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Vivek Veeriah
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2020 – today
- 2024
- [i16]Ryan Diaz, Adam Imdieke, Vivek Veeriah, Karthik Desingh:
AugInsert: Learning Robust Visual-Force Policies via Data Augmentation for Object Assembly Tasks. CoRR abs/2410.14968 (2024) - 2023
- [c11]Ted Moskovitz, Brendan O'Donoghue, Vivek Veeriah, Sebastian Flennerhag, Satinder Singh, Tom Zahavy:
ReLOAD: Reinforcement Learning with Optimistic Ascent-Descent for Last-Iterate Convergence in Constrained MDPs. ICML 2023: 25303-25336 - [i15]Ted Moskovitz, Brendan O'Donoghue, Vivek Veeriah, Sebastian Flennerhag, Satinder Singh, Tom Zahavy:
ReLOAD: Reinforcement Learning with Optimistic Ascent-Descent for Last-Iterate Convergence in Constrained MDPs. CoRR abs/2302.01275 (2023) - [i14]Tom Zahavy, Vivek Veeriah, Shaobo Hou, Kevin Waugh, Matthew Lai, Edouard Leurent, Nenad Tomasev, Lisa Schut, Demis Hassabis, Satinder Singh:
Diversifying AI: Towards Creative Chess with AlphaZero. CoRR abs/2308.09175 (2023) - 2022
- [i13]Vivek Veeriah, Zeyu Zheng, Richard L. Lewis, Satinder Singh:
GrASP: Gradient-Based Affordance Selection for Planning. CoRR abs/2202.04772 (2022) - 2021
- [c10]Zeyu Zheng, Vivek Veeriah, Risto Vuorio, Richard L. Lewis, Satinder Singh:
Learning State Representations from Random Deep Action-conditional Predictions. NeurIPS 2021: 23679-23691 - [c9]Vivek Veeriah, Tom Zahavy, Matteo Hessel, Zhongwen Xu, Junhyuk Oh, Iurii Kemaev, Hado van Hasselt, David Silver, Satinder Singh:
Discovery of Options via Meta-Learned Subgoals. NeurIPS 2021: 29861-29873 - [i12]Zeyu Zheng, Vivek Veeriah, Risto Vuorio, Richard L. Lewis, Satinder Singh:
Learning State Representations from Random Deep Action-conditional Predictions. CoRR abs/2102.04897 (2021) - [i11]Vivek Veeriah, Tom Zahavy, Matteo Hessel, Zhongwen Xu, Junhyuk Oh, Iurii Kemaev, Hado van Hasselt, David Silver, Satinder Singh:
Discovery of Options via Meta-Learned Subgoals. CoRR abs/2102.06741 (2021) - 2020
- [c8]Janarthanan Rajendran, Richard L. Lewis, Vivek Veeriah, Honglak Lee, Satinder Singh:
How Should an Agent Practice? AAAI 2020: 5454-5461 - [c7]Tom Zahavy, Zhongwen Xu, Vivek Veeriah, Matteo Hessel, Junhyuk Oh, Hado van Hasselt, David Silver, Satinder Singh:
A Self-Tuning Actor-Critic Algorithm. NeurIPS 2020 - [c6]Shangtong Zhang, Vivek Veeriah, Shimon Whiteson:
Learning Retrospective Knowledge with Reverse Reinforcement Learning. NeurIPS 2020 - [i10]Tom Zahavy, Zhongwen Xu, Vivek Veeriah, Matteo Hessel, Junhyuk Oh, Hado van Hasselt, David Silver, Satinder Singh:
Self-Tuning Deep Reinforcement Learning. CoRR abs/2002.12928 (2020) - [i9]Shangtong Zhang, Vivek Veeriah, Shimon Whiteson:
Learning Retrospective Knowledge with Reverse Reinforcement Learning. CoRR abs/2007.06703 (2020)
2010 – 2019
- 2019
- [c5]Vivek Veeriah, Matteo Hessel, Zhongwen Xu, Janarthanan Rajendran, Richard L. Lewis, Junhyuk Oh, Hado van Hasselt, David Silver, Satinder Singh:
Discovery of Useful Questions as Auxiliary Tasks. NeurIPS 2019: 9306-9317 - [i8]Alexandra Kearney, Vivek Veeriah, Jaden B. Travnik, Patrick M. Pilarski, Richard S. Sutton:
Learning Feature Relevance Through Step Size Adaptation in Temporal-Difference Learning. CoRR abs/1903.03252 (2019) - [i7]Vivek Veeriah, Matteo Hessel, Zhongwen Xu, Richard L. Lewis, Janarthanan Rajendran, Junhyuk Oh, Hado van Hasselt, David Silver, Satinder Singh:
Discovery of Useful Questions as Auxiliary Tasks. CoRR abs/1909.04607 (2019) - [i6]Janarthanan Rajendran, Richard L. Lewis, Vivek Veeriah, Honglak Lee, Satinder Singh:
How Should an Agent Practice? CoRR abs/1912.07045 (2019) - 2018
- [i5]Alexandra Kearney, Vivek Veeriah, Jaden B. Travnik, Richard S. Sutton, Patrick M. Pilarski:
TIDBD: Adapting Temporal-difference Step-sizes Through Stochastic Meta-descent. CoRR abs/1804.03334 (2018) - [i4]Vivek Veeriah, Junhyuk Oh, Satinder Singh:
Many-Goals Reinforcement Learning. CoRR abs/1806.09605 (2018) - 2017
- [c4]Vivek Veeriah, Harm van Seijen, Richard S. Sutton:
Forward Actor-Critic for Nonlinear Function Approximation in Reinforcement Learning. AAMAS 2017: 556-564 - [c3]Vivek Veeriah, Shangtong Zhang, Richard S. Sutton:
Crossprop: Learning Representations by Stochastic Meta-Gradient Descent in Neural Networks. ECML/PKDD (1) 2017: 445-459 - 2016
- [i3]Vivek Veeriah, Patrick M. Pilarski, Richard S. Sutton:
Face valuing: Training user interfaces with facial expressions and reinforcement learning. CoRR abs/1606.02807 (2016) - [i2]Richard S. Sutton, Vivek Veeriah:
Learning representations through stochastic gradient descent in cross-validation error. CoRR abs/1612.02879 (2016) - 2015
- [c2]Vivek Veeriah, Naifan Zhuang, Guo-Jun Qi
:
Differential Recurrent Neural Networks for Action Recognition. ICCV 2015: 4041-4049 - [c1]Vivek Veeriah, Rohit Durvasula, Guo-Jun Qi
Deep Learning Architecture with Dynamically Programmed Layers for Brain Connectome Prediction. KDD 2015: 1205-1214 - [i1]Vivek Veeriah, Naifan Zhuang, Guo-Jun Qi:
Differential Recurrent Neural Networks for Action Recognition. CoRR abs/1504.06678 (2015)
Coauthor Index
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