Jason D. Lee
Orcid: 0000-0003-0064-7800Affiliations:
- Stanford University, Institute of Computational and Mathematical Engineering
According to our database1,
Jason D. Lee
authored at least 163 papers
between 2007 and 2024.
Collaborative distances:
Collaborative distances:
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on orcid.org
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on stanford.edu
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Bibliography
2024
Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark.
CoRR, 2024
CoRR, 2024
2023
Policy Mirror Descent for Regularized Reinforcement Learning: A Generalized Framework with Linear Convergence.
SIAM J. Optim., June, 2023
CoRR, 2023
Sample Complexity for Quadratic Bandits: Hessian Dependent Bounds and Optimal Algorithms.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Smoothing the Landscape Boosts the Signal for SGD: Optimal Sample Complexity for Learning Single Index Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Reward-agnostic Fine-tuning: Provable Statistical Benefits of Hybrid Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Learning for Dynamics and Control Conference, 2023
Computationally Efficient PAC RL in POMDPs with Latent Determinism and Conditional Embeddings.
Proceedings of the International Conference on Machine Learning, 2023
Understanding Incremental Learning of Gradient Descent: A Fine-grained Analysis of Matrix Sensing.
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Decentralized Optimistic Hyperpolicy Mirror Descent: Provably No-Regret Learning in Markov Games.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023
Optimal Sample Complexity Bounds for Non-convex Optimization under Kurdyka-Lojasiewicz Condition.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023
2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
On the Effective Number of Linear Regions in Shallow Univariate ReLU Networks: Convergence Guarantees and Implicit Bias.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Identifying good directions to escape the NTK regime and efficiently learn low-degree plus sparse polynomials.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Implicit Bias of Gradient Descent on Reparametrized Models: On Equivalence to Mirror Descent.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the IEEE International Conference on Acoustics, 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
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022
2021
IEEE Trans. Signal Process., 2021
On the Theory of Policy Gradient Methods: Optimality, Approximation, and Distribution Shift.
J. Mach. Learn. Res., 2021
CoRR, 2021
MUSBO: Model-based Uncertainty Regularized and Sample Efficient Batch Optimization for Deployment Constrained Reinforcement Learning.
CoRR, 2021
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 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 38th International Conference on Machine Learning, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 9th International Conference on Learning Representations, 2021
Proceedings of the 9th International Conference on Learning Representations, 2021
Proceedings of the Conference on Learning Theory, 2021
Modeling from Features: a Mean-field Framework for Over-parameterized Deep Neural Networks.
Proceedings of the Conference on Learning Theory, 2021
2020
Found. Comput. Math., 2020
CoRR, 2020
Steepest Descent Neural Architecture Optimization: Escaping Local Optimum with Signed Neural Splitting.
CoRR, 2020
Agnostic Q-learning with Function Approximation in Deterministic Systems: Tight Bounds on Approximation Error and Sample Complexity.
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
Implicit Bias in Deep Linear Classification: Initialization Scale vs Training Accuracy.
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 Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
How to Characterize The Landscape of Overparameterized Convolutional Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Agnostic $Q$-learning with Function Approximation in Deterministic Systems: Near-Optimal Bounds on Approximation Error and Sample Complexity.
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 37th International Conference on Machine Learning, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Beyond Linearization: On Quadratic and Higher-Order Approximation of Wide Neural Networks.
Proceedings of the 8th International Conference on Learning Representations, 2020
Proceedings of the Conference on Learning Theory, 2020
Optimality and Approximation with Policy Gradient Methods in Markov Decision Processes.
Proceedings of the Conference on Learning Theory, 2020
2019
Theoretical Insights Into the Optimization Landscape of Over-Parameterized Shallow Neural Networks.
IEEE Trans. Inf. Theory, 2019
CoRR, 2019
Regularization Matters: Generalization and Optimization of Neural Nets v.s. their Induced Kernel.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Lexicographic and Depth-Sensitive Margins in Homogeneous and Non-Homogeneous Deep Models.
Proceedings of the 36th International Conference on Machine Learning, 2019
Proceedings of the 36th International Conference on Machine Learning, 2019
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019
2018
CoRR, 2018
Gradient Primal-Dual Algorithm Converges to Second-Order Stationary Solutions for Nonconvex Distributed Optimization.
CoRR, 2018
On the Convergence and Robustness of Training GANs with Regularized Optimal Transport.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Algorithmic Regularization in Learning Deep Homogeneous Models: Layers are Automatically Balanced.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Gradient Primal-Dual Algorithm Converges to Second-Order Stationary Solution for Nonconvex Distributed Optimization Over Networks.
Proceedings of the 35th International Conference on Machine Learning, 2018
Proceedings of the 35th International Conference on Machine Learning, 2018
Gradient Descent Learns One-hidden-layer CNN: Don't be Afraid of Spurious Local Minima.
Proceedings of the 35th International Conference on Machine Learning, 2018
Proceedings of the 35th International Conference on Machine Learning, 2018
Proceedings of the 6th International Conference on Learning Representations, 2018
Proceedings of the 6th International Conference on Learning Representations, 2018
Proceedings of the 6th International Conference on Learning Representations, 2018
2017
Distributed Stochastic Variance Reduced Gradient Methods by Sampling Extra Data with Replacement.
J. Mach. Learn. Res., 2017
CoRR, 2017
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017
Sketching Meets Random Projection in the Dual: A Provable Recovery Algorithm for Big and High-dimensional Data.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017
2016
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016
Proceedings of the 33nd International Conference on Machine Learning, 2016
Proceedings of the 33nd International Conference on Machine Learning, 2016
Proceedings of the 29th Conference on Learning Theory, 2016
2015
J. Mach. Learn. Res., 2015
ℓ<sub>1</sub>-regularized Neural Networks are Improperly Learnable in Polynomial Time.
CoRR, 2015
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015
2014
SIAM J. Optim., 2014
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014
Scalable Methods for Nonnegative Matrix Factorizations of Near-separable Tall-and-skinny Matrices.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014
2013
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 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 Sixteenth International Conference on Artificial Intelligence and Statistics, 2013
2012
Proximal Newton-type Methods for Minimizing Convex Objective Functions in Composite Form
CoRR, 2012
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012
2010
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010
2009
A distributed concurrent on-line test scheduling protocol for many-core NoC-based systems.
Proceedings of the 27th International Conference on Computer Design, 2009
2008
Proceedings of the 9th International Symposium on Quality of Electronic Design (ISQED 2008), 2008
Proceedings of the 26th International Conference on Computer Design, 2008
2007
Proceedings of the 2007 International Symposium on Low Power Electronics and Design, 2007
A Safety Analysis Framework for COTS Microprocessors in Safety-Critical Applications.
Proceedings of the Tenth IEEE International Symposium on High Assurance Systems Engineering (HASE 2007), 2007