b'Jun Lu'

research

∙ 03/01/2023

DMSA: Dynamic Multi-scale Unsupervised Semantic Segmentation Based on Adaptive Affinity

The proposed method in this paper proposes an end-to-end unsupervised se...

0 Kun Yang, et al. ∙

research

∙ 02/18/2023

Bayesian Matrix Decomposition and Applications

The sole aim of this book is to give a self-contained introduction to co...

0 Jun Lu, et al. ∙

research

∙ 09/29/2022

Feature Selection via the Intervened Interpolative Decomposition and its Application in Diversifying Quantitative Strategies

In this paper, we propose a probabilistic model for computing an interpo...

0 Jun Lu, et al. ∙

research

∙ 08/26/2022

Constraining Pseudo-label in Self-training Unsupervised Domain Adaptation with Energy-based Model

Deep learning is usually data starved, and the unsupervised domain adapt...

0 Lingsheng Kong, et al. ∙

research

∙ 08/22/2022

Robust Bayesian Nonnegative Matrix Factorization with Implicit Regularizers

We introduce a probabilistic model with implicit norm regularization for...

0 Jun Lu, et al. ∙

research

∙ 08/16/2022

Subtype-Aware Dynamic Unsupervised Domain Adaptation

Unsupervised domain adaptation (UDA) has been successfully applied to tr...

0 Xiaofeng Liu, et al. ∙

research

∙ 07/08/2022

A note on VIX for postprocessing quantitative strategies

In this note, we introduce how to use Volatility Index (VIX) for postpro...

0 Jun Lu, et al. ∙

research

∙ 06/29/2022

Comparative Study of Inference Methods for Interpolative Decomposition

In this paper, we propose a probabilistic model with automatic relevance...

0 Jun Lu, et al. ∙

research

∙ 06/05/2022

A weighted average distributed estimator for high dimensional parameter

In this paper, a new weighted average estimator (WAVE) is proposed to en...

0 Jun Lu, et al. ∙

research

∙ 06/04/2022

Feature screening for multi-response linear models by empirical likelihood

This paper proposes a new feature screening method for the multi-respons...

0 Jun Lu, et al. ∙

research

∙ 05/30/2022

Bayesian Low-Rank Interpolative Decomposition for Complex Datasets

In this paper, we introduce a probabilistic model for learning interpola...

0 Jun Lu, et al. ∙

research

∙ 05/23/2022

Flexible and Hierarchical Prior for Bayesian Nonnegative Matrix Factorization

In this paper, we introduce a probabilistic model for learning nonnegati...

0 Jun Lu, et al. ∙

research

∙ 05/02/2022

Gradient Descent, Stochastic Optimization, and Other Tales

The goal of this paper is to debunk and dispel the magic behind black-bo...

0 Jun Lu, et al. ∙

research

∙ 04/02/2022

AdaSmooth: An Adaptive Learning Rate Method based on Effective Ratio

It is well known that we need to choose the hyper-parameters in Momentum...

0 Jun Lu, et al. ∙

research

∙ 02/23/2022

Exploring Classic Quantitative Strategies

The goal of this paper is to debunk and dispel the magic behind the blac...

0 Jun Lu, et al. ∙

research

∙ 01/01/2022

Matrix Decomposition and Applications

In 1954, Alston S. Householder published Principles of Numerical Analysi...

386 Jun Lu, et al. ∙

research

∙ 11/23/2021

On the Column and Row Ranks of a Matrix

Every m by n matrix A with rank r has exactly r independent rows and r i...

0 Jun Lu, et al. ∙

research

∙ 11/15/2021

Fidelity-Guarantee Entanglement Routing in Quantum Networks

Entanglement routing establishes remote entanglement connection between ...

0 Jian Li, et al. ∙

research

∙ 09/06/2021

End to end hyperspectral imaging system with coded compression imaging process

Hyperspectral images (HSIs) can provide rich spatial and spectral inform...

10 Hui Xie, et al. ∙

research

∙ 08/20/2021

A survey on Bayesian inference for Gaussian mixture model

Clustering has become a core technology in machine learning, largely due...

231 Jun Lu, et al. ∙

research

∙ 08/10/2021

Revisit the Fundamental Theorem of Linear Algebra

This survey is meant to provide an introduction to the fundamental theor...

277 Jun Lu, et al. ∙

research

∙ 07/28/2021

Recursively Conditional Gaussian for Ordinal Unsupervised Domain Adaptation

There has been a growing interest in unsupervised domain adaptation (UDA...

0 Xiaofeng Liu, et al. ∙

research

∙ 07/22/2021

Domain Generalization under Conditional and Label Shifts via Variational Bayesian Inference

In this work, we propose a domain generalization (DG) approach to learn ...

0 Xiaofeng Liu, et al. ∙

research

∙ 07/06/2021

Numerical Matrix Decomposition and its Modern Applications: A Rigorous First Course

Matrix decomposition has become a core technology in machine learning, l...

1 Jun Lu, et al. ∙

research

∙ 05/10/2021

A rigorous introduction for linear models

This note is meant to provide an introduction to linear models and the t...

12 Jun Lu, et al. ∙

research

∙ 01/01/2021

Subtype-aware Unsupervised Domain Adaptation for Medical Diagnosis

Recent advances in unsupervised domain adaptation (UDA) show that transf...

0 Xiaofeng Liu, et al. ∙

research

∙ 01/01/2021

Identity-aware Facial Expression Recognition in Compressed Video

This paper targets to explore the inter-subject variations eliminated fa...

0 Xiaofeng Liu, et al. ∙

research

∙ 01/01/2021

Energy-constrained Self-training for Unsupervised Domain Adaptation

Unsupervised domain adaptation (UDA) aims to transfer the knowledge on a...

0 Xiaofeng Liu, et al. ∙

research

∙ 08/20/2020

Unified Rules of Renewable Weighted Sums for Various Online Updating Estimations

This paper establishes unified frameworks of renewable weighted sums (RW...

0 Lu Lin, et al. ∙

research

∙ 11/27/2019

A race-DC in Big Data

The strategy of divide-and-combine (DC) has been widely used in the area...

0 Lu Lin, et al. ∙

research

∙ 04/27/2018

CompNet: Neural networks growing via the compact network morphism

It is often the case that the performance of a neural network can be imp...

0 Jun Lu, et al. ∙

research

∙ 02/15/2018

Reducing over-clustering via the powered Chinese restaurant process

Dirichlet process mixture (DPM) models tend to produce many small cluste...

0 Jun Lu, et al. ∙

research

∙ 12/04/2017

An Equivalence of Fully Connected Layer and Convolutional Layer

This article demonstrates that convolutional operation can be converted ...

0 Wei Ma, et al. ∙

Jun Lu

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