Han-Jia Ye

Orcid: 0000-0003-1173-1880

According to our database1, Han-Jia Ye authored at least 97 papers between 2015 and 2025.

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

Timeline

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Bibliography

2025
Revisiting multi-dimensional classification from a dimension-wise perspective.
Frontiers Comput. Sci., January, 2025

2024
Class-Incremental Learning: A Survey.
IEEE Trans. Pattern Anal. Mach. Intell., December, 2024

The Capacity and Robustness Trade-Off: Revisiting the Channel Independent Strategy for Multivariate Time Series Forecasting.
IEEE Trans. Knowl. Data Eng., November, 2024

TV100: a TV series dataset that pre-trained CLIP has not seen.
Frontiers Comput. Sci., October, 2024

Few-Shot Learning With a Strong Teacher.
IEEE Trans. Pattern Anal. Mach. Intell., March, 2024

Contextualizing Meta-Learning via Learning to Decompose.
IEEE Trans. Pattern Anal. Mach. Intell., January, 2024

Dual Consolidation for Pre-Trained Model-Based Domain-Incremental Learning.
CoRR, 2024

Adaptive Adapter Routing for Long-Tailed Class-Incremental Learning.
CoRR, 2024

TALENT: A Tabular Analytics and Learning Toolbox.
CoRR, 2024

Modern Neighborhood Components Analysis: A Deep Tabular Baseline Two Decades Later.
CoRR, 2024

A Closer Look at Deep Learning on Tabular Data.
CoRR, 2024

Improving LLMs for Recommendation with Out-Of-Vocabulary Tokens.
CoRR, 2024

Wings: Learning Multimodal LLMs without Text-only Forgetting.
CoRR, 2024

Parrot: Multilingual Visual Instruction Tuning.
CoRR, 2024

Ovis: Structural Embedding Alignment for Multimodal Large Language Model.
CoRR, 2024

SOFTS: Efficient Multivariate Time Series Forecasting with Series-Core Fusion.
CoRR, 2024

Bridge the Modality and Capacity Gaps in Vision-Language Model Selection.
CoRR, 2024

Graph Contrastive Learning with Cohesive Subgraph Awareness.
Proceedings of the ACM on Web Conference 2024, 2024

Continual Learning with Pre-Trained Models: A Survey.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Multi-layer Rehearsal Feature Augmentation for Class-Incremental Learning.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Enhancing Class-Imbalanced Learning with Pre-Trained Guidance through Class-Conditional Knowledge Distillation.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Tabular Insights, Visual Impacts: Transferring Expertise from Tables to Images.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

SIN: Selective and Interpretable Normalization for Long-Term Time Series Forecasting.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Leveraging Cross-Modal Neighbor Representation for Improved CLIP Classification.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Expandable Subspace Ensemble for Pre-Trained Model-Based Class-Incremental Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Twice Class Bias Correction for Imbalanced Semi-supervised Learning.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Learning Only When It Matters: Cost-Aware Long-Tailed Classification.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Few-Shot Class-Incremental Learning by Sampling Multi-Phase Tasks.
IEEE Trans. Pattern Anal. Mach. Intell., November, 2023

PyCIL: a Python toolbox for class-incremental learning.
Sci. China Inf. Sci., September, 2023

Revisiting Unsupervised Meta-Learning via the Characteristics of Few-Shot Tasks.
IEEE Trans. Pattern Anal. Mach. Intell., March, 2023

Generalized Knowledge Distillation via Relationship Matching.
IEEE Trans. Pattern Anal. Mach. Intell., 2023

Learning Robust Precipitation Forecaster by Temporal Frame Interpolation.
CoRR, 2023

Training-Free Generalization on Heterogeneous Tabular Data via Meta-Representation.
CoRR, 2023

Unlocking the Transferability of Tokens in Deep Models for Tabular Data.
CoRR, 2023

PILOT: A Pre-Trained Model-Based Continual Learning Toolbox.
CoRR, 2023

ZhiJian: A Unifying and Rapidly Deployable Toolbox for Pre-trained Model Reuse.
CoRR, 2023

Streaming CTR Prediction: Rethinking Recommendation Task for Real-World Streaming Data.
CoRR, 2023

Learning without Forgetting for Vision-Language Models.
CoRR, 2023

Gen-L-Video: Multi-Text to Long Video Generation via Temporal Co-Denoising.
CoRR, 2023

Revisiting Class-Incremental Learning with Pre-Trained Models: Generalizability and Adaptivity are All You Need.
CoRR, 2023

Deep Class-Incremental Learning: A Survey.
CoRR, 2023

On Transferring Expert Knowledge from Tabular Data to Images.
Proceedings of UniReps: the First Workshop on Unifying Representations in Neural Models, 2023

Model Spider: Learning to Rank Pre-Trained Models Efficiently.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Few-Shot Class-Incremental Learning via Training-Free Prototype Calibration.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Multi-task Method for Immunofixation Electrophoresis Image Classification.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Preserving Locality in Vision Transformers for Class Incremental Learning.
Proceedings of the IEEE International Conference on Multimedia and Expo, 2023

Improved Dynamic Spatial-Temporal Attention Network for Early Anticipation of Traffic Accidents.
Proceedings of the IEEE International Conference on Multimedia and Expo Workshops, 2023

BEEF: Bi-Compatible Class-Incremental Learning via Energy-Based Expansion and Fusion.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Augmentation Component Analysis: Modeling Similarity via the Augmentation Overlaps.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

A Model or 603 Exemplars: Towards Memory-Efficient Class-Incremental Learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Learning Debiased Representations via Conditional Attribute Interpolation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Change Point Detection via Synthetic Signals.
Proceedings of the Advanced Analytics and Learning on Temporal Data, 2023

2022
On Pseudo-Labeling for Class-Mismatch Semi-Supervised Learning.
Trans. Mach. Learn. Res., 2022

Contrastive Principal Component Learning: Modeling Similarity by Augmentation Overlap.
CoRR, 2022

Faculty Distillation with Optimal Transport.
CoRR, 2022

Few-Shot Class-Incremental Learning by Sampling Multi-Phase Tasks.
CoRR, 2022

Audio-Visual Generalized Few-Shot Learning with Prototype-Based Co-Adaptation.
Proceedings of the 23rd Annual Conference of the International Speech Communication Association, 2022

How to Train Your MAML to Excel in Few-Shot Classification.
Proceedings of the Tenth International Conference on Learning Representations, 2022

FOSTER: Feature Boosting and Compression for Class-Incremental Learning.
Proceedings of the Computer Vision - ECCV 2022, 2022

Identifying Ambiguous Similarity Conditions via Semantic Matching.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Forward Compatible Few-Shot Class-Incremental Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Multi-Instance Learning With Emerging Novel Class.
IEEE Trans. Knowl. Data Eng., 2021

Heterogeneous Few-Shot Model Rectification With Semantic Mapping.
IEEE Trans. Pattern Anal. Mach. Intell., 2021

Learning Adaptive Classifiers Synthesis for Generalized Few-Shot Learning.
Int. J. Comput. Vis., 2021

Contextualizing Multiple Tasks via Learning to Decompose.
CoRR, 2021

Few-Shot Action Recognition with Compromised Metric via Optimal Transport.
CoRR, 2021

Support-Target Protocol for Meta-Learning.
CoRR, 2021

A$^2$-Net: Learning Attribute-Aware Hash Codes for Large-Scale Fine-Grained Image Retrieval.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Towards Enabling Meta-Learning from Target Models.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Co-Transport for Class-Incremental Learning.
Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 2021

MULL'21: First International Workshop on Multimedia Understanding with Less Labeling.
Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 2021

Procrustean Training for Imbalanced Deep Learning.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Learning Placeholders for Open-Set Recognition.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Task Cooperation for Semi-Supervised Few-Shot Learning.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Tailoring Embedding Function to Heterogeneous Few-Shot Tasks by Global and Local Feature Adaptors.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

DecAug: Out-of-Distribution Generalization via Decomposed Feature Representation and Semantic Augmentation.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Learning Multiple Local Metrics: Global Consideration Helps.
IEEE Trans. Pattern Anal. Mach. Intell., 2020

Few-shot learning with adaptively initialized task optimizer: a practical meta-learning approach.
Mach. Learn., 2020

Revisiting Unsupervised Meta-Learning: Amplifying or Compensating for the Characteristics of Few-Shot Tasks.
CoRR, 2020

Novelty-Prepared Few-Shot Classification.
CoRR, 2020

Revisiting Meta-Learning as Supervised Learning.
CoRR, 2020

Identifying and Compensating for Feature Deviation in Imbalanced Deep Learning.
CoRR, 2020

Distilling Cross-Task Knowledge via Relationship Matching.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Few-Shot Learning via Embedding Adaptation With Set-to-Set Functions.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019
What Makes Objects Similar: A Unified Multi-Metric Learning Approach.
IEEE Trans. Pattern Anal. Mach. Intell., 2019

Fast generalization rates for distance metric learning.
Mach. Learn., 2019

Learning Classifier Synthesis for Generalized Few-Shot Learning.
CoRR, 2019

2018
Learning Embedding Adaptation for Few-Shot Learning.
CoRR, 2018

Distance Metric Facilitated Transportation between Heterogeneous Domains.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Rectify Heterogeneous Models with Semantic Mapping.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
Learning Mahalanobis Distance Metric: Considering Instance Disturbance Helps.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

2016
What Makes Objects Similar: A Unified Multi-Metric Learning Approach.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

College Student Scholarships and Subsidies Granting: A Multi-modal Multi-label Approach.
Proceedings of the IEEE 16th International Conference on Data Mining, 2016

Learning Feature Aware Metric.
Proceedings of The 8th Asian Conference on Machine Learning, 2016

Instance Specific Metric Subspace Learning: A Bayesian Approach.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Auxiliary Information Regularized Machine for Multiple Modality Feature Learning.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Rank Consistency based Multi-View Learning: A Privacy-Preserving Approach.
Proceedings of the 24th ACM International Conference on Information and Knowledge Management, 2015


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