Summary of Do Causal Predictors Generalize Better to New Domains?, by Vivian Y. Nastl and Moritz Hardt
Do causal predictors generalize better to new domains?by Vivian Y. Nastl, Moritz HardtFirst submitted to…
Summary of Explaining Kernel Clustering Via Decision Trees, by Maximilian Fleissner et al.
Explaining Kernel Clustering via Decision Treesby Maximilian Fleissner, Leena Chennuru Vankadara, Debarghya GhoshdastidarFirst submitted to…
Summary of Fedlion: Faster Adaptive Federated Optimization with Fewer Communication, by Zhiwei Tang et al.
FedLion: Faster Adaptive Federated Optimization with Fewer Communicationby Zhiwei Tang, Tsung-Hui ChangFirst submitted to arxiv…
Summary of Explaining Probabilistic Models with Distributional Values, by Luca Franceschi et al.
Explaining Probabilistic Models with Distributional Valuesby Luca Franceschi, Michele Donini, Cédric Archambeau, Matthias SeegerFirst submitted…
Summary of Smart Information Exchange For Unsupervised Federated Learning Via Reinforcement Learning, by Seohyun Lee et al.
Smart Information Exchange for Unsupervised Federated Learning via Reinforcement Learningby Seohyun Lee, Anindya Bijoy Das,…
Summary of Multi-fidelity Methods For Optimization: a Survey, by Ke Li and Fan Li
Multi-Fidelity Methods for Optimization: A Surveyby Ke Li, Fan LiFirst submitted to arxiv on: 15…
Summary of Universal Black-box Reward Poisoning Attack Against Offline Reinforcement Learning, by Yinglun Xu et al.
Universal Black-Box Reward Poisoning Attack against Offline Reinforcement Learningby Yinglun Xu, Rohan Gumaste, Gagandeep SinghFirst…
Summary of Sparse and Faithful Explanations Without Sparse Models, by Yiyang Sun et al.
Sparse and Faithful Explanations Without Sparse Modelsby Yiyang Sun, Zhi Chen, Vittorio Orlandi, Tong Wang,…
Summary of Robust Svd Made Easy: a Fast and Reliable Algorithm For Large-scale Data Analysis, by Sangil Han et al.
Robust SVD Made Easy: A fast and reliable algorithm for large-scale data analysisby Sangil Han,…
Summary of Machine Learning For Stochastic Parametrisation, by Hannah M. Christensen et al.
Machine Learning for Stochastic Parametrisationby Hannah M. Christensen, Salah Kouhen, Greta Miller, Raghul ParthipanFirst submitted…