Geometrically Inspired Kernel Machines for Collaborative Learning Beyond Gradient Descentby Mohit Kumar, Alexander Valentinitsch, Magdalena…
Uncertainty-Guided Optimization on Large Language Model Search Treesby Julia Grosse, Ruotian Wu, Ahmad Rashid, Philipp…
ROER: Regularized Optimal Experience Replayby Changling Li, Zhang-Wei Hong, Pulkit Agrawal, Divyansh Garg, Joni PajarinenFirst…
Robust Learning under Hybrid Noiseby Yang Wei, Shuo Chen, Shanshan Ye, Bo Han, Chen GongFirst…
Mixture of A Million Expertsby Xu Owen HeFirst submitted to arxiv on: 4 Jul 2024CategoriesMain:…
NeuroSteiner: A Graph Transformer for Wirelength Estimationby Sahil Manchanda, Dana Kianfar, Markus Peschl, Romain Lepert,…
Bias of Stochastic Gradient Descent or the Architecture: Disentangling the Effects of Overparameterization of Neural…
Geodesic Optimization for Predictive Shift Adaptation on EEG databy Apolline Mellot, Antoine Collas, Sylvain Chevallier,…
Decision-Focused Evaluation of Worst-Case Distribution Shiftby Kevin Ren, Yewon Byun, Bryan WilderFirst submitted to arxiv…
Learning Scalable Model Soup on a Single GPU: An Efficient Subspace Training Strategyby Tao Li,…