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20202026
most citedInfoNCE Loss Provably Learns Cluster-Preserving Representations

9 citations · 20 across the 10 of their papers we have counts for

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cs.LG2021★ 1 cited

Improved Algorithms for Misspecified Linear Markov Decision Processes

Daniel Vial, Advait Parulekar, Sanjay Shakkottai +1

For the misspecified linear Markov decision process (MLMDP) model of Jin et al. [2020], we propose an algorithm with three desirable properties. (P1) Its regret after episodes…

cs.LG2021

L1 Regression with Lewis Weights Subsampling

Aditya Parulekar, Advait Parulekar, Eric Price

We consider the problem of finding an approximate solution to regression while only observing a small number of labels. Given an unlabeled data matrix , we…

cs.LG2021★ 4 cited

Regret Bounds for Stochastic Shortest Path Problems with Linear Function Approximation

Daniel Vial, Advait Parulekar, Sanjay Shakkottai +1

We propose an algorithm that uses linear function approximation (LFA) for stochastic shortest path (SSP). Under minimal assumptions, it obtains sublinear regret, is computationally…