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09/02/2023
Non-Asymptotic Bounds for Adversarial Excess Risk under Misspecified Models
We propose a general approach to evaluating the performance of robust es...
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03/19/2023
RKHS-based Latent Position Random Graph Correlation
In this article, we consider the problem of testing whether two latent p...
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03/02/2023
Identifiability and Consistent Estimation of the Gaussian Chain Graph Model
The chain graph model admits both undirected and directed edges in one g...
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02/05/2023
Crowdsourcing Utilizing Subgroup Structure of Latent Factor Modeling
Crowdsourcing has emerged as an alternative solution for collecting larg...
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11/17/2022
Transfer learning for tensor Gaussian graphical models
Tensor Gaussian graphical models (GGMs), interpreting conditional indepe...
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11/15/2022
Adaptive Embedding for Temporal Network
Temporal network has become ubiquitous with the rise of online social pl...
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07/30/2022
Efficient estimation and inference for the signed β-model in directed signed networks
This paper proposes a novel signed β-model for directed signed network, ...
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07/08/2022
Signed Network Embedding with Application to Simultaneous Detection of Communities and Anomalies
Signed networks are frequently observed in real life with additional sig...
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06/27/2022
Two ridge ratio criteria for multiple change point detection in tensors
This paper proposes two novel criteria for detecting change structures i...
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11/01/2021
Efficient Learning of Quadratic Variance Function Directed Acyclic Graphs via Topological Layers
Directed acyclic graph (DAG) models are widely used to represent causal ...
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11/01/2021
Learning linear non-Gaussian directed acyclic graph with diverging number of nodes
Acyclic model, often depicted as a directed acyclic graph (DAG), has bee...
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10/18/2021
Kernel-based estimation for partially functional linear model: Minimax rates and randomized sketches
This paper considers the partially functional linear model (PFLM) where ...
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03/28/2021
Community Detection in General Hypergraph via Graph Embedding
Network data has attracted tremendous attention in recent years, and mos...
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01/03/2019
Sparse Learning in reproducing kernel Hilbert space
Sparse learning aims to learn the sparse structure of the true target fu...
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10/04/2018
A statistical normalization method and differential expression analysis for RNA-seq data between different species
Background: High-throughput techniques bring novel tools but also statis...
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02/26/2018
Scalable kernel-based variable selection with sparsistency
Variable selection is central to high-dimensional data analysis, and var...
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06/19/2013
Joint estimation of sparse multivariate regression and conditional graphical models
Multivariate regression model is a natural generalization of the classic...
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01/30/2013
A note on selection stability: combining stability and prediction
Recently, many regularized procedures have been proposed for variable se...
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09/22/2012
An efficient model-free estimation of multiclass conditional probability
Conventional multiclass conditional probability estimation methods, such...
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08/16/2012