3 citations · 4 across the 6 of their papers we have counts for
6 papers
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…
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…
Local Convergence of Approximate Newton Method for Two Layer Nonlinear Regression
Zhihang Li, Zhao Song, Zifan Wang +1
There have been significant advancements made by large language models (LLMs) in various aspects of our daily lives. LLMs serve as a transformative force in natural language proces…
Revisiting Quantum Algorithms for Linear Regressions: Quadratic Speedups without Data-Dependent Parameters
Zhao Song, Junze Yin, Ruizhe Zhang
Linear regression is one of the most fundamental linear algebra problems. Given a dense matrix and a vector , the goal is to find such that…
The Expressibility of Polynomial based Attention Scheme
Zhao Song, Guangyi Xu, Junze Yin
Large language models (LLMs) have significantly improved various aspects of our daily lives. These models have impacted numerous domains, from healthcare to education, enhancing pr…
A Fast Optimization View: Reformulating Single Layer Attention in LLM Based on Tensor and SVM Trick, and Solving It in Matrix Multiplication Time
Yeqi Gao, Zhao Song, Weixin Wang +1
Large language models (LLMs) have played a pivotal role in revolutionizing various facets of our daily existence. Solving attention regression is a fundamental task in optimizing L…