Cost-Sensitive Two-Stage Depression Prediction Using Dynamic Visual Clues. - Xingchen Ma; Di Huang 001; Yunhong Wang 001; Yiding Wang (ACCV (2), 2016)

DepAudioNet: An Efficient Deep Model for Audio based Depression Classification. - Xingchen Ma; Hongyu Yang; Qiang Chen; Di Huang 001; Yunhong Wang 001 (AVEC@ACM Multimedia, 2016)

A Bayesian Optimization Framework for Neural Network Compression. - Xingchen Ma; Amal Rannen Triki; Maxim Berman; Christos Sagonas; Jacques Calì; Matthew B. Blaschko (ICCV, 2019)

Additive Tree-Structured Covariance Function for Conditional Parameter Spaces in Bayesian Optimization. - Xingchen Ma; Matthew B. Blaschko (AISTATS, 2020)

Meta-Cal: Well-controlled Post-hoc Calibration by Ranking. - Xingchen Ma; Matthew B. Blaschko (ICML, 2021)

Additive Tree-Structured Conditional Parameter Spaces in Bayesian Optimization: A Novel Covariance Function and a Fast Implementation. - Xingchen Ma; Matthew B. Blaschko (IEEE Trans. Pattern Anal. Mach. Intell., 2021)

A Corrected Expected Improvement Acquisition Function Under Noisy Observations. - Han Zhou 013; Xingchen Ma; Matthew B. Blaschko (ACML, 2023)

Confidence-Aware Personalized Federated Learning via Variational Expectation Maximization. - Junyi Zhu 002; Xingchen Ma; Matthew B. Blaschko (CVPR, 2023)

Structural Pruning of Pre-trained Language Models via Neural Architecture Search. - Aaron Klein; Jacek Golebiowski; Xingchen Ma; Valerio Perrone; Cédric Archambeau (Trans. Mach. Learn. Res., 2024)