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Data-Efficient Learning via Minimizing Hyperspherical Energy

  • Published:2023 Issue: Volume: Page:1-15
  • ISSN:0162-8828
  • Container-title:IEEE Transactions on Pattern Analysis and Machine Intelligence
  • language:
  • Short-container-title:IEEE Trans. Pattern Anal. Mach. Intell.

Author:

Cao Xiaofeng1ORCID,Liu Weiyang2ORCID,Tsang Ivor W.3ORCID

Affiliation:

1. School of Artificial Intelligence, Jilin University, Changchun, China

2. Department of Engineering, University of Cambridge, U.K.

3. Centre for Frontier AI Research, and the Institute of High-Performance Computing, Agency for Science, Technology and Research (A*STAR), Singapore

Funder

National Natural Science Foundation of China

Maritime AI Research Programme

AI Singapore OTTC

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Computer Vision and Pattern Recognition,Software

Reference79 articles.

1. Generative Modeling for Small-Data Object Detection

2. A kernel two-sample test;gretton;J Mach Learn Res,2012

3. Random Erasing Data Augmentation

4. Transfer learning by distribution matching for targeted advertising;bickel;Proc Int Conf Neural Inf Process,2008

5. Agnostic active learning without constraints;beygelzimer;Proc 23rd Int Conf Neural Inf Process Syst,2010

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1. Robust Uncertainty Estimation for Active Sampling;Proceedings of the 2024 3rd International Conference on Cyber Security, Artificial Intelligence and Digital Economy;2024-03

2. Hyperspherical Structural-Aware Distillation Enhanced Spatial–Spectral Bidirectional Interaction Network for Hyperspectral Image Classification;IEEE Transactions on Geoscience and Remote Sensing;2024

3. Cooperative Active Learning-Based Dual Control for Exploration and Exploitation in Autonomous Search;IEEE Transactions on Neural Networks and Learning Systems;2024

4. Cognition-Driven Structural Prior for Instance-Dependent Label Transition Matrix Estimation;IEEE Transactions on Neural Networks and Learning Systems;2024
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