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Jing An

4 accepted papers

2025

Dual Attention-Aided Cooperative Deep-Spatiotemporal-Feature-Extraction Network for Semi-Supervised Soft Sensing

RA-L 2025

Soft sensing is a promising solution to predict key quality variables in various industries. One of the major obstacles to building an accurate data-driven soft sensor is the scarcity of labeled data and the challenge of extracting useful information from unlabeled data. To mitigate this issue, this

Cited by 4SourceScholar
2023

Critical Points and Convergence Analysis of Generative Deep Linear Networks Trained with Bures-Wasserstein Loss

ICML 2023poster

We consider a deep matrix factorization model of covariance matrices trained with the Bures-Wasserstein distance. While recent works have made advances in the study of the optimization problem for overparametrized low-rank matrix approximation, much emphasis has been placed on discriminative setting…

2021

Why resampling outperforms reweighting for correcting sampling bias with stochastic gradients

ICLR 2021poster

A data set sampled from a certain population is biased if the subgroups of the population are sampled at proportions that are significantly different from their underlying proportions. Training machine learning models on biased data sets requires correction techniques to compensate for the bias. We…

Cited by 50SourcePDFScholar