Ivor W. Tsang

38 papers · 2005–2026 · 12 conferences · across top CS/AI conferences

Achievements

+14 more ↓

🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🗺️ Taxonomy Completionist (17) 🌍 Conference Polyglot (12)

🏃 Academic Marathon (21) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌟 Keyword Trendsetter Combo (5) 🏆 Grand Slam 🏆 Keyword Champion 🌱 Topic Pioneer 🔬 Deep Specialist (12) 💎 Century Club (38) 🗃️ Keyword Collector (193) 📈 Trend Setter 🚀 Conference Pioneer ⚡ Prolific Year (6) 🔥 Unstoppable (5)

Conferences

JMLR (12) NIPS (7) IJCAI (4) AAAI (3) CVPR (3) ACML (2) ICLR (2) ACL (1) AISTATS (1) ICCV (1) ICML (1) WACV (1)

Top co-authors

James T. Kwok (5) Joey Tianyi Zhou (4) Sinno Jialin Pan (4) Xiaofeng Cao (4) Ya Zhang (3) Mingkui Tan (3) Weiwei Liu (3) Yueming LYU (3) Yuangang Pan (3) Yew-Soon Ong (2)

Keywords

bayesian inference (3) representation learning (3) kernel methods (3) multiple kernel learning (3) multi-label classification (3) semi-supervised learning (2) support vector machine (2) distribution matching (2) transfer learning (2) generative adversarial network (2) multi-task learning (2) generalization error bound (2) core vector machine (2) metric learning (1) dimensionality reduction (1) semantic segmentation (1) zero-shot learning (1) active learning (1) multi-view clustering (1) compressed sensing (1)

Papers

Power of Boundary and Reflection: Semantic Transparent Object Segmentation using Pyramid Vision Transformer with Transparent Cues WACV 2026 Balanced Image Stylization with Style Matching Score ICCV 2025 Generative Adversarial Ranking Nets JMLR 2024 AHIVE: Anatomy-aware Hierarchical Vision Encoding for Interactive Radiology Report Retrieval CVPR 2024 Learning Discretized Neural Networks under Ricci Flow JMLR 2024 Towards Harmless Rawlsian Fairness Regardless of Demographic Prior NIPS 2024 Sharpness-Aware Minimization Activates the Interactive Teaching's Understanding and Optimization NIPS 2024 Mentored Learning: Improving Generalization and Convergence of Student Learner JMLR 2024 Multi-Task Learning via Time-Aware Neural ODE IJCAI 2023 Nonparametric Teaching for Multiple Learners NIPS 2023 Multi-view Subspace Clustering on Topological Manifold NIPS 2022 Fast and Robust Rank Aggregation against Model Misspecification JMLR 2022 XAI Beyond Classification: Interpretable Neural Clustering JMLR 2022 Curriculum Loss: Robust Learning and Generalization against Label Corruption ICLR 2020 Subgroup-based Rank-1 Lattice Quasi-Monte Carlo NIPS 2020 Graph Cross Networks with Vertex Infomax Pooling NIPS 2020 Copy and Paste GAN: Face Hallucination From Shaded Thumbnails CVPR 2020 Learning Image-Specific Attributes by Hyperbolic Neighborhood Graph Propagation IJCAI 2019 Label Embedding with Partial Heterogeneous Contexts AAAI 2019 Multi-class Heterogeneous Domain Adaptation JMLR 2019 MARGINALIZED AVERAGE ATTENTIONAL NETWORK FOR WEAKLY-SUPERVISED LEARNING ICLR 2019 Safeguarded Dynamic Label Regression for Noisy Supervision AAAI 2019 Understanding VAEs in Fisher-Shannon Plane AAAI 2019 Deep Discrete Prototype Multilabel Learning IJCAI 2018 An Easy-to-hard Learning Paradigm for Multiple Classes and Multiple Labels JMLR 2017 Making Decision Trees Feasible in Ultrahigh Feature and Label Dimensions JMLR 2017 Transfer Hashing with Privileged Information IJCAI 2016 Event Detection using Multi-Level Relevance Labels and Multiple Features CVPR 2014 Riemannian Pursuit for Big Matrix Recovery ICML 2014 Towards Ultrahigh Dimensional Feature Selection for Big Data JMLR 2014 Robust Domain Adaptation for Relation Extraction via Clustering Consistency ACL 2014 Convex and Scalable Weakly Labeled SVMs JMLR 2013 Multi-view Positive and Unlabeled Learning ACML 2012 Two-Layer Multiple Kernel Learning AISTATS 2011 Learning to Locate Relative Outliers ACML 2011 A Family of Simple Non-Parametric Kernel Learning Algorithms JMLR 2011 Large-Scale Sparsified Manifold Regularization NIPS 2006 Core Vector Machines: Fast SVM Training on Very Large Data Sets JMLR 2005