Summary of Towards Hyper-parameter-free Federated Learning, by Geetika et al.
Towards Hyper-parameter-free Federated Learningby Geetika, Drishya Uniyal, Bapi ChatterjeeFirst submitted to arxiv on: 30 Aug…
Towards Hyper-parameter-free Federated Learningby Geetika, Drishya Uniyal, Bapi ChatterjeeFirst submitted to arxiv on: 30 Aug…
Efficient Estimation of Unique Components in Independent Component Analysis by Matrix Representationby Yoshitatsu Matsuda, Kazunori…
Minimising changes to audit when updating decision treesby Anj Simmons, Scott Barnett, Anupam Chaudhuri, Sankhya…
AEMLO: AutoEncoder-Guided Multi-Label Oversamplingby Ao Zhou, Bin Liu, Jin Wang, Kaiwei Sun, Kelin LiuFirst submitted…
Total Uncertainty Quantification in Inverse PDE Solutions Obtained with Reduced-Order Deep Learning Surrogate Modelsby Yuanzhe…
Ancestral Reinforcement Learning: Unifying Zeroth-Order Optimization and Genetic Algorithms for Reinforcement Learningby So Nakashima, Tetsuya…
Value of Information and Reward Specification in Active Inference and POMDPsby Ran WeiFirst submitted to…
Graph Clustering with Cross-View Feature Propagationby Zhixuan Duan, Zuo Wang, Fanghui BiFirst submitted to arxiv…
Achieving More with Less: A Tensor-Optimization-Powered Ensemble Methodby Jinghui Yuan, Weijin Jiang, Zhe Cao, Fangyuan…
A Differential Smoothness-based Compact-Dynamic Graph Convolutional Network for Spatiotemporal Signal Recoveryby Pengcheng Gao, Zicheng Gao,…