"low-rank approximation" Papers
17 papers found
Conference
Demystifying Language Model Forgetting with Low-rank Example Associations
Xisen Jin, Xiang Ren
Efficient Parametric SVD of Koopman Operator for Stochastic Dynamical Systems
Minchan Jeong, Jongha (Jon) Ryu, Se-Young Yun et al.
HOT: Hadamard-based Optimized Training
Seonggon Kim, Juncheol Shin, Seung-taek Woo et al.
QERA: an Analytical Framework for Quantization Error Reconstruction
Cheng Zhang, Jeffrey T. H. Wong, Can Xiao et al.
QSVD: Efficient Low-rank Approximation for Unified Query-Key-Value Weight Compression in Low-Precision Vision-Language Models
Yutong Wang, Haiyu Wang, Sai Qian Zhang
Spectral Perturbation Bounds for Low-Rank Approximation with Applications to Privacy
Phuc Tran, Van Vu, Nisheeth K. Vishnoi
SVDQuant: Absorbing Outliers by Low-Rank Component for 4-Bit Diffusion Models
Muyang Li, Yujun Lin, Zhekai Zhang et al.
Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin
Fangyikang Wang, Hubery Yin, Lei Qian et al.
Debiased Distribution Compression
Lingxiao Li, Raaz Dwivedi, Lester Mackey
Fast White-Box Adversarial Streaming Without a Random Oracle
Ying Feng, Aayush Jain, David Woodruff
LoRAP: Transformer Sub-Layers Deserve Differentiated Structured Compression for Large Language Models
guangyan li, Yongqiang Tang, Wensheng Zhang
LQER: Low-Rank Quantization Error Reconstruction for LLMs
Cheng Zhang, Jianyi Cheng, George Constantinides et al.
LRANet: Towards Accurate and Efficient Scene Text Detection with Low-Rank Approximation
Yuchen Su, Zhineng Chen, Zhiwen Shao et al.
On Computational Limits of Modern Hopfield Models: A Fine-Grained Complexity Analysis
Jerry Yao-Chieh Hu, Thomas Lin, Zhao Song et al.
Operator SVD with Neural Networks via Nested Low-Rank Approximation
Jongha (Jon) Ryu, Xiangxiang Xu, Hasan Sabri Melihcan Erol et al.
PELA: Learning Parameter-Efficient Models with Low-Rank Approximation
Yangyang Guo, Guangzhi Wang, Mohan Kankanhalli
Reshape and Adapt for Output Quantization (RAOQ): Quantization-aware Training for In-memory Computing Systems
Bonan Zhang, Chia-Yu Chen, Naveen Verma