◼︎Information Akiyoshi Sannai, Masaaki Imaizumi, Makoto Kawano. “Improved Generalization Bounds of Group Invariant / Equivariant Deep Networks via Quotient Feature Spaces”, 37th Conference on Uncertainty in Artificial Intelligence (UAI 2021). ◼︎Overview Numerous invariant (or equivariant) neural networks have succeeded in handling the invariant data such as point clouds and graphs. However, a generalization theory for…
【Information】 Hiroki Furuta, Tatsuya Matsushima, Tadashi Kozuno, Yutaka Matsuo, Sergey Levine, Ofir Nachum, and Shixiang Shane Gu. “Policy Information Capacity: Information-Theoretic Measure for Task Complexity in Deep Reinforcement Learning”, International Conference on Machine Learning 2021 (ICML2021). July 2021. 【Overview】 Progress in deep reinforcement learning (RL) research is largely enabled by benchmark task environments. However, analyzing…
【NEWS】Our paper was accepted to ACL-IJCNLP 2021 (Findings) 【Title】LEWIS: Levenshtein Editing for Unsupervised Text Style Transfer 【Authors】Machel Reid and Victor Zhong (University of Washington) 【Overview】Many types of text style transfer can be achieved with only small, precise edits (e.g. sentiment transfer from “I had a terrible time…” to “I had a great time…”). We propose…
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