Weishi Shi

38 papers A* 10A 2B 2Journal 16Unranked 8
YearRankTypeTitle / Venue / Authors
2026 J jnl
OLC-WA: Drift aware tuning-free online classification with weighted average.
Expert Syst. Appl.
Mohammad Abu-Shaira, Yunhe Feng, Heng Fan, Weishi Shi
2026 J jnl
OLR-WAA: Adaptive and Drift-Resilient Online Regression with Dynamic Weighted Averaging.
Data Sci. Eng.
Mohammad Abu-Shaira, Weishi Shi
2026 J jnl
Online Domain-aware LLM Decoding for Continual Domain Evolution.
CoRR
Mohammad Abu-Shaira, Weishi Shi
2026 J jnl
Towards Visual Query Segmentation in the Wild.
CoRR
Bing Fan, Minghao Li, Hanzhi Zhang, Shaohua Dong, Naga Prudhvi Mareedu, Weishi Shi, Yunhe Feng, Yan Huang, Heng Fan
2025 B conf
DAO-GP Drift Aware Online Non-Linear Regression Gaussian-Process.
IEEE Big Data
Mohammad Abu-Shaira, Ajita Rattani, Weishi Shi
2025 J jnl
DAO-GP Drift Aware Online Non-Linear Regression Gaussian-Process.
CoRR
Mohammad Abu-Shaira, Ajita Rattani, Weishi Shi
2025 B conf
Deep Active Re-Labeling: Toward Noise-Resilient Annotation Efficiency.
IEEE Big Data
Md. Abdullah Al Forhad, Weishi Shi
2025 J jnl
Diagnosing Shortcut-Induced Rigidity in Continual Learning: The Einstellung Rigidity Index (ERI).
CoRR
Kai Gu, Weishi Shi
2025 J jnl
OLC-WA: Drift Aware Tuning-Free Online Classification with Weighted Average.
CoRR
Mohammad Abu-Shaira, Yunhe Feng, Heng Fan, Weishi Shi
2025 J jnl
OLR-WAA: Adaptive and Drift-Resilient Online Regression with Dynamic Weighted Averaging.
CoRR
Mohammad Abu-Shaira, Weishi Shi
2025 J jnl
Unveiling Statistical Significance of Online Regression over Multiple Datasets.
CoRR
Mohammad Abu-Shaira, Weishi Shi
2024 J jnl
ALL: Supporting Experiential Accessibility Education and Inclusive Software Development.
ACM Trans. Softw. Eng. Methodol.
Weishi Shi, Heather Moses, Qi Yu, Samuel A. Malachowsky, Daniel E. Krutz
2024 — conf
Balancing Explanations and Adaptation in Offline Continual Learning Systems Using Active Augmented Reply.
MIPR
Md. Abdullah Al Forhad, Weishi Shi
2024 A* conf
Evidential Mixture Machines: Deciphering Multi-Label Correlations for Active Learning Sensitivity.
NeurIPS
Dayou Yu, Minghao Li, Weishi Shi, Qi Yu
2024 — conf
Macro-AUC-Driven Active Learning Strategy for Multi-Label Classification Enhancement.
MIPR
Minghao Li, Junjie Qiu, Weishi Shi
2024 — conf
Unveiling Statistical Significance of Online Regression Over Multiple Datasets.
MIPR
Mohammad Abu-Shaira, Weishi Shi
2024 A* conf
Wearable Sensor-Based Few-Shot Continual Learning on Hand Gestures for Motor-Impaired Individuals via Latent Embedding Exploitation.
IJCAI
Riyad Bin Rafiq, Weishi Shi, Mark V. Albert
2024 J jnl
Wearable Sensor-Based Few-Shot Continual Learning on Hand Gestures for Motor-Impaired Individuals via Latent Embedding Exploitation.
CoRR
Riyad Bin Rafiq, Weishi Shi, Mark V. Albert
2023 A* conf
Actively Testing Your Model While It Learns: Realizing Label-Efficient Learning in Practice.
NeurIPS
Dayou Yu, Weishi Shi, Qi Yu
2023 A* conf
Discover-Then-Rank Unlabeled Support Vectors in the Dual Space for Multi-Class Active Learning.
ICML
Dayou Yu, Weishi Shi, Qi Yu
2023 A* conf
STARS: Spatial-Temporal Active Re-sampling for Label-Efficient Learning from Noisy Annotations.
AAAI
Dayou Yu, Weishi Shi, Qi Yu
2022 — conf
Hierarchical Bayesian multi-kernel learning for integrated classification and summarization of app reviews.
ESEC/SIGSOFT FSE
Moayad Alshangiti, Weishi Shi, Eduardo Lima, Xumin Liu, Qi Yu
2021 A* conf
A Gaussian Process-Bayesian Bernoulli Mixture Model for Multi-Label Active Learning.
NeurIPS
Weishi Shi, Dayou Yu, Qi Yu
2021 A conf
Active Learning with Maximum Margin Sparse Gaussian Processes.
AISTATS
Weishi Shi, Qi Yu
2021 — conf
Uncertainty-Aware Multiple Instance Learning from Large-Scale Long Time Series Data.
IEEE BigData
Yuansheng Zhu, Weishi Shi, Deep Shankar Pandey, Yang Liu, Xiaofan Que, Daniel E. Krutz, Qi Yu
2021 J jnl
Uncertainty-Aware Multiple Instance Learning from Large-Scale Long Time Series Data.
CoRR
Yuansheng Zhu, Weishi Shi, Deep Shankar Pandey, Yang Liu, Xiaofan Que, Daniel E. Krutz, Qi Yu
2020 J jnl
A Bayesian learning model for design-phase service mashup popularity prediction.
Expert Syst. Appl.
Moayad Alshangiti, Weishi Shi, Xumin Liu, Qi Yu
2020 — conf
Experiential learning in computing accessibility education.
ICSE (Companion Volume)
Weishi Shi, Saad Khan, Yasmine N. El-Glaly, Samuel A. Malachowsky, Qi Yu, Daniel E. Krutz
2020 A* conf
Multifaceted Uncertainty Estimation for Label-Efficient Deep Learning.
NeurIPS
Weishi Shi, Xujiang Zhao, Feng Chen, Qi Yu
2020 J jnl
Presenting and Evaluating the Impact of Experiential Learning in Computing Accessibility Education.
CoRR
Weishi Shi, Samuel A. Malachowsky, Yasmine N. El-Glaly, Qi Yu, Daniel E. Krutz
2020 — conf
Presenting and evaluating the impact of experiential learning in computing accessibility education.
ICSE (SEET)
Yasmine N. El-Glaly, Weishi Shi, Samuel A. Malachowsky, Qi Yu, Daniel E. Krutz
2019 A* conf
Fast Direct Search in an Optimally Compressed Continuous Target Space for Efficient Multi-Label Active Learning.
ICML
Weishi Shi, Qi Yu
2019 A* conf
Integrating Bayesian and Discriminative Sparse Kernel Machines for Multi-class Active Learning.
NeurIPS
Weishi Shi, Qi Yu
2019 J jnl
Integrating Multi-level Tag Recommendation with External Knowledge Bases for Automatic Question Answering.
ACM Trans. Internet Techn.
Eduardo Lima, Weishi Shi, Xumin Liu, Qi Yu
2018 A* conf
An Efficient Many-Class Active Learning Framework for Knowledge-Rich Domains.
ICDM
Weishi Shi, Qi Yu
2018 — conf
From Novice to Expert Narratives of Dermatological Disease.
PerCom Workshops
Nse Obot, Laura OrMalley, Ifeoma Nwogu, Qi Yu, Weishi Shi, Xuan Guo
2017 A conf
Correlation-Aware Multi-Label Active Learning for Web Service Tag Recommendation.
ICWS
Weishi Shi, Xumin Liu, Qi Yu
2017 J jnl
Statistical Learning of Domain-Specific Quality-of-Service Features from User Reviews.
ACM Trans. Internet Techn.
Xumin Liu, Weishi Shi, Arpeet Kale, Chen Ding, Qi Yu