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20192023
most citedOnline Learning for Stochastic Shortest Path Model via Posterior Sampling

6 citations · 11 across the 9 of their papers we have counts for

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Showing 2021Show all

5 papers · 1 filter

cs.LG2021

Improved No-Regret Algorithms for Stochastic Shortest Path with Linear MDP

Liyu Chen, Rahul Jain, Haipeng Luo

We introduce two new no-regret algorithms for the stochastic shortest path (SSP) problem with a linear MDP that significantly improve over the only existing results of (Vial et al.…

cs.LG2021★ 6 cited

Online Learning for Stochastic Shortest Path Model via Posterior Sampling

Mehdi Jafarnia-Jahromi, Liyu Chen, Rahul Jain +1

We consider the problem of online reinforcement learning for the Stochastic Shortest Path (SSP) problem modeled as an unknown MDP with an absorbing state. We propose PSRL-SSP, a si…

cs.LG2021

Implicit Finite-Horizon Approximation and Efficient Optimal Algorithms for Stochastic Shortest Path

Liyu Chen, Mehdi Jafarnia-Jahromi, Rahul Jain +1

We introduce a generic template for developing regret minimization algorithms in the Stochastic Shortest Path (SSP) model, which achieves minimax optimal regret as long as certain…

cs.LG2021

Finding the Stochastic Shortest Path with Low Regret: The Adversarial Cost and Unknown Transition Case

Liyu Chen, Haipeng Luo

We make significant progress toward the stochastic shortest path problem with adversarial costs and unknown transition. Specifically, we develop algorithms that achieve $\widetilde…

cs.LG2021

Impossible Tuning Made Possible: A New Expert Algorithm and Its Applications

Liyu Chen, Haipeng Luo, Chen-Yu Wei

We resolve the long-standing "impossible tuning" issue for the classic expert problem and show that, it is in fact possible to achieve regret $O\left(\sqrt{(\ln d)\sum_t \ell_{t,i}…