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Safe Model-Based Multi-Agent Mean-Field Reinforcement Learning
Matej Jusup, Barna Pásztor, Tadeusz Janik +4
Many applications, e.g., in shared mobility, require coordinating a large number of agents. Mean-field reinforcement learning addresses the resulting scalability challenge by optim…
Predict NAS Multi-Task by Stacking Ensemble Models using GP-NAS
Ke Zhang
Accurately predicting the performance of architecture with small sample training is an important but not easy task. How to analysis and train dataset to overcome overfitting is the…
Sharpness-Aware Minimization Revisited: Weighted Sharpness as a Regularization Term
Yun Yue, Jiadi Jiang, Zhiling Ye +3
Deep Neural Networks (DNNs) generalization is known to be closely related to the flatness of minima, leading to the development of Sharpness-Aware Minimization (SAM) for seeking fl…
Multi-head Uncertainty Inference for Adversarial Attack Detection
Yuqi Yang, Songyun Yang, Jiyang Xie. Zhongwei Si +3
Deep neural networks (DNNs) are sensitive and susceptible to tiny perturbation by adversarial attacks which causes erroneous predictions. Various methods, including adversarial def…
Groupwise Constrained Reconstruction for Subspace Clustering
Ruijiang Li, Bin Li, Ke Zhang +2
Reconstruction based subspace clustering methods compute a self reconstruction matrix over the samples and use it for spectral clustering to obtain the final clustering result. The…