Dr. Dung Le Duy
Education Background
- Visiting Scholar in Cornell University, Computer Science Department (2023 - now), USA
- PhD in Computer Science, School of Computing and Information Systems, Singapore Management University, Singapore
- Degree of Engineer in Mathematics and Informatics, School of Applied of Mathematics and Informatics, Hanoi University of Science and Technology, Hanoi, Vietnam
Research Interest
AI, Machine Learning, Optimization
Key Publications
[1] A Framework for Controllable Pareto Front Learning with Completed Scalarization Functions and its Applications Tran Anh Tuan, Long P. Hoang, Dung D. Le, Tran Ngoc Thang Neural Networks Journal, Jan 2024
[2] Enhancing Few-shot Image Classification with Cosine Transformer Quang-Huy Nguyen, Cuong Q. Nguyen, Dung D. Le, and Hieu H. Pham IEEE Access, 2023
[3] Efficient Retrieval of Matrix Factorization-based Top-k Recommendations: A Survey of Recent Approaches Dung D. Le and Hady W. Lauw Journal of Artificial Intelligence Research (JAIR), 2021
[4] Broadening the View: Demonstration-augmented Prompt Learning for Conversational Recommendation Huy Dao, Yang Deng, Dung D. Le, Lizi Liao The 47th ACM SIGIR on Research and Development in Information Retrieval (SIGIR 2024)
[5] Improving Vietnamese-English Medical Machine Translation Nhu Vo, Dat Quoc Nguyen, Dung D. Le, Massimo Piccardi and Wray Buntine The 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
[6] Towards Efficient Communication and Secure Federated Recommendation System via Low-rank Training Ngoc-Hieu Nguyen, Tuan-Anh Nguyen, Tuan Minh Nguyen, Vu Tien Hoang, Dung D. Le, Kok-Seng Wong The 2024 ACM Web Conference
[7] Reinforced Target-driven Conversational Promotion Huy Quang Dao, Lizi Liao, Dung D. Le, Yuxiang Nie The 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP 2023)
[8] Towards Data-Agnostic Pruning At Initialization: What Makes a Good Sparse Mask? Hoang Pham, The-Anh Ta, Shiwei Liu, Lichuan Xiang, Dung D. Le. Hongkai Wen, Long Tran-Thanh The 2023 Conference on Neural Processing Systems (NeurIPS 2023)
[9] A Probabilistic Framework for Pruning Transformers via a Finite Admixture of Keys T. Nguyen, T. Nguyen, Long Bui, Hai Do, Dung D. Le, Hung Tran-The, Duy Khuong Nguyen, N. Ho, S. J. Osher, R. G. Baraniuk The 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2023)
[10] Improving Pareto Front Learning via Multi-Sample Hypernetworks Hoang Phi Long, Dung D. Le, Tran Anh Tuan, Tran Ngoc Thang AAAI Conference on Artificial Intelligence (AAAI-23)
[11] Improving Transformers with Probabilistic Attention Keys T. Nguyen, T. Nguyen, Dung D. Le, K. Nguyen, A. Tran, R. G. Baraniuk, N. Ho, S. J. Osher The Thirty-ninth International Conference on Machine Learning (ICML 2022), July 2022
[12] Collaborative Curating for Discovery and Expansion of Visual Clusters Dung D. Le and Hady W. Lauw The 15th ACM International Conference in Web Search and Data Mining (WSDM-22), Feb 2022
[13] Stochastically Robust Personalized Ranking for LSH Recommendation Retrieval Dung D. Le and Hady W. Lauw AAAI Conference on Artificial Intelligence (AAAI-20), Feb 2020
[14] Learning Multiple Maps from Conditional Ordinal Triplets Dung D. Le and Hady W. Lauw International Joint Conference on Artificial Intelligence (IJCAI’19), Aug 2019
[15] Multiperspective Graph-Theoretic Similarity Measure Dung D. Le and Hady W. Lauw ACM Conference on Information and Knowledge Management (CIKM’18), Oct 2018
[16] Indexable Bayesian Personalized Ranking for Efficient Top-k Recommendation Dung D. Le and Hady W. Lauw ACM Conference on Information and Knowledge Management (CIKM’17), Nov 2017
[17] Euclidean Co-Embedding of Ordinal Data for Multi-Type Visualization Dung D. Le and Hady W. Lauw SIAM International Conference on Data Mining (SDM’16), May 2016