Jason M. Altschuler

Orcid: 0000-0001-7367-0097

Affiliations:
  • Massachusetts Institute of Technology (MIT), Laboratory for Information and Decision Systems, Cambridge, MA, USA
  • Princeton University, NJ, USA


According to our database1, Jason M. Altschuler authored at least 28 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Shifted Interpolation for Differential Privacy.
CoRR, 2024

Shifted Composition II: Shift Harnack Inequalities and Curvature Upper Bounds.
CoRR, 2024

2023
Polynomial-time algorithms for multimarginal optimal transport problems with structure.
Math. Program., May, 2023

Kernel Approximation on Algebraic Varieties.
SIAM J. Appl. Algebra Geom., March, 2023

Near-linear convergence of the Random Osborne algorithm for Matrix Balancing.
Math. Program., March, 2023

Shifted Composition I: Harnack and Reverse Transport Inequalities.
CoRR, 2023

Acceleration by Stepsize Hedging I: Multi-Step Descent and the Silver Stepsize Schedule.
CoRR, 2023

Faster high-accuracy log-concave sampling via algorithmic warm starts.
Proceedings of the 64th IEEE Annual Symposium on Foundations of Computer Science, 2023

Resolving the Mixing Time of the Langevin Algorithm to its Stationary Distribution for Log-Concave Sampling.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2022
Approximating Min-Mean-Cycle for Low-Diameter Graphs in Near-Optimal Time and Memory.
SIAM J. Optim., September, 2022

Wasserstein Barycenters Are NP-Hard to Compute.
SIAM J. Math. Data Sci., 2022

Asymptotics for Semidiscrete Entropic Optimal Transport.
SIAM J. Math. Anal., 2022

Concentration of the Langevin Algorithm's Stationary Distribution.
CoRR, 2022

Flows, Scaling, and Entropy Revisited: a Unified Perspective via Optimizing Joint Distributions.
CoRR, 2022

Privacy of Noisy Stochastic Gradient Descent: More Iterations without More Privacy Loss.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
Online Learning over a Finite Action Set with Limited Switching.
Math. Oper. Res., 2021

Wasserstein barycenters can be computed in polynomial time in fixed dimension.
J. Mach. Learn. Res., 2021

Hardness results for Multimarginal Optimal Transport problems.
Discret. Optim., 2021

Averaging on the Bures-Wasserstein manifold: dimension-free convergence of gradient descent.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020
Lyapunov Exponent of Rank-One Matrices: Ergodic Formula and Inapproximability of the Optimal Distribution.
SIAM J. Control. Optim., 2020

High-precision Wasserstein barycenters in polynomial time.
CoRR, 2020

Random Osborne: a simple, practical algorithm for Matrix Balancing in near-linear time.
CoRR, 2020

2019
Best Arm Identification for Contaminated Bandits.
J. Mach. Learn. Res., 2019

Massively scalable Sinkhorn distances via the Nyström method.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018
Approximating the Quadratic Transportation Metric in Near-Linear Time.
CoRR, 2018

2017
Inclusion of forbidden minors in random representable matroids.
Discret. Math., 2017

Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016
Greedy Column Subset Selection: New Bounds and Distributed Algorithms.
Proceedings of the 33nd International Conference on Machine Learning, 2016


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