Yin Tat Lee
Orcid: 0000-0002-4692-5442
According to our database1,
Yin Tat Lee
authored at least 117 papers
between 2013 and 2024.
Collaborative distances:
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Bibliography
2024
CoRR, 2024
Proceedings of the 56th Annual ACM Symposium on Theory of Computing, 2024
Proceedings of the 2024 ACM-SIAM Symposium on Discrete Algorithms, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
2023
Can Generalist Foundation Models Outcompete Special-Purpose Tuning? Case Study in Medicine.
CoRR, 2023
Proceedings of the 55th Annual ACM Symposium on Theory of Computing, 2023
Proceedings of the 2023 ACM-SIAM Symposium on Discrete Algorithms, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the 64th IEEE Annual Symposium on Foundations of Computer Science, 2023
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023
Condition-number-independent Convergence Rate of Riemannian Hamiltonian Monte Carlo with Numerical Integrators.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023
Algorithmic Aspects of the Log-Laplace Transform and a Non-Euclidean Proximal Sampler.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023
2022
Proceedings of the STOC '22: 54th Annual ACM SIGACT Symposium on Theory of Computing, Rome, Italy, June 20, 2022
Proceedings of the 2022 ACM-SIAM Symposium on Discrete Algorithms, 2022
Proceedings of the 2022 ACM-SIAM Symposium on Discrete Algorithms, 2022
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
Decomposable Non-Smooth Convex Optimization with Nearly-Linear Gradient Oracle Complexity.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
A gradient sampling method with complexity guarantees for Lipschitz functions in high and low dimensions.
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 49th International Colloquium on Automata, Languages, and Programming, 2022
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022
2021
SIAM J. Comput., 2021
Private Non-smooth Empirical Risk Minimization and Stochastic Convex Optimization in Subquadratic Steps.
CoRR, 2021
Reducing isotropy and volume to KLS: an <i>o</i>*(<i>n</i><sup>3</sup><i>ψ</i><sup>2</sup>) volume algorithm.
Proceedings of the STOC '21: 53rd Annual ACM SIGACT Symposium on Theory of Computing, 2021
A nearly-linear time algorithm for linear programs with small treewidth: a multiscale representation of robust central path.
Proceedings of the STOC '21: 53rd Annual ACM SIGACT Symposium on Theory of Computing, 2021
Minimum cost flows, MDPs, and ℓ<sub>1</sub>-regression in nearly linear time for dense instances.
Proceedings of the STOC '21: 53rd Annual ACM SIGACT Symposium on Theory of Computing, 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 Conference on Learning Theory, 2021
2020
Reducing Isotropy and Volume to KLS: An O(n<sup>3</sup>ψ<sup>2</sup>) Volume Algorithm.
CoRR, 2020
CoRR, 2020
Proceedings of the 52nd Annual ACM SIGACT Symposium on Theory of Computing, 2020
An improved cutting plane method for convex optimization, convex-concave games, and its applications.
Proceedings of the 52nd Annual ACM SIGACT Symposium on Theory of Computing, 2020
Proceedings of the 52nd Annual ACM SIGACT Symposium on Theory of Computing, 2020
Proceedings of the 52nd Annual ACM SIGACT Symposium on Theory of Computing, 2020
Proceedings of the 2020 ACM-SIAM Symposium on Discrete Algorithms, 2020
Proceedings of the 2020 ACM-SIAM Symposium on Discrete Algorithms, 2020
Proceedings of the 2020 ACM-SIAM Symposium on Discrete Algorithms, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Network size and size of the weights in memorization with two-layers neural networks.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the 40th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science, 2020
Proceedings of the 61st IEEE Annual Symposium on Foundations of Computer Science, 2020
Proceedings of the 61st IEEE Annual Symposium on Foundations of Computer Science, 2020
Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized Hamiltonian Monte Carlo.
Proceedings of the Conference on Learning Theory, 2020
An $\widetilde\mathcalO(m/\varepsilon^3.5)$-Cost Algorithm for Semidefinite Programs with Diagonal Constraints.
Proceedings of the Conference on Learning Theory, 2020
Proceedings of the Algorithmic Learning Theory, 2020
2019
J. Mach. Learn. Res., 2019
An Õ(m/ε<sup>3.5</sup>)-Cost Algorithm for Semidefinite Programs with Diagonal Constraints.
CoRR, 2019
Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing, 2019
Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete Algorithms, 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 36th International Conference on Machine Learning, 2019
Proceedings of the 60th IEEE Annual Symposium on Foundations of Computer Science, 2019
Proceedings of the Conference on Learning Theory, 2019
Near Optimal Methods for Minimizing Convex Functions with Lipschitz $p$-th Derivatives.
Proceedings of the Conference on Learning Theory, 2019
Proceedings of the Conference on Learning Theory, 2019
Proceedings of the Conference on Learning Theory, 2019
2018
SIAM J. Comput., 2018
CoRR, 2018
Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing, 2018
Convergence rate of riemannian Hamiltonian Monte Carlo and faster polytope volume computation.
Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing, 2018
Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing, 2018
Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing, 2018
Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing, 2018
An homotopy method for l<sub>p</sub> regression provably beyond self-concordance and in input-sparsity time.
Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing, 2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Proceedings of the Conference On Learning Theory, 2018
2017
Improved Cheeger's Inequality and Analysis of Local Graph Partitioning using Vertex Expansion and Expansion Profile.
SIAM J. Comput., 2017
Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing, 2017
Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing, 2017
Optimal Algorithms for Smooth and Strongly Convex Distributed Optimization in Networks.
Proceedings of the 34th International Conference on Machine Learning, 2017
Eldan's Stochastic Localization and the KLS Hyperplane Conjecture: An Improved Lower Bound for Expansion.
Proceedings of the 58th IEEE Annual Symposium on Foundations of Computer Science, 2017
2016
Landmark-Matching Transformation with Large Deformation Via n-dimensional Quasi-conformal Maps.
J. Sci. Comput., 2016
Proceedings of the 48th Annual ACM SIGACT Symposium on Theory of Computing, 2016
Proceedings of the 48th Annual ACM SIGACT Symposium on Theory of Computing, 2016
Using Optimization to Obtain a Width-Independent, Parallel, Simpler, and Faster Positive SDP Solver.
Proceedings of the Twenty-Seventh Annual ACM-SIAM Symposium on Discrete Algorithms, 2016
Proceedings of the 33nd International Conference on Machine Learning, 2016
2015
Proceedings of the 2015 Conference on Innovations in Theoretical Computer Science, 2015
A Faster Cutting Plane Method and its Implications for Combinatorial and Convex Optimization.
Proceedings of the IEEE 56th Annual Symposium on Foundations of Computer Science, 2015
Proceedings of the IEEE 56th Annual Symposium on Foundations of Computer Science, 2015
2014
An Almost-Linear-Time Algorithm for Approximate Max Flow in Undirected Graphs, and its Multicommodity Generalizations.
Proceedings of the Twenty-Fifth Annual ACM-SIAM Symposium on Discrete Algorithms, 2014
Path Finding Methods for Linear Programming: Solving Linear Programs in Õ(vrank) Iterations and Faster Algorithms for Maximum Flow.
Proceedings of the 55th IEEE Annual Symposium on Foundations of Computer Science, 2014
2013
Following the Path of Least Resistance : An Õ(m sqrt(n)) Algorithm for the Minimum Cost Flow Problem.
CoRR, 2013
Matching the Universal Barrier Without Paying the Costs : Solving Linear Programs with Õ(sqrt(rank)) Linear System Solves.
CoRR, 2013
Proceedings of the Symposium on Theory of Computing Conference, 2013
Improved Cheeger's inequality: analysis of spectral partitioning algorithms through higher order spectral gap.
Proceedings of the Symposium on Theory of Computing Conference, 2013
Efficient Accelerated Coordinate Descent Methods and Faster Algorithms for Solving Linear Systems.
Proceedings of the 54th Annual IEEE Symposium on Foundations of Computer Science, 2013