Bo An

Associate Professor

Nanyang Technological University (NTU)

Singapore

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Bo An is an Associate Professor at Nanyang Technological University in Singapore. His research interests include deep graph anomaly detection, multi-agent reinforcement learning, and neural architecture search. Dr. An has contributed significantly to advancing innovation and collaboration in the field, as evidenced by his recent publications in prominent academic journals.

Articles (18)

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2025

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2020

Collaborators (7)

Zexiang Shen

Assoc. Prof; Prof.

Nanyang Technological University (NTU)

SINGAPORE

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Masashi Sugiyama

University of Tokyo

JAPAN

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Donghui Lin

Associate Professor

Okayama University

JAPAN

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Xinrun Wang

Assistant Professor

Singapore Management University

SINGAPORE

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Nikolay Zheludev

Director/Professor

Nanyang Technological University (NTU)

SINGAPORE

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Miao Xu

Lecturer

The University of Queensland

AUSTRALIA

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Lei Feng

Assistant Professor

Singapore University of Technology and Design

SINGAPORE

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Bo An

Research Interests

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About

Articles (18)

Double Oracle Neural Architecture Search for Game Theoretic Deep Learning Models

Deep Graph Anomaly Detection: A Survey and New Perspectives

Pioneering the Future: Advancing Innovation and Collaboration

Robust Multi-Agent Reinforcement Learning by Mutual Information Regularization

Retrieving positions of closely packed subwavelength nanoparticles from their diffraction patterns

TWOSOME: An Efficient Online Framework to Align LLMs with Embodied Environments via Reinforcement Learning

Robust Multi-Agent Communication With Graph Information Bottleneck Optimization

Reinforcement Learning for Quantitative Trading

Multiagent Reinforcement Learning With Graphical Mutual Information Maximization

Multiple-Instance Learning From Unlabeled Bags With Pairwise Similarity

On the Robustness of Average Losses for Partial-Label Learning

Effective Interpretable Policy Distillation via Critical Experience Point Identification

Batch Crowdsourcing for Complex Tasks Based on Distributed Team Formation in E-Markets

Regularized Matrix Factorization for Multilabel Learning With Missing Labels

Deep Reinforcement Learning for Quantitative Trading: Challenges and Opportunities

Deep Learning From Multiple Noisy Annotators as A Union

Embedding-Augmented Generalized Matrix Factorization for Recommendation With Implicit Feedback

Context-Aware Reliable Crowdsourcing in Social Networks

Collaborators (7)

Zexiang Shen

Masashi Sugiyama

Donghui Lin

Xinrun Wang

Nikolay Zheludev

Miao Xu

Lei Feng

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