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Stas Tiomkin
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2020 – today
- 2024
- [j3]Derek Lilienthal
, Paul Mello
Multi-Resolution Diffusion for Privacy-Sensitive Recommender Systems. IEEE Access 12: 58275-58287 (2024) - [c11]Suruchi Sharma, Volodymyr Makarenko, Gautam Kumar, Stas Tiomkin:
Controllability-Constrained Deep Network Models for Enhanced Control of Dynamical Systems. ACC 2024: 159-166 - [c10]Wooyoung Chung, Daniel Polani, Stas Tiomkin:
Dimensionality Reduction of Dynamics on Lie Groups via Structure-Aware Canonical Correlation Analysis. ACC 2024: 439-446 - [i21]Nadav Amir, Stas Tiomkin, Angela Langdon:
Learning telic-controllable state representations. CoRR abs/2406.14476 (2024) - [i20]Jacob Adamczyk, Volodymyr Makarenko, Stas Tiomkin, Rahul V. Kulkarni:
Boosting Soft Q-Learning by Bounding. CoRR abs/2406.18033 (2024) - 2023
- [c9]Jacob Adamczyk, Argenis Arriojas, Stas Tiomkin, Rahul V. Kulkarni:
Utilizing Prior Solutions for Reward Shaping and Composition in Entropy-Regularized Reinforcement Learning. AAAI 2023: 6658-6665 - [c8]Jacob Adamczyk, Volodymyr Makarenko, Argenis Arriojas, Stas Tiomkin, Rahul V. Kulkarni:
Bounding the optimal value function in compositional reinforcement learning. UAI 2023: 22-32 - [c7]Argenis Arriojas, Jacob Adamczyk, Stas Tiomkin, Rahul V. Kulkarni:
Bayesian inference approach for entropy regularized reinforcement learning with stochastic dynamics. UAI 2023: 99-109 - [i19]Stas Tiomkin, Ilya Nemenman, Daniel Polani, Naftali Tishby:
Intrinsic Motivation in Dynamical Control Systems. CoRR abs/2301.00005 (2023) - [i18]Jacob Adamczyk, Stas Tiomkin, Rahul V. Kulkarni:
Compositionality and Bounds for Optimal Value Functions in Reinforcement Learning. CoRR abs/2302.09676 (2023) - [i17]Jacob Adamczyk, Volodymyr Makarenko, Argenis Arriojas, Stas Tiomkin, Rahul V. Kulkarni:
Bounding the Optimal Value Function in Compositional Reinforcement Learning. CoRR abs/2303.02557 (2023) - [i16]Derek Lilienthal, Paul Mello, Magdalini Eirinaki, Stas Tiomkin:
Multi-Resolution Diffusion for Privacy-Sensitive Recommender Systems. CoRR abs/2311.03488 (2023) - [i15]Suruchi Sharma, Volodymyr Makarenko, Gautam Kumar, Stas Tiomkin:
Controllability-Constrained Deep Network Models for Enhanced Control of Dynamical Systems. CoRR abs/2311.06438 (2023) - [i14]Wooyoung Chung, Daniel Polani, Stas Tiomkin:
Dimensionality Reduction of Dynamics on Lie Manifolds via Structure-Aware Canonical Correlation Analysis. CoRR abs/2311.10327 (2023) - [i13]Tristan Shah, Feruza Amirkulova, Stas Tiomkin:
Taming Waves: A Physically-Interpretable Machine Learning Framework for Realizable Control of Wave Dynamics. CoRR abs/2312.09460 (2023) - 2022
- [c6]Kyle Hollins Wray, Stas Tiomkin, Mykel J. Kochenderfer
Multi-Objective Policy Gradients with Topological Constraints. IROS 2022: 9034-9039 - [i12]Kyle Hollins Wray, Stas Tiomkin, Mykel J. Kochenderfer, Pieter Abbeel:
Multi-Objective Policy Gradients with Topological Constraints. CoRR abs/2209.07096 (2022) - [i11]Jacob Adamczyk, Argenis Arriojas, Stas Tiomkin, Rahul V. Kulkarni:
Utilizing Prior Solutions for Reward Shaping and Composition in Entropy-Regularized Reinforcement Learning. CoRR abs/2212.01174 (2022) - 2021
- [c5]Ruihan Zhao, Kevin Lu, Pieter Abbeel, Stas Tiomkin:
Efficient Empowerment Estimation for Unsupervised Stabilization. ICLR 2021 - [i10]Philippe Hansen-Estruch, Wenling Shang, Lerrel Pinto, Pieter Abbeel, Stas Tiomkin:
GEM: Group Enhanced Model for Learning Dynamical Control Systems. CoRR abs/2104.02844 (2021) - [i9]Argenis Arriojas, Stas Tiomkin, Rahul V. Kulkarni:
Closed-Form Analytical Results for Maximum Entropy Reinforcement Learning. CoRR abs/2106.03931 (2021) - 2020
- [c4]Yuqing Du, Stas Tiomkin, Emre Kiciman, Daniel Polani, Pieter Abbeel, Anca D. Dragan:
AvE: Assistance via Empowerment. NeurIPS 2020 - [i8]Albert Zhan, Stas Tiomkin, Pieter Abbeel:
Preventing Imitation Learning with Adversarial Policy Ensembles. CoRR abs/2002.01059 (2020) - [i7]Yuqing Du, Stas Tiomkin, Emre Kiciman, Daniel Polani, Pieter Abbeel, Anca D. Dragan:
AvE: Assistance via Empowerment. CoRR abs/2006.14796 (2020) - [i6]Ruihan Zhao, Pieter Abbeel, Stas Tiomkin:
Efficient Online Estimation of Empowerment for Reinforcement Learning. CoRR abs/2007.07356 (2020) - [i5]Xingyu Lu, Kimin Lee, Pieter Abbeel, Stas Tiomkin:
Dynamics Generalization via Information Bottleneck in Deep Reinforcement Learning. CoRR abs/2008.00614 (2020)
2010 – 2019
- 2019
- [i4]Ruihan Zhao, Stas Tiomkin, Pieter Abbeel:
Learning Efficient Representation for Intrinsic Motivation. CoRR abs/1912.02624 (2019) - [i3]Xingyu Lu, Stas Tiomkin, Pieter Abbeel:
Predictive Coding for Boosting Deep Reinforcement Learning with Sparse Rewards. CoRR abs/1912.13414 (2019) - 2017
- [i2]Stas Tiomkin, Daniel Polani, Naftali Tishby:
Control Capacity of Partially Observable Dynamic Systems in Continuous Time. CoRR abs/1701.04984 (2017) - [i1]Stas Tiomkin, Naftali Tishby:
A Unified Bellman Equation for Causal Information and Value in Markov Decision Processes. CoRR abs/1703.01585 (2017) - 2015
- [c3]Nadav Amir
Past-future Information Bottleneck for linear feedback systems. CDC 2015: 5737-5742 - [c2]Ron M. Hecht, Aharon Bar-Hillel, Stas Tiomkin, Hadar Levi, Omer Tsimhoni
Cognitive workload and vocabulary sparseness: theory and practice. INTERSPEECH 2015: 3394-3398 - 2011
- [j2]Stas Tiomkin, David Malah
A Hybrid Text-to-Speech System That Combines Concatenative and Statistical Synthesis Units. IEEE Trans. Speech Audio Process. 19(5): 1278-1288 (2011) - 2010
- [j1]Stas Tiomkin, David Malah
Statistical Text-to-Speech Synthesis Based on Segment-Wise Representation With a Norm Constraint. IEEE Trans. Speech Audio Process. 18(5): 1077-1082 (2010)
2000 – 2009
- 2008
- [c1]Stas Tiomkin, David Malah:
Statistical text-to-speech synthesis with improved dynamics. INTERSPEECH 2008: 1841-1844
Coauthor Index
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last updated on 2024-10-07 21:25 CEST by the dblp team
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