6 papers · 1 filter
Stochastic Heavy Ball with Polyak Step Size and Armijo Line Search: A General Convergence Analysis
Jiawei Zhang, Qitan Shi, Yuantao Gu
Polyak step size (PS) and Armijo line search (ALS) have received increasing attention in stochastic optimization, with encouraging empirical performance and theoretical guarantees.…
Quantization-Aware Kalman Estimation for Diffusion Sampling
Qitan Shi, Cheng Jin, Jiawei Zhang +1
Quantization offers a practical path to deploying diffusion models with reduced memory and computation, but aggressive compression can cause quantized outputs to deviate substantia…
Manifold-Constrained Noise Optimization for Diverse Diffusion Sampling
Qitan Shi, Cheng Jin, Ziyuan Liu +1
Few-step distilled diffusion models generate high-quality images quickly, but often lose per-prompt diversity, producing near-identical samples across random seeds. Optimizing the…
Distilling Drifting Transformers with Representation Autoencoders
Jiawei Zhang, Mengfei Xia, Gen Li +1
Despite the significant training acceleration and promising performance, Representation Autoencoders (RAEs) are mainly criticized for poor distillation effectiveness. In this work,…
Stage-wise Distortion-Perception Traversal in Zero-shot Inverse Problems with Diffusion Models
Jiawei Zhang, Ziyuan Liu, Leon Yan +2
The distortion-perception (D-P) tradeoff is a fundamental phenomenon of Bayesian inverse problems, which characterizes the inherent tension between distortion performance and perce…
Continuity and Ordinality Matter: Constraining Time Series Tokens for Effective Time Series Analysis with Large Language Models
Musheng Li, Ziying Zhang, Cheng jin +1
Token-based time series large language models (TS-LLMs) have emerged as a promising direction for time series analysis and reasoning. However, prior studies largely overlook the in…