82 citations · 170 across the 13 of their papers we have counts for
13 papers
TripHLApan: predicting HLA molecules binding peptides based on triple coding matrix and transfer learning
Meng Wang, Chuqi Lei, Jianxin Wang +2
Human leukocyte antigen (HLA) is an important molecule family in the field of human immunity, which recognizes foreign threats and triggers immune responses by presenting peptides…
Benchmarks for a Global Extraction of Information from Deeply Virtual Exclusive Scattering
Manal Almaeen, Jake Grigsby, Joshua Hoskins +4
We develop a framework to establish benchmarks for machine learning and deep neural networks analyses of exclusive scattering cross sections (FemtoNet). Within this framework we pr…
A Pseudo Label-wise Attention Network for Automatic ICD Coding
Yifan Wu, Min Zeng, Ying Yu +1
Automatic International Classification of Diseases (ICD) coding is defined as a kind of text multi-label classification problem, which is difficult because the number of labels is…
A survey of machine learning-based physics event generation
Yasir Alanazi, N. Sato, Pawel Ambrozewicz +5
Event generators in high-energy nuclear and particle physics play an important role in facilitating studies of particle reactions. We survey the state-of-the-art of machine learnin…
Simulation of electron-proton scattering events by a Feature-Augmented and Transformed Generative Adversarial Network (FAT-GAN)
Yasir Alanazi, N. Sato, Tianbo Liu +9
We apply generative adversarial network (GAN) technology to build an event generator that simulates particle production in electron-proton scattering that is free of theoretical as…
Faster Matrix Completion Using Randomized SVD
Xu Feng, Wenjian Yu, Yaohang Li
Matrix completion is a widely used technique for image inpainting and personalized recommender system, etc. In this work, we focus on accelerating the matrix completion using faste…
Gaussian Variant of Freivalds' Algorithm for Efficient and Reliable Matrix Product Verification
Hao Ji, Michael Mascagni, Yaohang Li
In this article, we consider the general problem of checking the correctness of matrix multiplication. Given three matrices , , and , the goal is to verify th…
Single-Pass PCA of Large High-Dimensional Data
Wenjian Yu, Yu Gu, Jian Li +2
Principal component analysis (PCA) is a fundamental dimension reduction tool in statistics and machine learning. For large and high-dimensional data, computing the PCA (i.e., the s…
A Fast Implementation of Singular Value Thresholding Algorithm using Recycling Rank Revealing Randomized Singular Value Decomposition
Yaohang Li, Wenjian Yu
In this paper, we present a fast implementation of the Singular Value Thresholding (SVT) algorithm for matrix completion. A rank-revealing randomized singular value decomposition (…
A Revisit of Block Power Methods for Finite State Markov Chain Applications
Hao Ji, Seth H. Weinberg, Yaohang Li
In this paper, we revisit the generalized block power methods for approximating the eigenvector associated with of a Markov chain transition matrix. Our analysis of the b…
Efficient Randomized Algorithms for the Fixed-Precision Low-Rank Matrix Approximation
Wenjian Yu, Yu Gu, Yaohang Li
Randomized algorithms for low-rank matrix approximation are investigated, with the emphasis on the fixed-precision problem and computational efficiency for handling large matrices.…
A Rank Revealing Randomized Singular Value Decomposition (R3SVD) Algorithm for Low-rank Matrix Approximations
Hao Ji, Wenjian Yu, Yaohang Li
In this paper, we present a Rank Revealing Randomized Singular Value Decomposition (R3SVD) algorithm to incrementally construct a low-rank approximation of a potentially large matr…
A GPU-based Large-scale Monte Carlo Simulation Method for Systems with Long-range Interactions
Yihao Liang, Xiangjun Xing, Yaohang Li
In this work we present an efficient implementation of Canonical Monte Carlo simulation for Coulomb many body systems on graphics processing units (GPU). Our method takes advantage…