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Learning to Classify With Incremental New Class

IEEE transaction on neural networks and learning systems, 2022-06, Vol.33 (6), p.2429-2443

2022

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Learning Adaptive Classifiers Synthesis for Generalized Few-Shot Learning

International journal of computer vision, 2021-06, Vol.129 (6), p.1930-1953

2021

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Generalized Knowledge Distillation via Relationship Matching

IEEE transactions on pattern analysis and machine intelligence, 2023-02, Vol.45 (2), p.1817-1834

2023

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Few-Shot Learning With a Strong Teacher

IEEE transactions on pattern analysis and machine intelligence, 2024-03, Vol.46 (3), p.1425-1440

2024

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Revisiting Unsupervised Meta-Learning via the Characteristics of Few-Shot Tasks

IEEE transactions on pattern analysis and machine intelligence, 2023-03, Vol.45 (3), p.3721-3737

2023

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Few-Shot Class-Incremental Learning by Sampling Multi-Phase Tasks

IEEE transactions on pattern analysis and machine intelligence, 2023-11, Vol.45 (11), p.12816-12831

2023

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Semi-Supervised Multi-Modal Clustering and Classification with Incomplete Modalities

IEEE transactions on knowledge and data engineering, 2021-02, Vol.33 (2), p.682-695

2021

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Few-shot learning with adaptively initialized task optimizer: a practical meta-learning approach

Machine learning, 2020-03, Vol.109 (3), p.643-664

2020

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Semi-Supervised Multi-Modal Multi-Instance Multi-Label Deep Network with Optimal Transport

IEEE transactions on knowledge and data engineering, 2021-02, Vol.33 (2), p.696-709

2021

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Learning Multiple Local Metrics: Global Consideration Helps

IEEE transactions on pattern analysis and machine intelligence, 2020-07, Vol.42 (7), p.1698-1712

2020

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Supervised nonlinear dimensionality reduction for visualization and classification

IEEE transactions on cybernetics, 2005-12, Vol.35 (6), p.1098-1107

2005

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Heterogeneous Few-Shot Model Rectification With Semantic Mapping

IEEE transactions on pattern analysis and machine intelligence, 2021-11, Vol.43 (11), p.3878-3891

2021

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Cost-Effective Incremental Deep Model: Matching Model Capacity With the Least Sampling

IEEE transactions on knowledge and data engineering, 2023-04, Vol.35 (4), p.3575-3588

2023

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Contextualizing Meta-Learning via Learning to Decompose

IEEE transactions on pattern analysis and machine intelligence, 2024-01, Vol.46 (1), p.117-133

2024

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What Makes Objects Similar: A Unified Multi-Metric Learning Approach

IEEE transactions on pattern analysis and machine intelligence, 2019-05, Vol.41 (5), p.1257-1270

2019

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Corporate Relative Valuation Using Heterogeneous Multi-Modal Graph Neural Network

IEEE transactions on knowledge and data engineering, 2023-01, Vol.35 (1), p.211-224

2023

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Few-Shot Learning via Embedding Adaptation With Set-to-Set Functions

2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020, p.8805-8814

2020

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Learning Placeholders for Open-Set Recognition

2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021, p.4399-4408

2021

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Robust Semi-Supervised Learning by Wisely Leveraging Open-Set Data

IEEE transactions on pattern analysis and machine intelligence, 2024-12, Vol.46 (12), p.8334-8347

2024

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The Capacity and Robustness Trade-Off: Revisiting the Channel Independent Strategy for Multivariate Time Series Forecasting

IEEE transactions on knowledge and data engineering, 2024-11, Vol.36 (11), p.7129-7142

2024

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A Novel Serial Multimodal Biometrics Framework Based on Semisupervised Learning Techniques

IEEE transactions on information forensics and security, 2014-10, Vol.9 (10), p.1681-1694

2014

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Forward Compatible Few-Shot Class-Incremental Learning

2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022, p.9036-9046

2022

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Physics‐Informed Inverse Design of Programmable Metasurfaces

Advanced science, 2024-11, Vol.11 (41), p.e2406878-n/a

2024

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Learning Debiased Representations via Conditional Attribute Interpolation

2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023, p.7599-7608

2023

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Aligning model outputs for class imbalanced non-IID federated learning

Machine learning, 2024-04, Vol.113 (4), p.1861-1884

2024

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Learning to Classify With Incremental New Class

Learning Adaptive Classifiers Synthesis for Generalized Few-Shot Learning

Generalized Knowledge Distillation via Relationship Matching

Few-Shot Learning With a Strong Teacher

Revisiting Unsupervised Meta-Learning via the Characteristics of Few-Shot Tasks

Few-Shot Class-Incremental Learning by Sampling Multi-Phase Tasks

Semi-Supervised Multi-Modal Clustering and Classification with Incomplete Modalities

Few-shot learning with adaptively initialized task optimizer: a practical meta-learning approach

Semi-Supervised Multi-Modal Multi-Instance Multi-Label Deep Network with Optimal Transport

Learning Multiple Local Metrics: Global Consideration Helps

Supervised nonlinear dimensionality reduction for visualization and classification

Heterogeneous Few-Shot Model Rectification With Semantic Mapping

Cost-Effective Incremental Deep Model: Matching Model Capacity With the Least Sampling

Contextualizing Meta-Learning via Learning to Decompose

What Makes Objects Similar: A Unified Multi-Metric Learning Approach

Corporate Relative Valuation Using Heterogeneous Multi-Modal Graph Neural Network

Few-Shot Learning via Embedding Adaptation With Set-to-Set Functions

Learning Placeholders for Open-Set Recognition

Robust Semi-Supervised Learning by Wisely Leveraging Open-Set Data

The Capacity and Robustness Trade-Off: Revisiting the Channel Independent Strategy for Multivariate Time Series Forecasting

A Novel Serial Multimodal Biometrics Framework Based on Semisupervised Learning Techniques

Forward Compatible Few-Shot Class-Incremental Learning

Physics‐Informed Inverse Design of Programmable Metasurfaces

Learning Debiased Representations via Conditional Attribute Interpolation

Aligning model outputs for class imbalanced non-IID federated learning

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