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🏢 UC San Diego

DiffuserLite: Towards Real-time Diffusion Planning
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AI Applications Robotics 🏢 UC San Diego
DiffuserLite: a super-fast diffusion planning framework achieving real-time performance (122Hz).
Differentially Private Reinforcement Learning with Self-Play
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AI Theory Privacy 🏢 UC San Diego
This paper presents DP-Nash-VI, a novel algorithm ensuring trajectory-wise privacy in multi-agent reinforcement learning, achieving near-optimal regret bounds under both joint and local differential p…
Continuous Partitioning for Graph-Based Semi-Supervised Learning
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Machine Learning Semi-Supervised Learning 🏢 UC San Diego
CutSSL: a novel framework for graph-based semi-supervised learning, surpasses state-of-the-art accuracy by solving a continuous nonconvex quadratic program that provably yields integer solutions, exce…
Clustering with Non-adaptive Subset Queries
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Machine Learning Unsupervised Learning 🏢 UC San Diego
This paper introduces novel non-adaptive algorithms for clustering using subset queries, achieving near-linear query complexity and improving upon existing limitations of pairwise query methods.
Average gradient outer product as a mechanism for deep neural collapse
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AI Theory Optimization 🏢 UC San Diego
Deep Neural Collapse (DNC) explained via Average Gradient Outer Product (AGOP).
Adapting Diffusion Models for Improved Prompt Compliance and Controllable Image Synthesis
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Computer Vision Image Generation 🏢 UC San Diego
FG-DMs revolutionize image synthesis by jointly modeling image and condition distributions, achieving higher object recall and enabling flexible editing.
Accelerating Transformers with Spectrum-Preserving Token Merging
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Multimodal Learning Vision-Language Models 🏢 UC San Diego
PITOME: a novel token merging method accelerates Transformers by 40-60% while preserving accuracy, prioritizing informative tokens via an energy score.