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Roman Pogodin
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2020 – today
- 2024
- [c7]Roman Pogodin, Jonathan Cornford, Arna Ghosh, Gauthier Gidel, Guillaume Lajoie, Blake Aaron Richards:
Synaptic Weight Distributions Depend on the Geometry of Plasticity. ICLR 2024 - [i9]Roman Pogodin, Antonin Schrab, Yazhe Li, Danica J. Sutherland, Arthur Gretton:
Practical Kernel Tests of Conditional Independence. CoRR abs/2402.13196 (2024) - 2023
- [c6]Roman Pogodin, Namrata Deka, Yazhe Li, Danica J. Sutherland, Victor Veitch, Arthur Gretton:
Efficient Conditionally Invariant Representation Learning. ICLR 2023 - [i8]Roman Pogodin, Jonathan Cornford, Arna Ghosh, Gauthier Gidel, Guillaume Lajoie, Blake A. Richards:
Synaptic Weight Distributions Depend on the Geometry of Plasticity. CoRR abs/2305.19394 (2023) - 2022
- [i7]Roman Pogodin, Namrata Deka, Yazhe Li, Danica J. Sutherland, Victor Veitch, Arthur Gretton:
Efficient Conditionally Invariant Representation Learning. CoRR abs/2212.08645 (2022) - 2021
- [c5]Roman Pogodin, Yash Mehta, Timothy P. Lillicrap, Peter E. Latham:
Towards Biologically Plausible Convolutional Networks. NeurIPS 2021: 13924-13936 - [c4]Yazhe Li, Roman Pogodin, Danica J. Sutherland, Arthur Gretton:
Self-Supervised Learning with Kernel Dependence Maximization. NeurIPS 2021: 15543-15556 - [i6]Yazhe Li, Roman Pogodin, Danica J. Sutherland, Arthur Gretton:
Self-Supervised Learning with Kernel Dependence Maximization. CoRR abs/2106.08320 (2021) - [i5]Roman Pogodin, Yash Mehta, Timothy P. Lillicrap, Peter E. Latham:
Towards Biologically Plausible Convolutional Networks. CoRR abs/2106.13031 (2021) - 2020
- [c3]Roman Pogodin, Peter E. Latham:
Kernelized information bottleneck leads to biologically plausible 3-factor Hebbian learning in deep networks. NeurIPS 2020 - [i4]Roman Pogodin, Peter E. Latham:
Kernelized information bottleneck leads to biologically plausible 3-factor Hebbian learning in deep networks. CoRR abs/2006.07123 (2020)
2010 – 2019
- 2019
- [c2]Roman Pogodin, Tor Lattimore:
On First-Order Bounds, Variance and Gap-Dependent Bounds for Adversarial Bandits. UAI 2019: 894-904 - [i3]Roman Pogodin, Tor Lattimore:
Adaptivity, Variance and Separation for Adversarial Bandits. CoRR abs/1903.07890 (2019) - [i2]Roman Pogodin, Dane S. Corneil, Alexander Seeholzer, Joseph Heng, Wulfram Gerstner:
Working memory facilitates reward-modulated Hebbian learning in recurrent neural networks. CoRR abs/1910.10559 (2019) - 2017
- [c1]Roman Pogodin, Mikhail Krechetov, Yury Maximov
:
Efficient rank minimization to tighten semidefinite programming for unconstrained binary quadratic optimization. Allerton 2017: 1153-1159 - [i1]Roman Pogodin, Mikhail Krechetov, Yury Maximov:
Efficient Rank Minimization to Tighten Semidefinite Programming for Unconstrained Binary Quadratic Optimization. CoRR abs/1708.01690 (2017)
Coauthor Index
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last updated on 2024-07-30 20:48 CEST by the dblp team
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