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...
share
research
∙
02/18/2023
Bayesian Matrix Decomposition and Applications
The sole aim of this book is to give a self-contained introduction to co...
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...
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...
research
∙
08/22/2022
Robust Bayesian Nonnegative Matrix Factorization with Implicit Regularizers
We introduce a probabilistic model with implicit norm regularization for...
research
∙
08/16/2022
Subtype-Aware Dynamic Unsupervised Domain Adaptation
Unsupervised domain adaptation (UDA) has been successfully applied to tr...
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...
research
∙
06/29/2022
Comparative Study of Inference Methods for Interpolative Decomposition
In this paper, we propose a probabilistic model with automatic relevance...
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...
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...
research
∙
05/30/2022
Bayesian Low-Rank Interpolative Decomposition for Complex Datasets
In this paper, we introduce a probabilistic model for learning interpola...
research
∙
05/23/2022
Flexible and Hierarchical Prior for Bayesian Nonnegative Matrix Factorization
In this paper, we introduce a probabilistic model for learning nonnegati...
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...
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...
research
∙
02/23/2022
Exploring Classic Quantitative Strategies
The goal of this paper is to debunk and dispel the magic behind the blac...
research
∙
01/01/2022
Matrix Decomposition and Applications
In 1954, Alston S. Householder published Principles of Numerical Analysi...
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...
research
∙
11/15/2021
Fidelity-Guarantee Entanglement Routing in Quantum Networks
Entanglement routing establishes remote entanglement connection between ...
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...
research
∙
08/20/2021
A survey on Bayesian inference for Gaussian mixture model
Clustering has become a core technology in machine learning, largely due...
research
∙
08/10/2021
Revisit the Fundamental Theorem of Linear Algebra
This survey is meant to provide an introduction to the fundamental theor...
research
∙
07/28/2021
Recursively Conditional Gaussian for Ordinal Unsupervised Domain Adaptation
There has been a growing interest in unsupervised domain adaptation (UDA...
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 ...
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...
research
∙
05/10/2021
A rigorous introduction for linear models
This note is meant to provide an introduction to linear models and the t...
research
∙
01/01/2021
Subtype-aware Unsupervised Domain Adaptation for Medical Diagnosis
Recent advances in unsupervised domain adaptation (UDA) show that transf...
research
∙
01/01/2021
Identity-aware Facial Expression Recognition in Compressed Video
This paper targets to explore the inter-subject variations eliminated fa...
research
∙
01/01/2021
Energy-constrained Self-training for Unsupervised Domain Adaptation
Unsupervised domain adaptation (UDA) aims to transfer the knowledge on a...
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...
research
∙
11/27/2019
A race-DC in Big Data
The strategy of divide-and-combine (DC) has been widely used in the area...
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...
research
∙
02/15/2018
Reducing over-clustering via the powered Chinese restaurant process
Dirichlet process mixture (DPM) models tend to produce many small cluste...
research
∙
12/04/2017
