activity
20142023
most citedA Convergence Theory for Deep Learning via Over-Parameterization

688 citations · 1.5k across the 49 of their papers we have counts for

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Showing 2023Show all

9 papers · 1 filter

cs.DS2023

Sparse Convolution for Approximate Sparse Instance

Xiaoxiao Li, Zhao Song, Guangyi Zhang

Computing the convolution of two vectors of dimension is one of the most important computational primitives in many fields. For the non-negative convolution scenari…

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.DS2023

Solving Tensor Low Cycle Rank Approximation

Yichuan Deng, Yeqi Gao, Zhao Song

Large language models have become ubiquitous in modern life, finding applications in various domains such as natural language processing, language translation, and speech recogniti…

cs.DS2023★ 3 cited

Randomized and Deterministic Attention Sparsification Algorithms for Over-parameterized Feature Dimension

Yichuan Deng, Sridhar Mahadevan, Zhao Song

Large language models (LLMs) have shown their power in different areas. Attention computation, as an important subroutine of LLMs, has also attracted interests in theory. Recently…

cs.DS2023★ 3 cited

Algorithm and Hardness for Dynamic Attention Maintenance in Large Language Models

Jan van den Brand, Zhao Song, Tianyi Zhou

Large language models (LLMs) have made fundamental changes in human life. The attention scheme is one of the key components over all the LLMs, such as BERT, GPT-1, Transformers, GP…

cs.LG2023★ 7 cited

An Over-parameterized Exponential Regression

Yeqi Gao, Sridhar Mahadevan, Zhao Song

Over the past few years, there has been a significant amount of research focused on studying the ReLU activation function, with the aim of achieving neural network convergence thro…

cs.IT2023★ 2 cited

An Improved Sample Complexity for Rank-1 Matrix Sensing

Yichuan Deng, Zhihang Li, Zhao Song

Matrix sensing is a problem in signal processing and machine learning that involves recovering a low-rank matrix from a set of linear measurements. The goal is to reconstruct the o…

cs.LG2023★ 6 cited

Solving Regularized Exp, Cosh and Sinh Regression Problems

Zhihang Li, Zhao Song, Tianyi Zhou

In modern machine learning, attention computation is a fundamental task for training large language models such as Transformer, GPT-4 and ChatGPT. In this work, we study exponentia…

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 …