Sina Ghiassian

29 papers A* 2A 2Journal 24Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Hallucination Detection on a Budget: Efficient Bayesian Estimation of Semantic Entropy. CoRR Kamil Ciosek, Nicolò Felicioni, Sina Ghiassian
2025	J	`jnl`	Hallucination Detection on a Budget: Efficient Bayesian Estimation of Semantic Entropy. Trans. Mach. Learn. Res. Kamil Ciosek, Nicolò Felicioni, Sina Ghiassian
2025	J	`jnl`	Learning in complex action spaces without policy gradients. Trans. Mach. Learn. Res. Arash Tavakoli, Sina Ghiassian, Nemanja Rakicevic
2025	J	`jnl`	Measuring Uncertainty Calibration. CoRR Kamil Ciosek, Nicolò Felicioni, Sina Ghiassian, Juan Elenter Litwin, Francesco Tonolini, David Gustaffson, Eva Garcia Martin, Carmen Barcena Gonzales, Raphaëlle Bertrand-Lalo
2025	J	`jnl`	Off-Policy Prediction Learning: An Empirical Study of Online Algorithms. IEEE Trans. Neural Networks Learn. Syst. Sina Ghiassian, Banafsheh Rafiee, Richard S. Sutton
2024	A*	`conf`	In-context Exploration-Exploitation for Reinforcement Learning. ICLR Zhenwen Dai, Federico Tomasi, Sina Ghiassian
2024	J	`jnl`	In-context Exploration-Exploitation for Reinforcement Learning. CoRR Zhenwen Dai, Federico Tomasi, Sina Ghiassian
2024	J	`jnl`	Learning in complex action spaces without policy gradients. CoRR Arash Tavakoli, Sina Ghiassian, Nemanja Rakicevic
2024	J	`jnl`	On the Importance of Uncertainty in Decision-Making with Large Language Models. CoRR Nicolò Felicioni, Lucas Maystre, Sina Ghiassian, Kamil Ciosek
2024	J	`jnl`	On the Importance of Uncertainty in Decision-Making with Large Language Models. Trans. Mach. Learn. Res. Nicolò Felicioni, Lucas Maystre, Sina Ghiassian, Kamil Ciosek
2024	J	`jnl`	Soft Preference Optimization: Aligning Language Models to Expert Distributions. CoRR Arsalan Sharifnassab, Sina Ghiassian, Saber Salehkaleybar, Surya Kanoria, Dale Schuurmans
2023	—	`conf`	Auxiliary task discovery through generate-and-test. CoLLAs Banafsheh Rafiee, Sina Ghiassian, Jun Jin, Richard S. Sutton, Jun Luo, Adam White
2023	J	`jnl`	From eye-blinks to state construction: Diagnostic benchmarks for online representation learning. Adapt. Behav. Banafsheh Rafiee, Zaheer Abbas, Sina Ghiassian, Raksha Kumaraswamy, Richard S. Sutton, Elliot A. Ludvig, Adam White
2022	J	`jnl`	Auxiliary task discovery through generate-and-test. CoRR Banafsheh Rafiee, Sina Ghiassian, Jun Jin, Richard S. Sutton, Jun Luo, Adam White
2022	J	`jnl`	Importance Sampling Placement in Off-Policy Temporal-Difference Methods. CoRR Eric Graves, Sina Ghiassian
2021	J	`jnl`	A Generalized Projected Bellman Error for Off-policy Value Estimation in Reinforcement Learning. CoRR Andrew Patterson, Adam White, Sina Ghiassian, Martha White
2021	J	`jnl`	An Empirical Comparison of Off-policy Prediction Learning Algorithms in the Four Rooms Environment. CoRR Sina Ghiassian, Richard S. Sutton
2021	J	`jnl`	An Empirical Comparison of Off-policy Prediction Learning Algorithms on the Collision Task. CoRR Sina Ghiassian, Richard S. Sutton
2021	J	`jnl`	Does Standard Backpropagation Forget Less Catastrophically Than Adam? CoRR Dylan R. Ashley, Sina Ghiassian, Richard S. Sutton
2020	A*	`conf`	Gradient Temporal-Difference Learning with Regularized Corrections. ICML Sina Ghiassian, Andrew Patterson, Shivam Garg, Dhawal Gupta, Adam White, Martha White
2020	J	`jnl`	Gradient Temporal-Difference Learning with Regularized Corrections. CoRR Sina Ghiassian, Andrew Patterson, Shivam Garg, Dhawal Gupta, Adam White, Martha White
2020	A	`conf`	Improving Performance in Reinforcement Learning by Breaking Generalization in Neural Networks. AAMAS Sina Ghiassian, Banafsheh Rafiee, Yat Long Lo, Adam White
2020	J	`jnl`	Improving Performance in Reinforcement Learning by Breaking Generalization in Neural Networks. CoRR Sina Ghiassian, Banafsheh Rafiee, Yat Long Lo, Adam White
2019	J	`jnl`	Overcoming Catastrophic Interference in Online Reinforcement Learning with Dynamic Self-Organizing Maps. CoRR Yat Long Lo, Sina Ghiassian
2019	A	`conf`	Prediction in Intelligence: An Empirical Comparison of Off-policy Algorithms on Robots. AAMAS Banafsheh Rafiee, Sina Ghiassian, Adam White, Richard S. Sutton
2019	J	`jnl`	Should All Temporal Difference Learning Use Emphasis? CoRR Xiang Gu, Sina Ghiassian, Richard S. Sutton
2018	J	`jnl`	Online Off-policy Prediction. CoRR Sina Ghiassian, Andrew Patterson, Martha White, Richard S. Sutton, Adam White
2018	J	`jnl`	Two geometric input transformation methods for fast online reinforcement learning with neural nets. CoRR Sina Ghiassian, Huizhen Yu, Banafsheh Rafiee, Richard S. Sutton
2017	J	`jnl`	A First Empirical Study of Emphatic Temporal Difference Learning. CoRR Sina Ghiassian, Banafsheh Rafiee, Richard S. Sutton