activity
20202024
most citedDynamical Fractal: Theory and Case Study

10 citations · 39 across the 22 of their papers we have counts for

collaborators
Showing 2023 · cs.LGShow all

11 papers · 2 filters

cs.LG2023★ 1 cited

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…

cs.LG2023

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…

cs.LG2023★ 1 cited

A Unified Scheme of ResNet and Softmax

Zhao Song, Weixin Wang, Junze Yin

Large language models (LLMs) have brought significant changes to human society. Softmax regression and residual neural networks (ResNet) are two important techniques in deep learni…

cs.LG2023★ 6 cited

GradientCoin: A Peer-to-Peer Decentralized Large Language Models

Yeqi Gao, Zhao Song, Junze Yin

Since 2008, after the proposal of a Bitcoin electronic cash system, Bitcoin has fundamentally changed the economic system over the last decade. Since 2022, large language models (L…

cs.LG2023★ 1 cited

Solving Attention Kernel Regression Problem via Pre-conditioner

Zhao Song, Junze Yin, Lichen Zhang

The attention mechanism is the key to large language models, and the attention matrix serves as an algorithmic and computational bottleneck for such a scheme. In this paper, we def…

cs.LG2023

Query Complexity of Active Learning for Function Family With Nearly Orthogonal Basis

Xiang Chen, Zhao Song, Baocheng Sun +2

Many machine learning algorithms require large numbers of labeled data to deliver state-of-the-art results. In applications such as medical diagnosis and fraud detection, though th…

cs.LG2023★ 1 cited

Efficient Alternating Minimization with Applications to Weighted Low Rank Approximation

Zhao Song, Mingquan Ye, Junze Yin +1

Weighted low rank approximation is a fundamental problem in numerical linear algebra, and it has many applications in machine learning. Given a matrix $M \in \mathbb{R}^{n \times n…

cs.LG2023★ 1 cited

Faster Robust Tensor Power Method for Arbitrary Order

Yichuan Deng, Zhao Song, Junze Yin

Tensor decomposition is a fundamental method used in various areas to deal with high-dimensional data. \emph{Tensor power method} (TPM) is one of the widely-used techniques in the…

cs.LG2023★ 1 cited

Federated Empirical Risk Minimization via Second-Order Method

Song Bian, Zhao Song, Junze Yin

Many convex optimization problems with important applications in machine learning are formulated as empirical risk minimization (ERM). There are several examples: linear and logist…

cs.LG2023★ 7 cited

An Iterative Algorithm for Rescaled Hyperbolic Functions Regression

Yeqi Gao, Zhao Song, Junze Yin

Large language models (LLMs) have numerous real-life applications across various domains, such as natural language translation, sentiment analysis, language modeling, chatbots and…

cs.LG2023★ 3 cited

Low Rank Matrix Completion via Robust Alternating Minimization in Nearly Linear Time

Yuzhou Gu, Zhao Song, Junze Yin +1

Given a matrix , the low rank matrix completion problem asks us to find a rank- approximation of as for …