Summary of A Two-stage Learning-to-defer Approach For Multi-task Learning, by Yannis Montreuil et al.
A Two-Stage Learning-to-Defer Approach for Multi-Task Learningby Yannis Montreuil, Shu Heng Yeo, Axel Carlier, Lai…
A Two-Stage Learning-to-Defer Approach for Multi-Task Learningby Yannis Montreuil, Shu Heng Yeo, Axel Carlier, Lai…
Multiple Kernel Clustering via Local Regression Integrationby Liang Du, Xin Ren, Haiying Zhang, Peng ZhouFirst…
Controllable RANSAC-based Anomaly Detection via Hypothesis Testingby Le Hong Phong, Ho Ngoc Luat, Vo Nguyen…
Learning Infinite-Horizon Average-Reward Linear Mixture MDPs of Bounded Spanby Woojin Chae, Kihyuk Hong, Yufan Zhang,…
FIT-GNN: Faster Inference Time for GNNs Using Coarseningby Shubhajit Roy, Hrriday Ruparel, Kishan Ved, Anirban…
Diffusion-based Semi-supervised Spectral Algorithm for Regression on Manifoldsby Weichun Xia, Jiaxin Jiang, Lei ShiFirst submitted…
A Statistical Machine Learning Approach for Adapting Reduced-Order Models using Projected Gaussian Processby Xiao Liu,…
A Mirror Descent Perspective of Smoothed Sign Descentby Shuyang Wang, Diego KlabjanFirst submitted to arxiv…
Diffusing States and Matching Scores: A New Framework for Imitation Learningby Runzhe Wu, Yiding Chen,…
Mixed-curvature decision trees and random forestsby Philippe Chlenski, Quentin Chu, Raiyan R. Khan, Kaizhu Du,…