Stebėti
Ehsan Imani
Pavadinimas
Cituota
Cituota
Metai
An off-policy policy gradient theorem using emphatic weightings
E Imani, E Graves, M White
Advances in Neural Information Processing Systems 31, 2018
842018
Improving regression performance with distributional losses
E Imani, M White
International Conference on Machine Learning, 2157-2166, 2018
602018
Hallucinating Value: A Pitfall of Dyna-style Planning with Imperfect Environment Models
T Jafferjee, E Imani, E Talvitie, M White, M Bowling
arXiv preprint arXiv:2006.04363, 2020
282020
An implicit function learning approach for parametric modal regression
Y Pan, E Imani, A Farahmand, M White
Advances in Neural Information Processing Systems 33, 2020
102020
The tunnel effect: Building data representations in deep neural networks
W Masarczyk, M Ostaszewski, E Imani, R Pascanu, P Miłoś, T Trzcinski
Advances in Neural Information Processing Systems 36, 2024
72024
Multi-modal deep distance metric learning
SM Roostaiyan, E Imani, MS Baghshah
Intelligent Data Analysis 21 (6), 1351-1369, 2017
72017
Off-policy actor-critic with emphatic weightings
E Graves, E Imani, R Kumaraswamy, M White
Journal of Machine Learning Research 24 (146), 1-63, 2023
62023
Representation Alignment in Neural Networks
E Imani, W Hu, M White
Transactions on Machine Learning Research, 2022
32022
Investigating the Histogram Loss in Regression
E Imani, K Luedemann, S Scholnick-Hughes, E Elelimy, M White
arXiv preprint arXiv:2402.13425, 2024
12024
Mitigating Value Hallucination in Dyna-Style Planning via Multistep Predecessor Models
F Aminmansour, T Jafferjee, E Imani, EJ Talvitie, M Bowling, M White
Journal of Artificial Intelligence Research 80, 441-473, 2024
2024
Label Alignment Regularization for Distribution Shift
E Imani, G Zhang, J Luo, P Poupart, PHS Torr, Y Pan
arXiv preprint arXiv:2211.14960, 2022
2022
Distributional Losses for Regression
E Imani
2019
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Straipsniai 1–12