Hsuan-Tien Lin

According to our database1, Hsuan-Tien Lin authored at least 98 papers between 2002 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
Learning key steps to attack deep reinforcement learning agents.
Mach. Learn., May, 2023

CAD-DA: Controllable Anomaly Detection after Domain Adaptation by Statistical Inference.
CoRR, 2023

From SMOTE to Mixup for Deep Imbalanced Classification.
CoRR, 2023

Score-based Conditional Generation with Fewer Labeled Data by Self-calibrating Classifier Guidance.
CoRR, 2023

Re-Benchmarking Pool-Based Active Learning for Binary Classification.
CoRR, 2023

Understanding and Mitigating Spurious Correlations in Text Classification.
CoRR, 2023

Enhancing Label Sharing Efficiency in Complementary-Label Learning with Label Augmentation.
CoRR, 2023

CLCIFAR: CIFAR-Derived Benchmark Datasets with Human Annotated Complementary Labels.
CoRR, 2023

SUNY: A Visual Interpretation Framework for Convolutional Neural Networks from a Necessary and Sufficient Perspective.
CoRR, 2023

Reduction from Complementary-Label Learning to Probability Estimates.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2023

Semi-Supervised Domain Adaptation with Source Label Adaptation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
Reducing Training Sample Memorization in GANs by Training with Memorization Rejection.
CoRR, 2022

Improving Clustering Uncertainty-weighted Embeddings for Active Domain Adaptation.
Proceedings of the International Conference on Technologies and Applications of Artificial Intelligence, 2022

Even the Simplest Baseline Needs Careful Re-investigation: A Case Study on XML-CNN.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

2021
Improving Model Compatibility of Generative Adversarial Networks by Boundary Calibration.
CoRR, 2021

Active Refinement for Multi-Label Learning: A Pseudo-Label Approach.
CoRR, 2021

Accurate and Clear Precipitation Nowcasting with Consecutive Attention and Rain-map Discrimination.
CoRR, 2021

A Unified View of cGANs with and without Classifiers.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

On Training Sample Memorization: Lessons from Benchmarking Generative Modeling with a Large-scale Competition.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Adaptive and Generative Zero-Shot Learning.
Proceedings of the 9th International Conference on Learning Representations, 2021

360-Degree Gaze Estimation in the Wild Using Multiple Zoom Scales.
Proceedings of the 32nd British Machine Vision Conference 2021, 2021

2020
Active deep Q-learning with demonstration.
Mach. Learn., 2020

360-Degree Gaze Estimation in the Wild Using Multiple Zoom Scales.
CoRR, 2020

Cost Learning Network for Imbalanced Classification.
Proceedings of the International Conference on Technologies and Applications of Artificial Intelligence, 2020

Cost-Sensitive Deep Learning with Layer-Wise Cost Estimation.
Proceedings of the International Conference on Technologies and Applications of Artificial Intelligence, 2020

Improving Unsupervised Domain Adaptation with Representative Selection Techniques.
Proceedings of the Workshop on Interactive Adaptive Learning co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2020), 2020

Benchmarking Tropical Cyclone Rapid Intensification with Satellite Images and Attention-Based Deep Models.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Applied Data Science Track, 2020

SERIL: Noise Adaptive Speech Enhancement Using Regularization-Based Incremental Learning.
Proceedings of the Interspeech 2020, 2020

Unbiased Risk Estimators Can Mislead: A Case Study of Learning with Complementary Labels.
Proceedings of the 37th International Conference on Machine Learning, 2020

Cold-start Active Learning through Self-supervised Language Modeling.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Learning from Label Proportions with Consistency Regularization.
Proceedings of The 12th Asian Conference on Machine Learning, 2020

2019
Annotation cost-sensitive active learning by tree sampling.
Mach. Learn., 2019

Dynamic principal projection for cost-sensitive online multi-label classification.
Mach. Learn., 2019

Attention-based Deep Tropical Cyclone Rapid Intensification Prediction.
Proceedings of MACLEAN: MAChine Learning for EArth ObservatioN Workshop co-located with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD 2019), 2019

Advances in Cost-sensitive Multiclass and Multilabel Classification.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Deep Learning with a Rethinking Structure for Multi-label Classification.
Proceedings of The 11th Asian Conference on Machine Learning, 2019

2018
Automatic Bridge Bidding Using Deep Reinforcement Learning.
IEEE Trans. Games, 2018

Multi-Label Classification with Feature-Aware Cost-Sensitive Label Embedding.
Proceedings of the Conference on Technologies and Applications of Artificial Intelligence, 2018

Cost-Sensitive Reference Pair Encoding for Multi-Label Learning.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2018

REFUEL: Exploring Sparse Features in Deep Reinforcement Learning for Fast Disease Diagnosis.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Rotation-blended CNNs on a New Open Dataset for Tropical Cyclone Image-to-intensity Regression.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Compatibility Family Learning for Item Recommendation and Generation.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

A Deep Model With Local Surrogate Loss for General Cost-Sensitive Multi-Label Learning.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Progressive random k-labelsets for cost-sensitive multi-label classification.
Mach. Learn., 2017

Cost-sensitive label embedding for multi-label classification.
Mach. Learn., 2017

Soft Methodology for Cost-and-error Sensitive Classification.
CoRR, 2017

libact: Pool-based Active Learning in Python.
CoRR, 2017

Cost-Sensitive Encoding for Label Space Dimension Reduction Algorithms on Multi-label Classification.
Proceedings of the Conference on Technologies and Applications of Artificial Intelligence, 2017

Cyclic Classifier Chain for Cost-Sensitive Multilabel Classification.
Proceedings of the 2017 IEEE International Conference on Data Science and Advanced Analytics, 2017

2016
Cost-Sensitive Random Pair Encoding for Multi-Label Classification.
CoRR, 2016

Cost-Sensitive Deep Learning with Layer-Wise Cost Estimation.
CoRR, 2016

A Simple Unlearning Framework for Online Learning Under Concept Drifts.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2016

Linear Upper Confidence Bound Algorithm for Contextual Bandit Problem with Piled Rewards.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2016

Cost-Aware Pre-Training for Multiclass Cost-Sensitive Deep Learning.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

A Novel Uncertainty Sampling Algorithm for Cost-Sensitive Multiclass Active Learning.
Proceedings of the IEEE 16th International Conference on Data Mining, 2016

Can Active Learning Experience Be Transferred?
Proceedings of the IEEE 16th International Conference on Data Mining, 2016

Automatic Bridge Bidding Using Deep Reinforcement Learning.
Proceedings of the ECAI 2016 - 22nd European Conference on Artificial Intelligence, 29 August-2 September 2016, The Hague, The Netherlands, 2016

Rivalry of Two Families of Algorithms for Memory-Restricted Streaming PCA.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015
Active Learning Using Hint Information.
Neural Comput., 2015

Combination of feature engineering and ranking models for paper-author identification in KDD cup 2013.
J. Mach. Learn. Res., 2015

A practical divide-and-conquer approach for preference-based learning to rank.
Proceedings of the Conference on Technologies and Applications of Artificial Intelligence, 2015

Active Learning by Learning.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

Contract Bridge Bidding by Learning.
Proceedings of the Computer Poker and Imperfect Information, 2015

2014
Effective string processing and matching for author disambiguation.
J. Mach. Learn. Res., 2014

Improving ranking performance with cost-sensitive ordinal classification via regression.
Inf. Retr., 2014

Machine Learning Approaches for Interactive Verification.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2014

Condensed Filter Tree for Cost-Sensitive Multi-Label Classification.
Proceedings of the 31th International Conference on Machine Learning, 2014

Boosting with Online Binary Learners for the Multiclass Bandit Problem.
Proceedings of the 31th International Conference on Machine Learning, 2014

Reduction from Cost-Sensitive Multiclass Classification to One-versus-One Binary Classification.
Proceedings of the Sixth Asian Conference on Machine Learning, 2014

Pseudo-reward Algorithms for Contextual Bandits with Linear Payoff Functions.
Proceedings of the Sixth Asian Conference on Machine Learning, 2014

2013
Multilabel Classification Using Error-Correcting Codes of Hard or Soft Bits.
IEEE Trans. Neural Networks Learn. Syst., 2013

Data Selection Techniques for Large-Scale Rank SVM.
Proceedings of the Conference on Technologies and Applications of Artificial Intelligence, 2013

Active Learning for Multiclass Cost-Sensitive Classification Using Probabilistic Models.
Proceedings of the Conference on Technologies and Applications of Artificial Intelligence, 2013

Pairwise Regression with Upper Confidence Bound for Contextual Bandit with Multiple Actions.
Proceedings of the Conference on Technologies and Applications of Artificial Intelligence, 2013

Active Sampling of Pairs and Points for Large-scale Linear Bipartite Ranking.
Proceedings of the Asian Conference on Machine Learning, 2013

2012
Unsupervised Semantic Feature Discovery for Image Object Retrieval and Tag Refinement.
IEEE Trans. Multim., 2012

Multilabel Classification with Principal Label Space Transformation.
Neural Comput., 2012

Reduction from Cost-Sensitive Ordinal Ranking to Weighted Binary Classification.
Neural Comput., 2012

Novel Models and Ensemble Techniques to Discriminate Favorite Items from Unrated Ones for Personalized Music Recommendation.
Proceedings of KDD Cup 2011 competition, San Diego, CA, USA, 2011, 2012

Active Learning with Hinted Support Vector Machine.
Proceedings of the 4th Asian Conference on Machine Learning, 2012


Feature-aware Label Space Dimension Reduction for Multi-label Classification.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

A simple methodology for soft cost-sensitive classification.
Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

An Online Boosting Algorithm with Theoretical Justifications.
Proceedings of the 29th International Conference on Machine Learning, 2012

2011
Multi-label Active Learning with Auxiliary Learner.
Proceedings of the 3rd Asian Conference on Machine Learning, 2011

Multi-label Classification with Error-correcting Codes.
Proceedings of the 3rd Asian Conference on Machine Learning, 2011

Unsupervised auxiliary visual words discovery for large-scale image object retrieval.
Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition, 2011

Cost-Sensitive Classification on Pathogen Species of Bacterial Meningitis by Surface Enhanced Raman Scattering.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2011

2010
One-sided Support Vector Regression for Multiclass Cost-sensitive Classification.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

2009
An Ensemble of Three Classifiers for KDD Cup 2009: Expanded Linear Model, Heterogeneous Boosting, and Selective Naive Bayes.
Proceedings of KDD-Cup 2009 competition, Paris, France, June 28, 2009, 2009

2008
Support Vector Machinery for Infinite Ensemble Learning.
J. Mach. Learn. Res., 2008

2007
A note on Platt's probabilistic outputs for support vector machines.
Mach. Learn., 2007

Optimizing 0/1 Loss for Perceptrons by Random Coordinate Descent.
Proceedings of the International Joint Conference on Neural Networks, 2007

2006
Ordinal Regression by Extended Binary Classification.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Large-Margin Thresholded Ensembles for Ordinal Regression: Theory and Practice.
Proceedings of the Algorithmic Learning Theory, 17th International Conference, 2006

2005
Improving Generalization by Data Categorization.
Proceedings of the Knowledge Discovery in Databases: PKDD 2005, 2005

Infinite Ensemble Learning with Support Vector Machines.
Proceedings of the Machine Learning: ECML 2005, 2005

2002
A Note on the Decomposition Methods for Support Vector Regression.
Neural Comput., 2002


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