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cs.LG2024
Inverting the Leverage Score Gradient: An Efficient Approximate Newton Method
Chenyang Li, Zhao Song, Zhaoxing Xu +1
Leverage scores have become essential in statistics and machine learning, aiding regression analysis, randomized matrix computations, and various other tasks. This paper delves int…
cs.LG2024
Conv-Basis: A New Paradigm for Efficient Attention Inference and Gradient Computation in Transformers
Yingyu Liang, Heshan Liu, Zhenmei Shi +3
The self-attention mechanism is the key to the success of transformers in recent Large Language Models (LLMs). However, the quadratic computational cost in the input seque…
cs.LG2024
How to Inverting the Leverage Score Distribution?
Zhihang Li, Zhao Song, Weixin Wang +2
Leverage score is a fundamental problem in machine learning and theoretical computer science. It has extensive applications in regression analysis, randomized algorithms, and neura…