4 citations · 7 across the 6 of their papers we have counts for
9 papers
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…
Efficient Algorithm for Solving Hyperbolic Programs
Yichuan Deng, Zhao Song, Lichen Zhang +1
Hyperbolic polynomials is a class of real-roots polynomials that has wide range of applications in theoretical computer science. Each hyperbolic polynomial also induces a hyperboli…
Bypass Exponential Time Preprocessing: Fast Neural Network Training via Weight-Data Correlation Preprocessing
Josh Alman, Jiehao Liang, Zhao Song +2
Over the last decade, deep neural networks have transformed our society, and they are already widely applied in various machine learning applications. State-of-art deep neural netw…
Quantum Speedups of Optimizing Approximately Convex Functions with Applications to Logarithmic Regret Stochastic Convex Bandits
Tongyang Li, Ruizhe Zhang
We initiate the study of quantum algorithms for optimizing approximately convex functions. Given a convex set and a function $F\colon\mathbb{R}^{n…
Fast Distance Oracles for Any Symmetric Norm
Yichuan Deng, Zhao Song, Omri Weinstein +1
In the Distance Oracle problem, the goal is to preprocess vectors in a -dimensional metric space into a cheap data st…
Does Preprocessing Help Training Over-parameterized Neural Networks?
Zhao Song, Shuo Yang, Ruizhe Zhang
Deep neural networks have achieved impressive performance in many areas. Designing a fast and provable method for training neural networks is a fundamental question in machine lear…