Optimizing Cox Models with Stochastic Gradient Descent: Theoretical Foundations and Practical Guidancesby Lang Zeng, Weijing…
Alpha-VI DeepONet: A prior-robust variational Bayesian approach for enhancing DeepONets with uncertainty quantificationby Soban Nasir…
Downlink Channel Covariance Matrix Estimation via Representation Learning with Graph Regularizationby Melih Can Zerin, Elif…
Gaussian Process Kolmogorov-Arnold Networksby Andrew Siyuan ChenFirst submitted to arxiv on: 25 Jul 2024CategoriesMain: Machine…
Maximum Entropy On-Policy Actor-Critic via Entropy Advantage Estimationby Jean Seong Bjorn Choe, Jong-Kook KimFirst submitted…
A New Theoretical Perspective on Data Heterogeneity in Federated Optimizationby Jiayi Wang, Shiqiang Wang, Rong-Rong…
Learning to Steer Markovian Agents under Model Uncertaintyby Jiawei Huang, Vinzenz Thoma, Zebang Shen, Heinrich…
CONGO: Compressive Online Gradient Optimizationby Jeremy Carleton, Prathik Vijaykumar, Divyanshu Saxena, Dheeraj Narasimha, Srinivas Shakkottai,…
Discounted Pseudocosts in MILPby Krunal Kishor PatelFirst submitted to arxiv on: 7 Jul 2024CategoriesMain: Artificial…
ReCAP: Recursive Cross Attention Network for Pseudo-Label Generation in Robotic Surgical Skill Assessmentby Julien Quarez,…