September 8, 2024
tac_drc_po
Wasserstein distributionally robust control of partially observable linear stochastic systems Astghik Hakobyan, and Insoon Yang…
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September 8, 2024
tcst_vessel
Risk-aware Wasserstein distributionally robust control of vessels in natural waterways Juan Moreno Nadales, Astghik Hakobyan,…
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September 8, 2024
l4dc_metarl
On task-relevant loss functions in meta-reinforcement learning Jaeuk Shin, Giho Kim, Howon Lee, Joonho Han,…
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September 8, 2024
lcss_multi
Multiparametric analysis of multi-task Markov decision processes: Structure, invariance, and reducibility Jaeuk Shin, and Insoon…
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September 8, 2024
lcss_regret
Wasserstein distributionally robust regret minimization Youngchae Cho, and Insoon Yang IEEE Control Systems Letters, 8:820-825,…
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September 8, 2024
Aut_pomdp
Anderson acceleration for partially observable Markov decision processes: A maximum entropy approach Mingyu Park, Jaeuk…
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September 29, 2023
[NeurIPS] Analysis of ODE models for accelerated methods via positive semidefinite kernels
The paper “Convergence analysis of ODE models for accelerated first-order methods via positive semidefinite kernels,”…
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September 29, 2023
[CDC] 3 papers
The following three papers from our group have been accepted for presentation at the 62nd…
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September 29, 2023
neurips23
Convergence analysis of ODE models for accelerated first-order methods via positive semidefinite kernels Jungbin Kim,…
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September 29, 2023
t-ase23
Control of fab lifters via deep reinforcement learning: A semi-MDP approach Giho Kim, Jaeuk Shin,…
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