196 citations · 1.4k across the 75 of their papers we have counts for
9 papers · 1 filter
A Distributed Block Chebyshev-Davidson Algorithm for Parallel Spectral Clustering
Qiyuan Pang, Haizhao Yang
We develop a distributed Block Chebyshev-Davidson algorithm to solve large-scale leading eigenvalue problems for spectral analysis in spectral clustering. First, the efficiency of…
What is the Solution for State-Adversarial Multi-Agent Reinforcement Learning?
Songyang Han, Sanbao Su, Sihong He +4
Various methods for Multi-Agent Reinforcement Learning (MARL) have been developed with the assumption that agents' policies are based on accurate state information. However, polici…
The Lottery Ticket Hypothesis for Self-attention in Convolutional Neural Network
Zhongzhan Huang, Senwei Liang, Mingfu Liang +3
Recently many plug-and-play self-attention modules (SAMs) are proposed to enhance the model generalization by exploiting the internal information of deep convolutional neural netwo…
Finite Expression Method for Solving High-Dimensional Partial Differential Equations
Senwei Liang, Haizhao Yang
Designing efficient and accurate numerical solvers for high-dimensional partial differential equations (PDEs) remains a challenging and important topic in computational science and…
Reinforced Inverse Scattering
Hanyang Jiang, Yuehaw Khoo, Haizhao Yang
Inverse wave scattering aims at determining the properties of an object using data on how the object scatters incoming waves. In order to collect information, sensors are put in di…
Neural Network Architecture Beyond Width and Depth
Zuowei Shen, Haizhao Yang, Shijun Zhang
This paper proposes a new neural network architecture by introducing an additional dimension called height beyond width and depth. Neural network architectures with height, width,…
IAE-Net: Integral Autoencoders for Discretization-Invariant Learning
Yong Zheng Ong, Zuowei Shen, Haizhao Yang
Discretization invariant learning aims at learning in the infinite-dimensional function spaces with the capacity to process heterogeneous discrete representations of functions as i…
From Optimization Dynamics to Generalization Bounds via Łojasiewicz Gradient Inequality
Fusheng Liu, Haizhao Yang, Soufiane Hayou +1
Optimization and generalization are two essential aspects of statistical machine learning. In this paper, we propose a framework to connect optimization with generalization by anal…
Deep Nonparametric Estimation of Operators between Infinite Dimensional Spaces
Hao Liu, Haizhao Yang, Minshuo Chen +2
Learning operators between infinitely dimensional spaces is an important learning task arising in wide applications in machine learning, imaging science, mathematical modeling and…