b'Jiang Hu'

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research

∙ 04/03/2023

Two-sample test of sparse stochastic block models

The paper discusses a statistical problem related to testing for differe...

0 Qianyong Wu, et al. ∙

research

∙ 03/31/2023

Decentralized Weakly Convex Optimization Over the Stiefel Manifold

We focus on a class of non-smooth optimization problems over the Stiefel...

0 Jinxin Wang, et al. ∙

research

∙ 03/30/2023

KOO approach for scalable variable selection problem in large-dimensional regression

An important issue in many multivariate regression problems is to elimin...

0 Zhidong Bai, et al. ∙

research

∙ 03/27/2023

Machine Learning for Microprocessor Performance Bug Localization

The validation process for microprocessors is a very complex task that c...

0 Erick Carvajal Barboza, et al. ∙

research

∙ 03/25/2023

A spectral based goodness-of-fit test for stochastic block models

Community detection in complex networks has attracted considerable atten...

0 Qianyong Wu, et al. ∙

research

∙ 03/22/2023

No Eigenvalues Outside the Support of the Limiting Spectral Distribution of Large Dimensional noncentral Sample Covariance Matrices

Let _n =1/n(_n + ^1/2_n _n)(_n + ^1/2_n _n)^*, where _n is a p × n matri...

0 Zhidong Bai, et al. ∙

research

∙ 03/16/2023

Decentralized Riemannian natural gradient methods with Kronecker-product approximations

With a computationally efficient approximation of the second-order infor...

0 Jiang Hu, et al. ∙

research

∙ 02/03/2023

Analysis of the limiting spectral distribution of large dimensional General information-plus-noise type matrices

In this paper, we derive the analytical behavior of the limiting spectra...

0 Huanchao Zhou, et al. ∙

research

∙ 01/27/2023

Sampling without replacement from a high-dimensional finite population

It is well known that most of the existing theoretical results in statis...

0 Jiang Hu, et al. ∙

research

∙ 12/12/2022

A CLT for the LSS of large dimensional sample covariance matrices with diverging spikes

In this paper, we establish the central limit theorem (CLT) for linear s...

0 Zhijun Liu, et al. ∙

research

∙ 07/15/2022

Riemannian Natural Gradient Methods

This paper studies large-scale optimization problems on Riemannian manif...

0 Jiang Hu, et al. ∙

research

∙ 07/13/2022

Spectral Statistics of Sample Block Correlation Matrices

A fundamental concept in multivariate statistics, sample correlation mat...

0 Zhigang Bao, et al. ∙

research

∙ 05/15/2022

A CLT for the LSS of large dimensional sample covariance matrices with unbounded dispersions

In this paper, we establish the central limit theorem (CLT) for linear s...

0 Zhijun Liu, et al. ∙

research

∙ 03/30/2022

Towards Collaborative Intelligence: Routability Estimation based on Decentralized Private Data

Applying machine learning (ML) in design flow is a popular trend in EDA ...

0 Jingyu Pan, et al. ∙

research

∙ 01/28/2022

The limiting spectral distribution of large dimensional general information-plus-noise type matrices

Let X_n be n× N random complex matrices, R_n and T_n be non-random compl...

0 Huanchao Zhou, et al. ∙

research

∙ 04/10/2021

Spiked eigenvalues of noncentral Fisher matrix with applications

In this paper, we investigate the asymptotic behavior of spiked eigenval...

0 Xiaozhuo Zhang, et al. ∙

research

∙ 02/19/2021

Toward Taming the Overhead Monster for Data-Flow Integrity

Data-Flow Integrity (DFI) is a well-known approach to effectively detect...

0 Lang Feng, et al. ∙

research

∙ 12/03/2020

Automatic Routability Predictor Development Using Neural Architecture Search

The rise of machine learning technology inspires a boom of its applicati...

0 Jingyu Pan, et al. ∙

research

∙ 11/27/2020

Net2: A Graph Attention Network Method Customized for Pre-Placement Net Length Estimation

Net length is a key proxy metric for optimizing timing and power across ...

0 Zhiyao Xie, et al. ∙

research

∙ 11/26/2020

PowerNet: Transferable Dynamic IR Drop Estimation via Maximum Convolutional Neural Network

IR drop is a fundamental constraint required by almost all chip designs....

0 Zhiyao Xie, et al. ∙

research

∙ 11/26/2020

FIST: A Feature-Importance Sampling and Tree-Based Method for Automatic Design Flow Parameter Tuning

Design flow parameters are of utmost importance to chip design quality a...

0 Zhiyao Xie, et al. ∙

research

∙ 11/26/2020

Fast IR Drop Estimation with Machine Learning

IR drop constraint is a fundamental requirement enforced in almost all c...

0 Zhiyao Xie, et al. ∙

research

∙ 11/17/2020

Automatic Microprocessor Performance Bug Detection

Processor design validation and debug is a difficult and complex task, w...

0 Erick Carvajal Barboza, et al. ∙

research

∙ 08/24/2020

ALIGN: A System for Automating Analog Layout

ALIGN ("Analog Layout, Intelligently Generated from Netlists") is an ope...

0 Tonmoy Dhar, et al. ∙

research

∙ 01/02/2020

Modified Pillai's trace statistics for two high-dimensional sample covariance matrices

The goal of this study was to test the equality of two covariance matric...

0 Qiuyan Zhang, et al. ∙

research

∙ 12/06/2019

The limits of the sample spiked eigenvalues for a high-dimensional generalized Fisher matrix and its applications

A generalized spiked Fisher matrix is considered in this paper. We estab...

0 Dandan Jiang, et al. ∙

research

∙ 06/16/2019

Community Detection Based on the L_∞ convergence of eigenvectors in DCBM

Spectral clustering is one of the most popular algorithms for community ...

0 Yan Liu, et al. ∙

research

∙ 10/30/2018

Strong consistency of the AIC, BIC, C_p and KOO methods in high-dimensional multivariate linear regression

Variable selection is essential for improving inference and interpretati...

0 Zhidong Bai, et al. ∙

research

∙ 03/21/2018

High-dimensional covariance matrices in elliptical distributions with application to spherical test

This paper discusses fluctuations of linear spectral statistics of high-...

0 Jiang Hu, et al. ∙