Tiến sĩ Lê Duy Dũng

Trình độ học vấn

• Học giả thỉnh giảng tại Đại học Cornell, Khoa Khoa học Máy tính (2023 - nay), Mỹ
• Tiến sĩ Khoa học Máy tính, Trường Hệ thống Thông tin và Máy tính, Đại học Quản lý Singapore, Singapore
• Bằng Kỹ sư Toán tin, Trường Toán tin ứng dụng, Đại học Bách khoa Hà Nội, Hà Nội, Việt Nam

Hướng nghiên cứu chính

AI, Học máy, Tối ưu hóa

Các ấn phẩm nghiên cứu khoa học tiêu biểu

[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