Demystifying Functional Random Forests: Novel Explainability Tools for Model Transparency in High-Dimensional Spacesby Fabrizio Maturo,…
Leveraging Unlabeled Data Sharing through Kernel Function Approximation in Offline Reinforcement Learningby Yen-Ru Lai, Fu-Chieh…
Tackling Data Heterogeneity in Federated Learning via Loss Decompositionby Shuang Zeng, Pengxin Guo, Shuai Wang,…
Neural Symbolic Logical Rule Learner for Interpretable Learningby Bowen Wei, Ziwei ZhuFirst submitted to arxiv…
Two-Timescale Gradient Descent Ascent Algorithms for Nonconvex Minimax Optimizationby Tianyi Lin, Chi Jin, Michael. I.…
An Asymptotically Optimal Coordinate Descent Algorithm for Learning Bayesian Networks from Gaussian Modelsby Tong Xu,…
Only Strict Saddles in the Energy Landscape of Predictive Coding Networks?by Francesco Innocenti, El Mehdi…
Time Series Foundation Models and Deep Learning Architectures for Earthquake Temporal and Spatial Nowcastingby Alireza…
QuaCK-TSF: Quantum-Classical Kernelized Time Series Forecastingby Abdallah Aaraba, Soumaya Cherkaoui, Ola Ahmad, Jean-Frédéric Laprade, Olivier…
CSPI-MT: Calibrated Safe Policy Improvement with Multiple Testing for Threshold Policiesby Brian M Cho, Ana-Roxana…