Sina Ghiassian

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 23

Top Topics

Bandit Problems

Function Approximation

Reinforcement Learning

Top Venues

Publications

Zhenwen Dai, Federico Tomasi, Sina Ghiassian
In-context Exploration-Exploitation for Reinforcement Learning. CoRR (2024)
Nicolò Felicioni, Lucas Maystre, Sina Ghiassian, Kamil Ciosek
On the Importance of Uncertainty in Decision-Making with Large Language Models. Trans. Mach. Learn. Res. 2024 (2024)
Nicolò Felicioni, Lucas Maystre, Sina Ghiassian, Kamil Ciosek
On the Importance of Uncertainty in Decision-Making with Large Language Models. CoRR (2024)
Zhenwen Dai, Federico Tomasi, Sina Ghiassian
In-context Exploration-Exploitation for Reinforcement Learning. ICLR (2024)
Arsalan Sharifnassab, Sina Ghiassian, Saber Salehkaleybar, Surya Kanoria, Dale Schuurmans
Soft Preference Optimization: Aligning Language Models to Expert Distributions. CoRR (2024)
Banafsheh Rafiee, Zaheer Abbas, Sina Ghiassian, Raksha Kumaraswamy, Richard S. Sutton, Elliot A. Ludvig, Adam White
From eye-blinks to state construction: Diagnostic benchmarks for online representation learning. Adapt. Behav. 31 (1) (2023)
Banafsheh Rafiee, Sina Ghiassian, Jun Jin, Richard S. Sutton, Jun Luo, Adam White
Auxiliary task discovery through generate-and-test. CoLLAs (2023)
Banafsheh Rafiee, Sina Ghiassian, Jun Jin, Richard S. Sutton, Jun Luo, Adam White
Auxiliary task discovery through generate-and-test. CoRR (2022)
Eric Graves, Sina Ghiassian
Importance Sampling Placement in Off-Policy Temporal-Difference Methods. CoRR (2022)
Sina Ghiassian, Richard S. Sutton
An Empirical Comparison of Off-policy Prediction Learning Algorithms on the Collision Task. CoRR (2021)
Dylan R. Ashley, Sina Ghiassian, Richard S. Sutton
Does Standard Backpropagation Forget Less Catastrophically Than Adam? CoRR (2021)
Sina Ghiassian, Richard S. Sutton
An Empirical Comparison of Off-policy Prediction Learning Algorithms in the Four Rooms Environment. CoRR (2021)
Andrew Patterson, Adam White, Sina Ghiassian, Martha White
A Generalized Projected Bellman Error for Off-policy Value Estimation in Reinforcement Learning. CoRR (2021)
Sina Ghiassian, Banafsheh Rafiee, Yat Long Lo, Adam White
Improving Performance in Reinforcement Learning by Breaking Generalization in Neural Networks. CoRR (2020)
Sina Ghiassian, Andrew Patterson, Shivam Garg, Dhawal Gupta, Adam White, Martha White
Gradient Temporal-Difference Learning with Regularized Corrections. ICML (2020)
Sina Ghiassian, Andrew Patterson, Shivam Garg, Dhawal Gupta, Adam White, Martha White
Gradient Temporal-Difference Learning with Regularized Corrections. CoRR (2020)
Sina Ghiassian, Banafsheh Rafiee, Yat Long Lo, Adam White
Improving Performance in Reinforcement Learning by Breaking Generalization in Neural Networks. AAMAS (2020)
Yat Long Lo, Sina Ghiassian
Overcoming Catastrophic Interference in Online Reinforcement Learning with Dynamic Self-Organizing Maps. CoRR (2019)
Xiang Gu, Sina Ghiassian, Richard S. Sutton
Should All Temporal Difference Learning Use Emphasis? CoRR (2019)
Banafsheh Rafiee, Sina Ghiassian, Adam White, Richard S. Sutton
Prediction in Intelligence: An Empirical Comparison of Off-policy Algorithms on Robots. AAMAS (2019)
Sina Ghiassian, Huizhen Yu, Banafsheh Rafiee, Richard S. Sutton
Two geometric input transformation methods for fast online reinforcement learning with neural nets. CoRR (2018)
Sina Ghiassian, Andrew Patterson, Martha White, Richard S. Sutton, Adam White
Online Off-policy Prediction. CoRR (2018)
Sina Ghiassian, Banafsheh Rafiee, Richard S. Sutton
A First Empirical Study of Emphatic Temporal Difference Learning. CoRR (2017)