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08/07/2023
Multi-Label Self-Supervised Learning with Scene Images
Self-supervised learning (SSL) methods targeting scene images have seen ...
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07/20/2023
Quantized Feature Distillation for Network Quantization
Neural network quantization aims to accelerate and trim full-precision n...
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06/08/2023
Matrix GARCH Model: Inference and Application
Matrix-variate time series data are largely available in applications. H...
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06/07/2023
Coarse Is Better? A New Pipeline Towards Self-Supervised Learning with Uncurated Images
Most self-supervised learning (SSL) methods often work on curated datase...
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05/27/2023
Instance-based Max-margin for Practical Few-shot Recognition
In order to mimic the human few-shot learning (FSL) ability better and t...
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02/14/2023
Quantiled conditional variance, skewness, and kurtosis by Cornish-Fisher expansion
The conditional variance, skewness, and kurtosis play a central role in ...
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01/27/2023
Big portfolio selection by graph-based conditional moments method
How to do big portfolio selection is very important but challenging for ...
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01/17/2023
Statistical inference for the logarithmic spatial heteroskedasticity model with exogenous variables
The spatial dependence in mean has been well studied by plenty of models...
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09/23/2021
Blocking, rerandomization, and regression adjustment in randomized experiments with high-dimensional covariates
Blocking, a special case of rerandomization, is routinely implemented in...
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08/05/2021
Residual Attention: A Simple but Effective Method for Multi-Label Recognition
Multi-label image recognition is a challenging computer vision task of p...
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06/06/2021
Path-specific Effects Based on Information Accounts of Causality
Path-specific effects in mediation analysis provide a useful tool for fa...
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03/24/2021
Pair-switching rerandomization
Rerandomization discards assignments with covariates unbalanced in the t...
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09/20/2020
Confidence intervals for parameters in high-dimensional sparse vector autoregression
Vector autoregression (VAR) models are widely used to analyze the interr...
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08/03/2020
Testing error distribution by kernelized Stein discrepancy in multivariate time series models
Knowing the error distribution is important in many multivariate time se...
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04/20/2020
Multi-frequency-band tests for white noise under heteroskedasticity
This paper proposes a new family of multi-frequency-band (MFB) tests for...
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11/21/2019
Hybrid quantile estimation for asymmetric power GARCH models
Asymmetric power GARCH models have been widely used to study the higher ...
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07/09/2019
Adaptive inference for a semiparametric GARCH model
This paper considers a semiparametric generalized autoregressive conditi...
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05/06/2019
Non-standard inference for augmented double autoregressive models with null volatility coefficients
This paper considers an augmented double autoregressive (DAR) model, whi...
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03/26/2019
Time series models for realized covariance matrices based on the matrix-F distribution
We propose a new Conditional BEKK matrix-F (CBF) model for the time-vary...
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04/26/2018
New HSIC-based tests for independence between two stationary multivariate time series
This paper proposes some novel one-sided omnibus tests for independence ...
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04/06/2018
Statistical inference for autoregressive models under heteroscedasticity of unknown form
This paper provides an entire inference procedure for the autoregressive...
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02/18/2018
