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Hsuan-tien Lin

33 papers · 2006–2025 · 14 conferences · across top CS/AI conferences

Achievements

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+12 more ↓ 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer πŸ—ΊοΈ Taxonomy Completionist (18) 🌍 Conference Polyglot (14)
🌈 Renaissance Researcher (10) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸ‘₯ Mega-Team (24) πŸ”¬ Deep Specialist (14) πŸ† Keyword Champion πŸ—ƒοΈ Keyword Collector (127) πŸš€ Conference Pioneer πŸ“ˆ Trend Setter πŸ’Ž Century Club (33) πŸ”₯ Unstoppable (8) ⚑ Prolific Year (5)

Conferences

ACML (9) NIPS (5) ICML (4) JMLR (3) AISTATS (2) NAACL (2) CVPR (1) EACL (1) ECCV (1) EMNLP (1) ICCV (1) ICLR (1) IJCAI (1) INTERSPEECH (1)

Papers

Tackling Dimensional Collapse toward Comprehensive Universal Domain Adaptation ICML 2025 Soft Separation and Distillation: Toward Global Uniformity in Federated Unsupervised Learning ICCV 2025 Preserving Zero-shot Capability in Supervised Fine-tuning for Multi-label Text Classification NAACL 2025 Understanding and Mitigating Spurious Correlations in Text Classification with Neighborhood Analysis EACL 2024 Asian Conference on Machine Learning: Preface ACML 2024 CAD-DA: Controllable Anomaly Detection after Domain Adaptation by Statistical Inference AISTATS 2024 TableRAG: Million-Token Table Understanding with Language Models NIPS 2024 SLIM: Spuriousness Mitigation with Minimal Human Annotations ECCV 2024 Semi-Supervised Domain Adaptation With Source Label Adaptation CVPR 2023 Even the Simplest Baseline Needs Careful Re-investigation: A Case Study on XML-CNN NAACL 2022 Adaptive and Generative Zero-Shot Learning ICLR 2021 A Unified View of cGANs with and without Classifiers NIPS 2021 Learning from Label Proportions with Consistency Regularization ACML 2020 SERIL: Noise Adaptive Speech Enhancement Using Regularization-Based Incremental Learning INTERSPEECH 2020 Cold-start Active Learning through Self-supervised Language Modeling EMNLP 2020 Unbiased Risk Estimators Can Mislead: A Case Study of Learning with Complementary Labels ICML 2020 Deep Learning with a Rethinking Structure for Multi-label Classification ACML 2019 REFUEL: Exploring Sparse Features in Deep Reinforcement Learning for Fast Disease Diagnosis NIPS 2018 Cost-Aware Pre-Training for Multiclass Cost-Sensitive Deep Learning IJCAI 2016 Rivalry of Two Families of Algorithms for Memory-Restricted Streaming PCA AISTATS 2016 Combination of Feature Engineering and Ranking Models for Paper-Author Identification in KDD Cup 2013 JMLR 2015 Pseudo-reward Algorithms for Contextual Bandits with Linear Payoff Functions ACML 2014 Reduction from Cost-Sensitive Multiclass Classification to One-versus-One Binary Classification ACML 2014 Boosting with Online Binary Learners for the Multiclass Bandit Problem ICML 2014 Condensed Filter Tree for Cost-Sensitive Multi-Label Classification ICML 2014 Effective String Processing and Matching for Author Disambiguation JMLR 2014 Active Sampling of Pairs and Points for Large-scale Linear Bipartite Ranking ACML 2013 Feature-aware Label Space Dimension Reduction for Multi-label Classification NIPS 2012 Active Learning with Hinted Support Vector Machine ACML 2012 Multi-label Active Learning with Auxiliary Learner ACML 2011 Multi-label Classification with Error-correcting Codes ACML 2011 Support Vector Machinery for Infinite Ensemble Learning JMLR 2008 Ordinal Regression by Extended Binary Classification NIPS 2006