Vivek Veeriah

According to our database, Vivek Veeriah authored at least 20 papers between 2015 and 2024.

Collaborative distances:

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

2024

AugInsert: Learning Robust Visual-Force Policies via Data Augmentation for Object Assembly Tasks.

Ryan Diaz, Adam Imdieke, Vivek Veeriah, Karthik Desingh

CoRR, 2024

2023

Diversifying AI: Towards Creative Chess with AlphaZero.

Tom Zahavy, Vivek Veeriah, Shaobo Hou, Kevin Waugh, Matthew Lai, Edouard Leurent, Nenad Tomasev, Lisa Schut, Demis Hassabis, Satinder Singh

CoRR, 2023

ReLOAD: Reinforcement Learning with Optimistic Ascent-Descent for Last-Iterate Convergence in Constrained MDPs.

Ted Moskovitz, Brendan O'Donoghue, Vivek Veeriah, Sebastian Flennerhag, Satinder Singh, Tom Zahavy

Proceedings of the International Conference on Machine Learning, 2023

2022

GrASP: Gradient-Based Affordance Selection for Planning.

Vivek Veeriah, Zeyu Zheng, Richard L. Lewis, Satinder Singh

CoRR, 2022

2021

Learning State Representations from Random Deep Action-conditional Predictions.

Zeyu Zheng, Vivek Veeriah, Risto Vuorio, Richard L. Lewis, Satinder Singh

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Discovery of Options via Meta-Learned Subgoals.

Vivek Veeriah, Tom Zahavy, Matteo Hessel, Zhongwen Xu, Junhyuk Oh, Iurii Kemaev, Hado van Hasselt, David Silver, Satinder Singh

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Self-Tuning Deep Reinforcement Learning.

Tom Zahavy, Zhongwen Xu, Vivek Veeriah, Matteo Hessel, Junhyuk Oh, Hado van Hasselt, David Silver, Satinder Singh

CoRR, 2020

Learning Retrospective Knowledge with Reverse Reinforcement Learning.

Shangtong Zhang, Vivek Veeriah, Shimon Whiteson

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

A Self-Tuning Actor-Critic Algorithm.

Tom Zahavy, Zhongwen Xu, Vivek Veeriah, Matteo Hessel, Junhyuk Oh, Hado van Hasselt, David Silver, Satinder Singh

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

How Should an Agent Practice?

Janarthanan Rajendran, Richard L. Lewis, Vivek Veeriah, Honglak Lee, Satinder Singh

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Learning Feature Relevance Through Step Size Adaptation in Temporal-Difference Learning.

Alexandra Kearney, Vivek Veeriah, Jaden B. Travnik, Patrick M. Pilarski, Richard S. Sutton

CoRR, 2019

Discovery of Useful Questions as Auxiliary Tasks.

Vivek Veeriah, Matteo Hessel, Zhongwen Xu, Janarthanan Rajendran, Richard L. Lewis, Junhyuk Oh, Hado van Hasselt, David Silver, Satinder Singh

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Many-Goals Reinforcement Learning.

Vivek Veeriah, Junhyuk Oh, Satinder Singh

CoRR, 2018

TIDBD: Adapting Temporal-difference Step-sizes Through Stochastic Meta-descent.

Alexandra Kearney, Vivek Veeriah, Jaden B. Travnik, Richard S. Sutton, Patrick M. Pilarski

CoRR, 2018

2017

Crossprop: Learning Representations by Stochastic Meta-Gradient Descent in Neural Networks.

Vivek Veeriah, Shangtong Zhang, Richard S. Sutton

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Forward Actor-Critic for Nonlinear Function Approximation in Reinforcement Learning.

Vivek Veeriah, Harm van Seijen, Richard S. Sutton

Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems, 2017

2016

Face valuing: Training user interfaces with facial expressions and reinforcement learning.

Vivek Veeriah, Patrick M. Pilarski, Richard S. Sutton

CoRR, 2016

Learning representations through stochastic gradient descent in cross-validation error.

Richard S. Sutton, Vivek Veeriah

CoRR, 2016

2015

Deep Learning Architecture with Dynamically Programmed Layers for Brain Connectome Prediction.

Vivek Veeriah, Rohit Durvasula, Guo-Jun Qi

Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Differential Recurrent Neural Networks for Action Recognition.

Vivek Veeriah, Naifan Zhuang, Guo-Jun Qi

Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015