Using functional or structural magnetic resonance images and personal characteristic data to identify ADHD and autism S Ghiassian, R Greiner, P Jin, MRG Brown PloS one 11 (12), e0166934, 2016 | 110 | 2016 |
Gradient temporal-difference learning with regularized corrections S Ghiassian, A Patterson, S Garg, D Gupta, A White, M White International Conference on Machine Learning, 3524-3534, 2020 | 44 | 2020 |
Improving performance in reinforcement learning by breaking generalization in neural networks S Ghiassian, B Rafiee, YL Lo, A White arXiv preprint arXiv:2003.07417, 2020 | 33 | 2020 |
Learning to classify psychiatric disorders based on fMR images: Autism vs healthy and ADHD vs healthy S Ghiassian, R Greiner, P Jin, M Brown Proceedings of 3rd NIPS Workshop on Machine Learning and Interpretation in …, 2013 | 32 | 2013 |
Online off-policy prediction S Ghiassian, A Patterson, M White, RS Sutton, A White arXiv preprint arXiv:1811.02597, 2018 | 30 | 2018 |
A generalized projected bellman error for off-policy value estimation in reinforcement learning A Patterson, A White, M White Journal of Machine Learning Research 23 (145), 1-61, 2022 | 16 | 2022 |
A first empirical study of emphatic temporal difference learning S Ghiassian, B Rafiee, RS Sutton arXiv preprint arXiv:1705.04185, 2017 | 11 | 2017 |
From eye-blinks to state construction: Diagnostic benchmarks for online representation learning B Rafiee, Z Abbas, S Ghiassian, R Kumaraswamy, RS Sutton, EA Ludvig, ... Adaptive behavior 31 (1), 3-19, 2023 | 8 | 2023 |
Overcoming catastrophic interference in online reinforcement learning with dynamic self-organizing maps YL Lo, S Ghiassian arXiv preprint arXiv:1910.13213, 2019 | 8 | 2019 |
Two geometric input transformation methods for fast online reinforcement learning with neural nets S Ghiassian, H Yu, B Rafiee, RS Sutton arXiv preprint arXiv:1805.07476, 2018 | 8 | 2018 |
An empirical comparison of off-policy prediction learning algorithms on the collision task S Ghiassian, RS Sutton arXiv preprint arXiv:2106.00922, 2021 | 6 | 2021 |
An empirical comparison of off-policy prediction learning algorithms in the four rooms environment S Ghiassian, RS Sutton arXiv preprint arXiv:2109.05110, 2021 | 5 | 2021 |
Prediction in intelligence: An empirical comparison of off-policy algorithms on robots B Rafiee, S Ghiassian, A White, RS Sutton Proceedings of the 18th International Conference on Autonomous Agents and …, 2019 | 5 | 2019 |
Does the Adam Optimizer Exacerbate Catastrophic Forgetting? DR Ashley, S Ghiassian, RS Sutton arXiv preprint arXiv:2102.07686, 2021 | 4 | 2021 |
Should All Temporal Difference Learning Use Emphasis? X Gu, S Ghiassian, RS Sutton arXiv preprint arXiv:1903.00194, 2019 | 4 | 2019 |
Does Standard Backpropagation Forget Less Catastrophically Than Adam? DR Ashley, S Ghiassian, RS Sutton arXiv preprint arXiv:2102.07686, 2021 | 2 | 2021 |
Auxiliary task discovery through generate-and-test B Rafiee, S Ghiassian, J Jin, R Sutton, J Luo, A White Conference on Lifelong Learning Agents, 703-714, 2023 | 1 | 2023 |
Importance Sampling Placement in Off-Policy Temporal-Difference Methods E Graves, S Ghiassian arXiv preprint arXiv:2203.10172, 2022 | 1 | 2022 |
Online off-policy prediction S Ghiassian | 1 | 2022 |
Investigating Objectives for Off-policy Value Estimation in Reinforcement Learning A Patterson, S Ghiassian, D Gupta, A White, M White Preparation, 2021 | 1 | 2021 |