Correlation-Aware Multi-Label Active Learning for Web Service Tag Recommendation. - Weishi Shi; Xumin Liu; Qi Yu 001 (ICWS, 2017)

Statistical Learning of Domain-Specific Quality-of-Service Features from User Reviews. - Xumin Liu; Weishi Shi; Arpeet Kale; Chen Ding 004; Qi Yu 001 (ACM Trans. Internet Techn., 2017)

An Efficient Many-Class Active Learning Framework for Knowledge-Rich Domains. - Weishi Shi; Qi Yu 001 (ICDM, 2018)

From Novice to Expert Narratives of Dermatological Disease. - Nse Obot; Laura OrMalley; Ifeoma Nwogu; Qi Yu 001; Weishi Shi; Xuan Guo (PerCom Workshops, 2018)

Fast Direct Search in an Optimally Compressed Continuous Target Space for Efficient Multi-Label Active Learning. - Weishi Shi; Qi Yu 001 (ICML, 2019)

Integrating Bayesian and Discriminative Sparse Kernel Machines for Multi-class Active Learning. - Weishi Shi; Qi Yu 001 (NeurIPS, 2019)

Integrating Multi-level Tag Recommendation with External Knowledge Bases for Automatic Question Answering. - Eduardo Lima; Weishi Shi; Xumin Liu; Qi Yu 001 (ACM Trans. Internet Techn., 2019)

Presenting and evaluating the impact of experiential learning in computing accessibility education. - Yasmine N. El-Glaly; Weishi Shi; Samuel A. Malachowsky; Qi Yu 001; Daniel E. Krutz (ICSE (SEET), 2020)

Experiential learning in computing accessibility education. - Weishi Shi; Saad Khan 006; Yasmine N. El-Glaly; Samuel A. Malachowsky; Qi Yu 001; Daniel E. Krutz (ICSE (Companion Volume), 2020)

Multifaceted Uncertainty Estimation for Label-Efficient Deep Learning. - Weishi Shi; Xujiang Zhao; Feng Chen 001; Qi Yu 001 (NeurIPS, 2020)

A Bayesian learning model for design-phase service mashup popularity prediction. - Moayad Alshangiti; Weishi Shi; Xumin Liu; Qi Yu 001 (Expert Syst. Appl., 2020)

Active Learning with Maximum Margin Sparse Gaussian Processes. - Weishi Shi; Qi Yu 001 (AISTATS, 2021)

Uncertainty-Aware Multiple Instance Learning from Large-Scale Long Time Series Data. - Yuansheng Zhu; Weishi Shi; Deep Shankar Pandey; Yang Liu; Xiaofan Que; Daniel E. Krutz; Qi Yu 001 (IEEE BigData, 2021)

A Gaussian Process-Bayesian Bernoulli Mixture Model for Multi-Label Active Learning. - Weishi Shi; Dayou Yu; Qi Yu 001 (NeurIPS, 2021)

Hierarchical Bayesian multi-kernel learning for integrated classification and summarization of app reviews. - Moayad Alshangiti; Weishi Shi; Eduardo Lima; Xumin Liu; Qi Yu 001 (ESEC/SIGSOFT FSE, 2022)

STARS: Spatial-Temporal Active Re-sampling for Label-Efficient Learning from Noisy Annotations. - Dayou Yu; Weishi Shi; Qi Yu 001 (AAAI, 2023)

Discover-Then-Rank Unlabeled Support Vectors in the Dual Space for Multi-Class Active Learning. - Dayou Yu; Weishi Shi; Qi Yu 001 (ICML, 2023)

Actively Testing Your Model While It Learns: Realizing Label-Efficient Learning in Practice. - Dayou Yu; Weishi Shi; Qi Yu 001 (NeurIPS, 2023)

Wearable Sensor-Based Few-Shot Continual Learning on Hand Gestures for Motor-Impaired Individuals via Latent Embedding Exploitation. - Riyad Bin Rafiq; Weishi Shi; Mark V. Albert (IJCAI, 2024)

Unveiling Statistical Significance of Online Regression Over Multiple Datasets. - Mohammad Abu-Shaira; Weishi Shi (MIPR, 2024)

Balancing Explanations and Adaptation in Offline Continual Learning Systems Using Active Augmented Reply. - Md. Abdullah Al Forhad; Weishi Shi (MIPR, 2024)

Macro-AUC-Driven Active Learning Strategy for Multi-Label Classification Enhancement. - Minghao Li; Junjie Qiu; Weishi Shi (MIPR, 2024)

Evidential Mixture Machines: Deciphering Multi-Label Correlations for Active Learning Sensitivity. - Dayou Yu; Minghao Li; Weishi Shi; Qi Yu 001 (NeurIPS, 2024)

ALL: Supporting Experiential Accessibility Education and Inclusive Software Development. - Weishi Shi; Heather Moses; Qi Yu 001; Samuel A. Malachowsky; Daniel E. Krutz (ACM Trans. Softw. Eng. Methodol., 2024)