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2020 – today
- 2022
[i22]Allen Liu, Mark Sellke:
The Pareto Frontier of Instance-Dependent Guarantees in Multi-Player Multi-Armed Bandits with no Communication. CoRR abs/2202.09653 (2022)- [i21]Ahmed El Alaoui, Andrea Montanari, Mark Sellke:
Sampling from the Sherrington-Kirkpatrick Gibbs measure via algorithmic stochastic localization. CoRR abs/2203.05093 (2022) - 2021
- [j1]Victoria Kostina
, Yuval Peres, Gireeja Ranade, Mark Sellke:
Stabilizing a System With an Unbounded Random Gain Using Only Finitely Many Bits. IEEE Trans. Inf. Theory 67(4): 2554-2561 (2021) - [c13]Sébastien Bubeck, Thomas Budzinski, Mark Sellke:
Cooperative and Stochastic Multi-Player Multi-Armed Bandit: Optimal Regret With Neither Communication Nor Collisions. COLT 2021: 821-822 - [c12]Sébastien Bubeck, Niv Buchbinder, Christian Coester, Mark Sellke:
Metrical Service Systems with Transformations. ITCS 2021: 21:1-21:20 - [c11]Sébastien Bubeck, Mark Sellke:
A Universal Law of Robustness via Isoperimetry. NeurIPS 2021: 28811-28822 - [c10]Mark Sellke, Aleksandrs Slivkins:
The Price of Incentivizing Exploration: A Characterization via Thompson Sampling and Sample Complexity. EC 2021: 795-796 - [c9]Parinya Chalermsook, Syamantak Das, Yunbum Kook, Bundit Laekhanukit, Yang P. Liu, Richard Peng, Mark Sellke, Daniel Vaz:
Vertex Sparsification for Edge Connectivity. SODA 2021: 1206-1225 - [c8]Sébastien Bubeck, Yuval Rabani, Mark Sellke:
Online Multiserver Convex Chasing and Optimization. SODA 2021: 2093-2104 - [i20]Sébastien Bubeck, Mark Sellke:
A Universal Law of Robustness via Isoperimetry. CoRR abs/2105.12806 (2021) - [i19]Yining Chen, Elan Rosenfeld, Mark Sellke, Tengyu Ma, Andrej Risteski:
Iterative Feature Matching: Toward Provable Domain Generalization with Logarithmic Environments. CoRR abs/2106.09913 (2021) - [i18]Brice Huang, Mark Sellke:
Tight Lipschitz Hardness for Optimizing Mean Field Spin Glasses. CoRR abs/2110.07847 (2021) - [i17]Ahmed El Alaoui, Andrea Montanari, Mark Sellke:
Local algorithms for Maximum Cut and Minimum Bisection on locally treelike regular graphs of large degree. CoRR abs/2111.06813 (2021) - 2020
- [c7]Sébastien Bubeck, Mark Sellke:
First-Order Bayesian Regret Analysis of Thompson Sampling. ALT 2020: 196-233 - [c6]Sébastien Bubeck, Yuanzhi Li, Yuval Peres, Mark Sellke:
Non-Stochastic Multi-Player Multi-Armed Bandits: Optimal Rate With Collision Information, Sublinear Without. COLT 2020: 961-987 - [c5]Sébastien Bubeck, Bo'az Klartag, Yin Tat Lee, Yuanzhi Li, Mark Sellke:
Chasing Nested Convex Bodies Nearly Optimally. SODA 2020: 1496-1508 - [c4]Mark Sellke:
Chasing Convex Bodies Optimally. SODA 2020: 1509-1518 - [i16]Mark Sellke, Aleksandrs Slivkins:
Sample Complexity of Incentivized Exploration. CoRR abs/2002.00558 (2020) - [i15]Sébastien Bubeck, Yuval Rabani, Mark Sellke:
Online Multiserver Convex Chasing and Optimization. CoRR abs/2004.07346 (2020) - [i14]Parinya Chalermsook, Syamantak Das, Bundit Laekhanukit, Yunbum Kook, Yang P. Liu, Richard Peng, Mark Sellke, Daniel Vaz:
Vertex Sparsification for Edge Connectivity. CoRR abs/2007.07862 (2020) - [i13]Sébastien Bubeck, Niv Buchbinder, Christian Coester, Mark Sellke:
Metrical Service Systems with Transformations. CoRR abs/2009.08266 (2020) - [i12]Ahmed El Alaoui, Mark Sellke:
Algorithmic pure states for the negative spherical perceptron. CoRR abs/2010.15811 (2020) - [i11]Sébastien Bubeck, Thomas Budzinski, Mark Sellke:
Cooperative and Stochastic Multi-Player Multi-Armed Bandit: Optimal Regret With Neither Communication Nor Collisions. CoRR abs/2011.03896 (2020) - [i10]Timothy Chu, Gary L. Miller, Shyam Narayanan, Mark Sellke:
Functions that Preserve Manhattan Distances. CoRR abs/2011.11503 (2020)
2010 – 2019
- 2019
- [c3]Sébastien Bubeck, Yin Tat Lee, Yuanzhi Li, Mark Sellke:
Competitively chasing convex bodies. STOC 2019: 861-868 - [i9]Sébastien Bubeck, Mark Sellke:
First-Order Regret Analysis of Thompson Sampling. CoRR abs/1902.00681 (2019) - [i8]Sébastien Bubeck, Yuanzhi Li, Yuval Peres, Mark Sellke:
Non-Stochastic Multi-Player Multi-Armed Bandits: Optimal Rate With Collision Information, Sublinear Without. CoRR abs/1904.12233 (2019) - [i7]Mark Sellke:
Chasing Convex Bodies Optimally. CoRR abs/1905.11968 (2019) - [i6]Yang P. Liu, Richard Peng, Mark Sellke:
Vertex Sparsifiers for c-Edge Connectivity. CoRR abs/1910.10359 (2019) - 2018
- [c2]Victoria Kostina, Yuval Peres, Gireeja Ranade, Mark Sellke:
Exact minimum number of bits to stabilize a linear system. CDC 2018: 453-458 - [c1]Victoria Kostina, Yuval Peres, Gireeja Ranade, Mark Sellke:
Stabilizing a System with an Unbounded Random Gain Using Only Finitely Many Bits. ISIT 2018: 2256-2260 - [i5]Victoria Kostina, Yuval Peres, Gireeja Ranade, Mark Sellke:
Stabilizing a system with an unbounded random gain using only a finite number of bits. CoRR abs/1805.05535 (2018) - [i4]Victoria Kostina, Yuval Peres, Gireeja Ranade, Mark Sellke:
Exact minimum number of bits to stabilize a linear system. CoRR abs/1807.07686 (2018) - [i3]Sébastien Bubeck, Yin Tat Lee, Yuanzhi Li, Mark Sellke:
Competitively Chasing Convex Bodies. CoRR abs/1811.00887 (2018) - [i2]Sébastien Bubeck, Yin Tat Lee, Yuanzhi Li, Mark Sellke:
Chasing Nested Convex Bodies Nearly Optimally. CoRR abs/1811.00999 (2018) - 2017
- [i1]Boris Hanin, Mark Sellke:
Approximating Continuous Functions by ReLU Nets of Minimal Width. CoRR abs/1710.11278 (2017)
Coauthor Index
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