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Jason M. Altschuler
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- affiliation: Massachusetts Institute of Technology (MIT), Laboratory for Information and Decision Systems, Cambridge, MA, USA
- affiliation: Princeton University, NJ, USA
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2020 – today
- 2024
- [j14]Jason M. Altschuler
, Sinho Chewi
Faster High-accuracy Log-concave Sampling via Algorithmic Warm Starts. J. ACM 71(3): 24 (2024) - [j13]Jason M. Altschuler
On the Privacy of Noisy Stochastic Gradient Descent for Convex Optimization. SIAM J. Comput. 53(4): 969-1001 (2024) - [c10]Jinho Bok, Weijie J. Su, Jason M. Altschuler:
Shifted Interpolation for Differential Privacy. ICML 2024 - [i22]Jason M. Altschuler, Sinho Chewi:
Shifted Composition II: Shift Harnack Inequalities and Curvature Upper Bounds. CoRR abs/2401.00071 (2024) - [i21]Jinho Bok, Weijie Su, Jason M. Altschuler:
Shifted Interpolation for Differential Privacy. CoRR abs/2403.00278 (2024) - 2023
- [j12]Jason M. Altschuler
Near-linear convergence of the Random Osborne algorithm for Matrix Balancing. Math. Program. 198(1): 363-397 (2023) - [j11]Jason M. Altschuler
Polynomial-time algorithms for multimarginal optimal transport problems with structure. Math. Program. 199(1): 1107-1178 (2023) - [j10]Jason M. Altschuler
Kernel Approximation on Algebraic Varieties. SIAM J. Appl. Algebra Geom. 7(1): 1-28 (2023) - [c9]Jason M. Altschuler, Kunal Talwar:
Resolving the Mixing Time of the Langevin Algorithm to its Stationary Distribution for Log-Concave Sampling. COLT 2023: 2509-2510 - [c8]Jason M. Altschuler, Sinho Chewi:
Faster high-accuracy log-concave sampling via algorithmic warm starts. FOCS 2023: 2169-2176 - [i20]Jason M. Altschuler, Sinho Chewi:
Faster high-accuracy log-concave sampling via algorithmic warm starts. CoRR abs/2302.10249 (2023) - [i19]Jason M. Altschuler, Pablo A. Parrilo
Acceleration by Stepsize Hedging I: Multi-Step Descent and the Silver Stepsize Schedule. CoRR abs/2309.07879 (2023) - [i18]Jason M. Altschuler, Sinho Chewi:
Shifted Composition I: Harnack and Reverse Transport Inequalities. CoRR abs/2311.14520 (2023) - 2022
- [b1]Jason M. Altschuler:
Transport and Beyond: Efficient Optimization over Probability Distributions. MIT, USA, 2022 - [j9]Jason M. Altschuler
Approximating Min-Mean-Cycle for Low-Diameter Graphs in Near-Optimal Time and Memory. SIAM J. Optim. 32(3): 1791-1816 (2022) - [j8]Jason M. Altschuler
Asymptotics for Semidiscrete Entropic Optimal Transport. SIAM J. Math. Anal. 54(2): 1718-1741 (2022) - [j7]Jason M. Altschuler
Wasserstein Barycenters Are NP-Hard to Compute. SIAM J. Math. Data Sci. 4(1): 179-203 (2022) - [c7]Jason M. Altschuler, Kunal Talwar:
Privacy of Noisy Stochastic Gradient Descent: More Iterations without More Privacy Loss. NeurIPS 2022 - [i17]Jason M. Altschuler, Kunal Talwar:
Privacy of Noisy Stochastic Gradient Descent: More Iterations without More Privacy Loss. CoRR abs/2205.13710 (2022) - [i16]Jason M. Altschuler:
Flows, Scaling, and Entropy Revisited: a Unified Perspective via Optimizing Joint Distributions. CoRR abs/2210.16456 (2022) - [i15]Jason M. Altschuler, Kunal Talwar:
Concentration of the Langevin Algorithm's Stationary Distribution. CoRR abs/2212.12629 (2022) - 2021
- [j6]Jason M. Altschuler
Hardness results for Multimarginal Optimal Transport problems. Discret. Optim. 42: 100669 (2021) - [j5]Jason M. Altschuler, Enric Boix-Adserà:
Wasserstein barycenters can be computed in polynomial time in fixed dimension. J. Mach. Learn. Res. 22: 44:1-44:19 (2021) - [j4]Jason M. Altschuler
Online Learning over a Finite Action Set with Limited Switching. Math. Oper. Res. 46(1): 179-203 (2021) - [c6]Jason M. Altschuler, Sinho Chewi, Patrik Gerber, Austin J. Stromme:
Averaging on the Bures-Wasserstein manifold: dimension-free convergence of gradient descent. NeurIPS 2021: 22132-22145 - [i14]Jason M. Altschuler, Enric Boix-Adserà:
Wasserstein barycenters are NP-hard to compute. CoRR abs/2101.01100 (2021) - [i13]Jason M. Altschuler, Pablo A. Parrilo:
Kernel approximation on algebraic varieties. CoRR abs/2106.02755 (2021) - [i12]Jason M. Altschuler, Sinho Chewi, Patrik Gerber, Austin J. Stromme:
Averaging on the Bures-Wasserstein manifold: dimension-free convergence of gradient descent. CoRR abs/2106.08502 (2021) - 2020
- [j3]Jason M. Altschuler, Pablo A. Parrilo
Lyapunov Exponent of Rank-One Matrices: Ergodic Formula and Inapproximability of the Optimal Distribution. SIAM J. Control. Optim. 58(1): 510-528 (2020) - [i11]Jason M. Altschuler, Pablo A. Parrilo:
Random Osborne: a simple, practical algorithm for Matrix Balancing in near-linear time. CoRR abs/2004.02837 (2020) - [i10]Jason M. Altschuler, Pablo A. Parrilo:
Approximating Min-Mean-Cycle for low-diameter graphs in near-optimal time and memory. CoRR abs/2004.03114 (2020) - [i9]Jason M. Altschuler, Enric Boix-Adserà:
High-precision Wasserstein barycenters in polynomial time. CoRR abs/2006.08012 (2020) - [i8]Jason M. Altschuler, Enric Boix-Adserà:
Polynomial-time algorithms for Multimarginal Optimal Transport problems with structure. CoRR abs/2008.03006 (2020) - [i7]Jason M. Altschuler, Enric Boix-Adserà:
Hardness results for Multimarginal Optimal Transport problems. CoRR abs/2012.05398 (2020)
2010 – 2019
- 2019
- [j2]Jason M. Altschuler, Victor-Emmanuel Brunel, Alan Malek:
Best Arm Identification for Contaminated Bandits. J. Mach. Learn. Res. 20: 91:1-91:39 (2019) - [c5]Jason M. Altschuler, Pablo A. Parrilo
Lyapunov Exponent of Rank One Matrices: Ergodic Formula and Inapproximability of the Optimal Distribution. CDC 2019: 4439-4445 - [c4]Jason M. Altschuler, Francis R. Bach, Alessandro Rudi, Jonathan Niles-Weed:
Massively scalable Sinkhorn distances via the Nyström method. NeurIPS 2019: 4429-4439 - 2018
- [c3]Jason M. Altschuler, Kunal Talwar:
Online learning over a finite action set with limited switching. COLT 2018: 1569-1573 - [i6]Jason M. Altschuler, Victor-Emmanuel Brunel, Alan Malek:
Best Arm Identification for Contaminated Bandits. CoRR abs/1802.09514 (2018) - [i5]Jason M. Altschuler, Kunal Talwar:
Online learning over a finite action set with limited switching. CoRR abs/1803.01548 (2018) - [i4]Jason M. Altschuler, Francis R. Bach, Alessandro Rudi, Jonathan Weed:
Approximating the Quadratic Transportation Metric in Near-Linear Time. CoRR abs/1810.10046 (2018) - [i3]Jason M. Altschuler, Francis R. Bach, Alessandro Rudi, Jonathan Weed:
Massively scalable Sinkhorn distances via the Nyström method. CoRR abs/1812.05189 (2018) - 2017
- [j1]Jason M. Altschuler, Elizabeth Yang:
Inclusion of forbidden minors in random representable matroids. Discret. Math. 340(7): 1553-1563 (2017) - [c2]Jason M. Altschuler, Jonathan Weed, Philippe Rigollet:
Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration. NIPS 2017: 1964-1974 - [i2]Jason M. Altschuler, Jonathan Weed, Philippe Rigollet:
Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration. CoRR abs/1705.09634 (2017) - 2016
- [c1]Jason M. Altschuler, Aditya Bhaskara, Gang Fu, Vahab S. Mirrokni, Afshin Rostamizadeh, Morteza Zadimoghaddam:
Greedy Column Subset Selection: New Bounds and Distributed Algorithms. ICML 2016: 2539-2548 - [i1]Jason M. Altschuler, Aditya Bhaskara, Gang Fu, Vahab S. Mirrokni, Afshin Rostamizadeh, Morteza Zadimoghaddam:
Greedy Column Subset Selection: New Bounds and Distributed Algorithms. CoRR abs/1605.08795 (2016)
Coauthor Index
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