Eigenvector Computation.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Proceedings of the 35th International Conference on Machine Learning, 2018
Proceedings of the 35th International Conference on Machine Learning, 2018
Gradient descent with identity initialization efficiently learns positive definite linear transformations.
Proceedings of the 35th International Conference on Machine Learning, 2018
Proceedings of the 1st ACM SIGCAS Conference on Computing and Sustainable Societies, 2018
Proceedings of the Conference On Learning Theory, 2018
Proceedings of the Conference On Learning Theory, 2018
Proceedings of the Algorithmic Learning Theory, 2018
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018
2017
Exchangeability Characterizes Optimality of Sequential Normalized Maximum Likelihood and Bayesian Prediction.
IEEE Trans. Inf. Theory, 2017
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
Proceedings of the 34th International Conference on Machine Learning, 2017
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017
2016
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016
2015
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015
Large-Scale Markov Decision Problems with KL Control Cost and its Application to Crowdsourcing.
Proceedings of the 32nd International Conference on Machine Learning, 2015
Proceedings of The 28th Conference on Learning Theory, 2015
2014
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014
Proceedings of the 31th International Conference on Machine Learning, 2014
Proceedings of the 31th International Conference on Machine Learning, 2014
Proceedings of the 31th International Conference on Machine Learning, 2014
2013
Online Learning in Markov Decision Processes with Adversarially Chosen Transition Probability Distributions
CoRR, 2013
How to Hedge an Option Against an Adversary: Black-Scholes Pricing is Minimax Optimal.
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
Online Learning in Markov Decision Processes with Adversarially Chosen Transition Probability Distributions.
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
Proceedings of the COLT 2013, 2013
Proceedings of the COLT 2013, 2013
2012
Information-Theoretic Lower Bounds on the Oracle Complexity of Stochastic Convex Optimization.
IEEE Trans. Inf. Theory, 2012
IEEE Trans. Dependable Secur. Comput., 2012
J. Priv. Confidentiality, 2012
Exchangeability Characterizes Optimality of Sequential Normalized Maximum Likelihood and Bayesian Prediction with Jeffreys Prior.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012
The Optimality of Jeffreys Prior for Online Density Estimation and the Asymptotic Normality of Maximum Likelihood Estimators.
Proceedings of the COLT 2012, 2012
Proceedings of the 51th IEEE Conference on Decision and Control, 2012
2011
Proceedings of the COLT 2011, 2011
Proceedings of the COLT 2011, 2011
2010
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010
Corrigendum to "Shifting: One-inclusion mistake bounds and sample compression" [J. Comput. System Sci 75 (1) (2009) 37-59].
J. Comput. Syst. Sci., 2010
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010
Proceedings of the Discovery Science - 13th International Conference, 2010
Proceedings of the Algorithmic Learning Theory, 21st International Conference, 2010
2009
IEEE Signal Process. Mag., 2009
J. Comput. Syst. Sci., 2009
REGAL: A Regularization based Algorithm for Reinforcement Learning in Weakly Communicating MDPs.
Proceedings of the UAI 2009, 2009
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009
Proceedings of the COLT 2009, 2009
2008
IEEE Trans. Inf. Theory, 2008
Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks.
J. Mach. Learn. Res., 2008
Proceedings of the 21st Annual Conference on Learning Theory, 2008
Proceedings of the 21st Annual Conference on Learning Theory, 2008
Proceedings of the 1st ACM Workshop on Security and Artificial Intelligence, 2008
2007
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007
J. Mach. Learn. Res., 2007
Proceedings of the Advances in Neural Information Processing Systems 20, 2007
Proceedings of the Advances in Neural Information Processing Systems 20, 2007
Proceedings of the Learning Theory, 20th Annual Conference on Learning Theory, 2007
Proceedings of the Learning Theory, 20th Annual Conference on Learning Theory, 2007
2006
Proceedings of the Advances in Neural Information Processing Systems 19, 2006
Proceedings of the Advances in Neural Information Processing Systems 19, 2006
2004
J. Mach. Learn. Res., 2004
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004
Proceedings of the Learning Theory, 17th Annual Conference on Learning Theory, 2004
Proceedings of the Learning Theory, 17th Annual Conference on Learning Theory, 2004
2003
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003
2002
Theor. Comput. Sci., 2002
J. Mach. Learn. Res., 2002
J. Comput. Syst. Sci., 2002
Proceedings of the Advanced Lectures on Machine Learning, 2002
Learning the Kernel Matrix with Semi-Definite Programming.
Proceedings of the Machine Learning, 2002
Proceedings of the Computational Learning Theory, 2002
Cambridge University Press, ISBN: 978-0-521-57353-5, 2002
2001
J. Artif. Intell. Res., 2001
2000
Proceedings of the Advances in Neural Information Processing Systems 13, 2000
Proceedings of the IEEE International Symposium on Circuits and Systems, 2000
Reinforcement Learning in POMDP's via Direct Gradient Ascent.
Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000
Stochastic optimization of controlled partially observable Markov decision processes.
Proceedings of the 39th IEEE Conference on Decision and Control, 2000
1999
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999
1998
IEEE Trans. Inf. Theory, 1998
IEEE Trans. Inf. Theory, 1998
IEEE Trans. Inf. Theory, 1998
The Sample Complexity of Pattern Classification with Neural Networks: The Size of the Weights is More Important than the Size of the Network.
IEEE Trans. Inf. Theory, 1998
Neural Comput., 1998
J. Comput. Syst. Sci., 1998
Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998
Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998
1997
Correction to 'Lower Bounds on the VC-Dimension of Smoothly Parametrized Function Classes'.
Neural Comput., 1997
Proceedings of the Advances in Neural Information Processing Systems 10, 1997
Proceedings of the Advances in Neural Information Processing Systems 10, 1997
A Result Relating Convex <i>n</i>-Widths to Covering Numbers with some Applications to Neural Networks.
Proceedings of the Computational Learning Theory, Third European Conference, 1997
Proceedings of the Computational Learning Theory, Third European Conference, 1997
1996
IEEE Trans. Inf. Theory, 1996
The VC Dimension and Pseudodimension of Two-Layer Neural Networks with Discrete Inputs.
Neural Comput., 1996
J. Comput. Syst. Sci., 1996
For Valid Generalization the Size of the Weights is More Important than the Size of the Network.
Proceedings of the Advances in Neural Information Processing Systems 9, 1996
Proceedings of the Ninth Annual Conference on Computational Learning Theory, 1996
1995
Neural Comput., 1995
Proceedings of the Advances in Neural Information Processing Systems 8, 1995
Proceedings of the Eigth Annual Conference on Computational Learning Theory, 1995
Proceedings of the Eigth Annual Conference on Computational Learning Theory, 1995
1994
Proceedings of the Seventh Annual ACM Conference on Computational Learning Theory, 1994
1993
Neural Comput., 1993
Proceedings of the Sixth Annual ACM Conference on Computational Learning Theory, 1993
1992
IEEE Trans. Neural Networks, 1992
Proceedings of the Fifth Annual ACM Conference on Computational Learning Theory, 1992
1991
Proceedings of the Advances in Neural Information Processing Systems 4, 1991
Proceedings of the Fourth Annual Workshop on Computational Learning Theory, 1991