Summary of A Naive Aggregation Algorithm For Improving Generalization in a Class Of Learning Problems, by Getachew K Befekadu
A naive aggregation algorithm for improving generalization in a class of learning problemsby Getachew K…
Summary of Leveraging Machine Learning For Official Statistics: a Statistical Manifesto, by Marco Puts et al.
Leveraging Machine Learning for Official Statistics: A Statistical Manifestoby Marco Puts, David Salgado, Piet DaasFirst…
Summary of Algorithm Configuration For Structured Pfaffian Settings, by Maria-florina Balcan et al.
Algorithm Configuration for Structured Pfaffian Settingsby Maria-Florina Balcan, Anh Tuan Nguyen, Dravyansh SharmaFirst submitted to…
Summary of Can We Theoretically Quantify the Impacts Of Local Updates on the Generalization Performance Of Federated Learning?, by Peizhong Ju et al.
Can We Theoretically Quantify the Impacts of Local Updates on the Generalization Performance of Federated…
Summary of The Influence Of Faulty Labels in Data Sets on Human Pose Estimation, by Arnold Schwarz et al.
The Influence of Faulty Labels in Data Sets on Human Pose Estimationby Arnold Schwarz, Levente…
Summary of Active Sampling Of Interpolation Points to Identify Dominant Subspaces For Model Reduction, by Celine Reddig et al.
Active Sampling of Interpolation Points to Identify Dominant Subspaces for Model Reductionby Celine Reddig, Pawan…
Summary of Overfitting Behaviour Of Gaussian Kernel Ridgeless Regression: Varying Bandwidth or Dimensionality, by Marko Medvedev et al.
Overfitting Behaviour of Gaussian Kernel Ridgeless Regression: Varying Bandwidth or Dimensionalityby Marko Medvedev, Gal Vardi,…
Summary of Understanding Fairness in Recommender Systems: a Healthcare Perspective, by Veronica Kecki et al.
Understanding Fairness in Recommender Systems: A Healthcare Perspectiveby Veronica Kecki, Alan SaidFirst submitted to arxiv…
Summary of On the Convergence Rates Of Federated Q-learning Across Heterogeneous Environments, by Muxing Wang et al.
On the Convergence Rates of Federated Q-Learning across Heterogeneous Environmentsby Muxing Wang, Pengkun Yang, Lili…
Summary of Watermas: Sharpness-aware Maximization For Neural Network Watermarking, by Carl De Sousa Trias et al.
WaterMAS: Sharpness-Aware Maximization for Neural Network Watermarkingby Carl De Sousa Trias, Mihai Mitrea, Attilio Fiandrotti,…