Stas Tiomkin

According to our database, Stas Tiomkin authored at least 30 papers between 2008 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

SuPLE: Robot Learning with Lyapunov Rewards.

Phu Nguyen, Daniel Polani, Stas Tiomkin

CoRR, 2024

Learning telic-controllable state representations.

Nadav Amir, Stas Tiomkin, Angela Langdon

CoRR, 2024

Multi-Resolution Diffusion for Privacy-Sensitive Recommender Systems.

Derek Lilienthal, Paul Mello, Magdalini Eirinaki, Stas Tiomkin

IEEE Access, 2024

Boosting Soft Q-Learning by Bounding.

Jacob Adamczyk, Volodymyr Makarenko, Stas Tiomkin, Rahul V. Kulkarni

RLJ, 2024

Controllability-Constrained Deep Network Models for Enhanced Control of Dynamical Systems.

Suruchi Sharma, Volodymyr Makarenko, Gautam Kumar, Stas Tiomkin

Proceedings of the American Control Conference, 2024

Dimensionality Reduction of Dynamics on Lie Groups via Structure-Aware Canonical Correlation Analysis.

Wooyoung Chung, Daniel Polani, Stas Tiomkin

Proceedings of the American Control Conference, 2024

2023

Taming Waves: A Physically-Interpretable Machine Learning Framework for Realizable Control of Wave Dynamics.

Tristan Shah, Feruza Amirkulova, Stas Tiomkin

CoRR, 2023

Dimensionality Reduction of Dynamics on Lie Manifolds via Structure-Aware Canonical Correlation Analysis.

Wooyoung Chung, Daniel Polani, Stas Tiomkin

CoRR, 2023

Compositionality and Bounds for Optimal Value Functions in Reinforcement Learning.

Jacob Adamczyk, Stas Tiomkin, Rahul V. Kulkarni

CoRR, 2023

Intrinsic Motivation in Dynamical Control Systems.

Stas Tiomkin, Ilya Nemenman, Daniel Polani, Naftali Tishby

CoRR, 2023

Bayesian inference approach for entropy regularized reinforcement learning with stochastic dynamics.

Argenis Arriojas, Jacob Adamczyk, Stas Tiomkin, Rahul V. Kulkarni

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Bounding the optimal value function in compositional reinforcement learning.

Jacob Adamczyk, Volodymyr Makarenko, Argenis Arriojas, Stas Tiomkin, Rahul V. Kulkarni

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Utilizing Prior Solutions for Reward Shaping and Composition in Entropy-Regularized Reinforcement Learning.

Jacob Adamczyk, Argenis Arriojas, Stas Tiomkin, Rahul V. Kulkarni

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Multi-Objective Policy Gradients with Topological Constraints.

Kyle Hollins Wray, Stas Tiomkin, Mykel J. Kochenderfer, Pieter Abbeel

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

2021

Closed-Form Analytical Results for Maximum Entropy Reinforcement Learning.

Argenis Arriojas, Stas Tiomkin, Rahul V. Kulkarni

CoRR, 2021

GEM: Group Enhanced Model for Learning Dynamical Control Systems.

Philippe Hansen-Estruch, Wenling Shang, Lerrel Pinto, Pieter Abbeel, Stas Tiomkin

CoRR, 2021

Efficient Empowerment Estimation for Unsupervised Stabilization.

Ruihan Zhao, Kevin Lu, Pieter Abbeel, Stas Tiomkin

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Dynamics Generalization via Information Bottleneck in Deep Reinforcement Learning.

Xingyu Lu, Kimin Lee, Pieter Abbeel, Stas Tiomkin

CoRR, 2020

Efficient Online Estimation of Empowerment for Reinforcement Learning.

Ruihan Zhao, Pieter Abbeel, Stas Tiomkin

CoRR, 2020

Preventing Imitation Learning with Adversarial Policy Ensembles.

Albert Zhan, Stas Tiomkin, Pieter Abbeel

CoRR, 2020

AvE: Assistance via Empowerment.

Yuqing Du, Stas Tiomkin, Emre Kiciman, Daniel Polani, Pieter Abbeel, Anca D. Dragan

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Predictive Coding for Boosting Deep Reinforcement Learning with Sparse Rewards.

Xingyu Lu, Stas Tiomkin, Pieter Abbeel

CoRR, 2019

Learning Efficient Representation for Intrinsic Motivation.

Ruihan Zhao, Stas Tiomkin, Pieter Abbeel

CoRR, 2019

2017

A Unified Bellman Equation for Causal Information and Value in Markov Decision Processes.

Stas Tiomkin, Naftali Tishby

CoRR, 2017

Control Capacity of Partially Observable Dynamic Systems in Continuous Time.

Stas Tiomkin, Daniel Polani, Naftali Tishby

CoRR, 2017

2015

Cognitive workload and vocabulary sparseness: theory and practice.

Ron M. Hecht, Aharon Bar-Hillel, Stas Tiomkin, Hadar Levi, Omer Tsimhoni, Naftali Tishby

Proceedings of the 16th Annual Conference of the International Speech Communication Association, 2015

Past-future Information Bottleneck for linear feedback systems.

Nadav Amir, Stas Tiomkin, Naftali Tishby

Proceedings of the 54th IEEE Conference on Decision and Control, 2015

2011

A Hybrid Text-to-Speech System That Combines Concatenative and Statistical Synthesis Units.

Stas Tiomkin, David Malah, Slava Shechtman, Zvi Kons

IEEE Trans. Speech Audio Process., 2011

2010

Statistical Text-to-Speech Synthesis Based on Segment-Wise Representation With a Norm Constraint.

Stas Tiomkin, David Malah, Slava Shechtman

IEEE Trans. Speech Audio Process., 2010

2008

Statistical text-to-speech synthesis with improved dynamics.

Stas Tiomkin, David Malah

Proceedings of the 9th Annual Conference of the International Speech Communication Association, 2008