Sparsity regularization via tree-structured environments for disentangled representationsby Elliot Layne, Jason Hartford, Sébastien Lachapelle, Mathieu…
Unified Explanations in Machine Learning Models: A Perturbation Approachby Jacob Dineen, Don Kridel, Daniel Dolk,…
Exploring Diffusion Models’ Corruption Stage in Few-Shot Fine-tuning and Mitigating with Bayesian Neural Networksby Xiaoyu…
Task-Agnostic Machine-Learning-Assisted Inferenceby Jiacheng Miao, Qiongshi LuFirst submitted to arxiv on: 30 May 2024CategoriesMain: Machine…
Fourier Controller Networks for Real-Time Decision-Making in Embodied Learningby Hengkai Tan, Songming Liu, Kai Ma,…
Efficient Trajectory Inference in Wasserstein Space Using Consecutive Averagingby Amartya Banerjee, Harlin Lee, Nir Sharon,…
Diffusion Policies creating a Trust Region for Offline Reinforcement Learningby Tianyu Chen, Zhendong Wang, Mingyuan…
SpecDec++: Boosting Speculative Decoding via Adaptive Candidate Lengthsby Kaixuan Huang, Xudong Guo, Mengdi WangFirst submitted…
LLM as a Complementary Optimizer to Gradient Descent: A Case Study in Prompt Tuningby Zixian…
Faster Cascades via Speculative Decodingby Harikrishna Narasimhan, Wittawat Jitkrittum, Ankit Singh Rawat, Seungyeon Kim, Neha…