March 13, 2020 11:25
Ten papers were accepted at AISTATS 2020, a major conference on machine learning. For more details, please refer to the link below.
[Accepted Papers] https://www.aistats.org/accepted.html
- RCD: Repetitive causal discovery of linear non-Gaussian acyclic models with latent confounders
Takashi Nicholas Maeda (RIKEN AIP / Shiga University)
Shohei Shimizu (RIKEN AIP / Shiga University) - Mitigating Overfitting in Supervised Classification from Two Unlabeled Datasets: A Consistent Risk Correction Approach
Nan Lu (The University of Tokyo)
Tianyi Zhang (The University of Tokyo)
Gang Niu (RIKEN AIP)
Masashi Sugiyama (RIKEN AIP / The University of Tokyo) - Calibrated Surrogate Maximization of Linear-fractional Utility in Binary Classification
Han Bao (The University of Tokyo / RIKEN AIP)
Masashi Sugiyama (RIKEN AIP / The University of Tokyo) - A Unified Statistically Efficient Estimation Framework for Unnormalized Models
Masatoshi Uehara (Harvard University)
Takafumi Kanamori (Tokyo Institute of Technology/ RIKEN AIP)
Takashi Takenouchi (Future University Hakodate/ RIKEN AIP)
Takeru Matsuda (University of Tokyo/ RIKEN CBS) - Functional Gradient Boosting for Learning Residual-like Networks with Statistical Guarantees
Atsushi Nitanda (The University of Tokyo/ RIKEN AIP / JST PRESTO)
Taiji Suzuki (The University of Tokyo/ RIKEN AIP) - Understanding Generalization in Deep Learning via Tensor Methods
Jingling Li (UMD)
Yanchao Sun (University of Maryland/ College Park)
Jiahao Su (UMD)
Taiji Suzuki (The University of Tokyo/ RIKEN AIP)
Furong Huang (University of Maryland) - Sparse Hilbert-Schmidt Independence Criterion Regression
Benjamin Poignard (Osaka University/ RIKEN AIP)
Makoto Yamada (RIKEN AIP/ Kyoto University) - More Powerful Selective Kernel Tests for Feature Selection
Jen Ning Lim (University College London)
Makoto Yamada (RIKEN AIP/ Kyoto University)
Wittawat Jitkrittum (Max Planck Institute for Intelligent Systems)
Yoshikazu Terada (Osaka University/ RIKEN AIP)
Shigeyuki Matsui (Nagoya University)
Hidetoshi Shimodaira (Kyoto University/ RIKEN AIP) - On Random Subsampling of Gaussian Process Regression: A Graphon-Based Analysis
Kohei Hayashi (Preferred Networks, Inc.)
Masaaki Imaizumi (The Institute of Statistical Mathematics/ RIKEN AIP)
Yuichi Yoshida (NII) - Stopping criterion for active learning based on deterministic generalization bounds
Hideaki Ishibashi (Kyushu Institute of Technology)
Hideitsu Hino (The Institute of Statistical Mathematics/ RIKEN AIP)
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