Summary of Limit Theorems For Stochastic Gradient Descent with Infinite Variance, by Jose Blanchet et al.
Limit Theorems for Stochastic Gradient Descent with Infinite Varianceby Jose Blanchet, Aleksandar Mijatović, Wenhao YangFirst…
Limit Theorems for Stochastic Gradient Descent with Infinite Varianceby Jose Blanchet, Aleksandar Mijatović, Wenhao YangFirst…
Data Augmentation via Diffusion Model to Enhance AI Fairnessby Christina Hastings Blow, Lijun Qian, Camille…
Advancements In Heart Disease Prediction: A Machine Learning Approach For Early Detection And Risk Assessmentby…
Comparison of deep learning and conventional methods for disease onset predictionby Luis H. John, Chungsoo…
Unlocking FedNL: Self-Contained Compute-Optimized Implementationby Konstantin Burlachenko, Peter RichtárikFirst submitted to arxiv on: 11 Oct…
Graph Network Models To Detect Illicit Transactions In Block Chainby Hrushyang Adloori, Vaishnavi Dasanapu, Abhijith…
Adversarial Vulnerability as a Consequence of On-Manifold Inseparibilityby Rajdeep Haldar, Yue Xing, Qifan Song, Guang…
Distributionally Robust Clustered Federated Learning: A Case Study in Healthcareby Xenia Konti, Hans Riess, Manos…
Shap-Select: Lightweight Feature Selection Using SHAP Values and Regressionby Egor Kraev, Baran Koseoglu, Luca Traverso,…
Grokking at the Edge of Linear Separabilityby Alon Beck, Noam Levi, Yohai Bar-SinaiFirst submitted to…