Hung Bui - RankMe

48 papers A* 14A 3Journal 21Unranked 10

Year	Rank	Type	Title / Venue / Authors
2023	—	`conf`	A Vietnamese Spelling Correction System. IUI Companion Thien Hai Nguyen, Thinh Pham, Khoi Minh Le, Manh Luong, Nguyen Luong Tran, Hieu Man, Dang Minh Nguyen, Tuan Anh Luu, Thien Huu Nguyen, Hung Bui, Dinh Phung, Dat Quoc Nguyen
2023	J	`jnl`	Building and Nurturing AI Development in Vietnam. Commun. ACM Hung Bui, Nguyen Minh Le, Dat Quoc Nguyen, Linh Pham, Dinh Q. Phung
2022	A*	`conf`	On Transportation of Mini-batches: A Hierarchical Approach. ICML Khai Nguyen, Dang Nguyen, Quoc Dinh Nguyen, Tung Pham, Hung Bui, Dinh Phung, Trung Le, Nhat Ho
2022	—	`conf`	Vietnamese Speech-based Question Answering over Car Manuals. IUI Companion Tin Duy Vo, Manh Luong, Duong Minh Le, Hieu Tran, Nhan Do, Tuan-Duy H. Nguyen, Thien Nguyen, Hung Bui, Dat Quoc Nguyen, Dinh Q. Phung
2021	J	`jnl`	BoMb-OT: On Batch of Mini-batches Optimal Transport. CoRR Khai Nguyen, Quoc Nguyen, Nhat Ho, Tung Pham, Hung Bui, Dinh Phung, Trung Le
2021	A*	`conf`	Distributional Sliced-Wasserstein and Applications to Generative Modeling. ICLR Khai Nguyen, Nhat Ho, Tung Pham, Hung Bui
2021	A*	`conf`	Improving Relational Regularized Autoencoders with Spherical Sliced Fused Gromov Wasserstein. ICLR Khai Nguyen, Son Nguyen, Nhat Ho, Tung Pham, Hung Bui
2021	A*	`conf`	LAMDA: Label Matching Deep Domain Adaptation. ICML Trung Le, Tuan Nguyen, Nhat Ho, Hung Bui, Dinh Phung
2021	J	`jnl`	Model Fusion of Heterogeneous Neural Networks via Cross-Layer Alignment. CoRR Dang Nguyen, Khai Nguyen, Dinh Phung, Hung Bui, Nhat Ho
2021	J	`jnl`	On Label Shift in Domain Adaptation via Wasserstein Distance. CoRR Trung Le, Dat Do, Tuan Nguyen, Huy Nguyen, Hung Bui, Nhat Ho, Dinh Q. Phung
2021	A*	`conf`	On Learning Domain-Invariant Representations for Transfer Learning with Multiple Sources. NeurIPS Trung Phung, Trung Le, Long Vuong, Toan Tran, Anh Tran, Hung Bui, Dinh Q. Phung
2021	J	`jnl`	On Learning Domain-Invariant Representations for Transfer Learning with Multiple Sources. CoRR Trung Phung, Trung Le, Long Vuong, Toan Tran, Anh Tran, Hung Bui, Dinh Phung
2021	A*	`conf`	On Robust Optimal Transport: Computational Complexity and Barycenter Computation. NeurIPS Khang Le, Huy Nguyen, Quang Minh Nguyen, Tung Pham, Hung Bui, Nhat Ho
2021	J	`jnl`	On Robust Optimal Transport: Computational Complexity, Low-rank Approximation, and Barycenter Computation. CoRR Khang Le, Huy Nguyen, Quang Nguyen, Nhat Ho, Tung Pham, Hung Bui
2021	J	`jnl`	On efficient multilevel Clustering via Wasserstein distances. J. Mach. Learn. Res. Viet Huynh, Nhat Ho, Nhan Dam, XuanLong Nguyen, Mikhail Yurochkin, Hung Bui, Dinh Q. Phung
2020	J	`jnl`	Distributional Sliced-Wasserstein and Applications to Generative Modeling. CoRR Khai Nguyen, Nhat Ho, Tung Pham, Hung Bui
2020	J	`jnl`	Improving Relational Regularized Autoencoders with Spherical Sliced Fused Gromov Wasserstein. CoRR Khai Nguyen, Son Nguyen, Nhat Ho, Tung Pham, Hung Bui
2020	A*	`conf`	On Unbalanced Optimal Transport: An Analysis of Sinkhorn Algorithm. ICML Khiem Pham, Khang Le, Nhat Ho, Tung Pham, Hung Bui
2020	J	`jnl`	On Unbalanced Optimal Transport: An Analysis of Sinkhorn Algorithm. CoRR Khiem Pham, Khang Le, Nhat Ho, Tung Pham, Hung Bui
2019	A*	`conf`	Learning Generative Adversarial Networks from Multiple Data Sources. IJCAI Trung Le, Quan Hoang, Hung Vu, Tu Dinh Nguyen, Hung Bui, Dinh Q. Phung
2019	J	`jnl`	On Efficient Multilevel Clustering via Wasserstein Distances. CoRR Viet Huynh, Nhat Ho, Nhan Dam, XuanLong Nguyen, Mikhail Yurochkin, Hung Bui, Dinh Q. Phung
2019	A*	`conf`	Three-Player Wasserstein GAN via Amortised Duality. IJCAI Nhan Dam, Quan Hoang, Trung Le, Tu Dinh Nguyen, Hung Bui, Dinh Phung
2018	A	`conf`	Robust Locally-Linear Controllable Embedding. AISTATS Ershad Banijamali, Rui Shu, Mohammad Ghavamzadeh, Hung Bui, Ali Ghodsi
2018	—	`conf`	SpectralLeader: Online Spectral Learning for Single Topic Models. ECML/PKDD (2) Tong Yu, Branislav Kveton, Zheng Wen, Hung Bui, Ole J. Mengshoel
2017	A*	`conf`	Discriminative Bayesian Nonparametric Clustering. IJCAI Vu Nguyen, Dinh Q. Phung, Trung Le, Hung Bui
2017	J	`jnl`	Hierarchical semi-Markov conditional random fields for deep recursive sequential data. Artif. Intell. Truyen Tran, Dinh Quoc Phung, Hung Bui, Svetha Venkatesh
2017	A*	`conf`	Large-scale Online Kernel Learning with Random Feature Reparameterization. IJCAI Tu Dinh Nguyen, Trung Le, Hung Bui, Dinh Q. Phung
2017	J	`jnl`	Robust Locally-Linear Controllable Embedding. CoRR Ershad Banijamali, Rui Shu, Mohammad Ghavamzadeh, Hung Bui, Ali Ghodsi
2017	J	`jnl`	SpectralFPL: Online Spectral Learning for Single Topic Models. CoRR Tong Yu, Branislav Kveton, Zheng Wen, Hung Bui, Ole J. Mengshoel
2016	—	`conf`	Graphical Model Sketch. ECML/PKDD (1) Branislav Kveton, Hung Bui, Mohammad Ghavamzadeh, Georgios Theocharous, S. Muthukrishnan, Siqi Sun
2016	J	`jnl`	Graphical Model Sketch. CoRR Branislav Kveton, Hung Bui, Mohammad Ghavamzadeh, Georgios Theocharous, S. Muthukrishnan, Siqi Sun
2016	A*	`conf`	Practical Linear Models for Large-Scale One-Class Collaborative Filtering. IJCAI Suvash Sedhain, Hung Bui, Jaya Kawale, Nikos Vlassis, Branislav Kveton, Aditya Krishna Menon, Trung Bui, Scott Sanner
2015	J	`jnl`	Architectures for Activity Recognition and Context-Aware Computing. AI Mag. Christopher W. Geib, Vikas Agrawal, Gita Sukthankar, Lokendra Shastri, Hung Bui
2014	A*	`conf`	Bayesian Nonparametric Multilevel Clustering with Group-Level Contexts. ICML Tien-Vu Nguyen, Dinh Quoc Phung, XuanLong Nguyen, Svetha Venkatesh, Hung Bui
2014	J	`jnl`	Boosted Markov Networks for Activity Recognition. CoRR Tran The Truyen, Hung Bui, Svetha Venkatesh
2014	J	`jnl`	Human Activity Learning and Segmentation using Partially Hidden Discriminative Models. CoRR Tran The Truyen, Hung Bui, Svetha Venkatesh
2013	A	`conf`	Automorphism Groups of Graphical Models and Lifted Variational Inference. UAI Hung Bui, Tuyen N. Huynh, Sebastian Riedel
2013	J	`jnl`	Automorphism Groups of Graphical Models and Lifted Variational Inference. CoRR Hung Bui, Tuyen N. Huynh, Sebastian Riedel
2013	J	`jnl`	The AAAI-13 Conference Workshops. AI Mag. Vikas Agrawal, Christopher Archibald, Mehul Bhatt, Hung Bui, Diane J. Cook, Juan Cortés, Christopher W. Geib, Vibhav Gogate, Hans W. Guesgen, Dietmar Jannach, Michael Johanson, Kristian Kersting, George Dimitri Konidaris, Lars Kotthoff, Martin Michalowski, Sriraam Natarajan, Barry O'Sullivan, Marc Pickett, Vedran Podobnik, David Poole, Lokendra Shastri, Amarda Shehu, Gita Sukthankar
2012	—	`conf`	Initial Empirical Evaluation of Anytime Lifted Belief Propagation. StarAI@UAI Richard G. Freedman, Rodrigo de Salvo Braz, Hung Bui, Sriraam Natarajan
2012	—	`conf`	Lifted Arbitrary Constraint Solving for Lifted Probabilistic Inference. StarAI@UAI Rodrigo de Salvo Braz, Shahin Saadati, Hung Bui, Ciaran O'Reilly
2009	—	`conf`	Anytime Lifted Belief Propagation. MLG/SRL@ILP Rodrigo de Salvo Braz, Sriraam Natarajan, Hung Bui, Jude W. Shavlik, Stuart Russell
2009	A*	`conf`	Efficient Online Learning and Prediction of Users' Desktop Actions. IJCAI Omid Madani, Hung Bui, Eric Yeh
2009	J	`jnl`	Efficient duration and hierarchical modeling for human activity recognition. Artif. Intell. Thi V. Duong, Dinh Q. Phung, Hung Bui, Svetha Venkatesh
2009	—	`conf`	Prediction and Discovery of Users' Desktop Behavior. AAAI Spring Symposium: Human Behavior Modeling Omid Madani, Hung Bui, Eric Yeh
2008	—	`conf`	Hierarchical Semi-Markov Conditional Random Fields for Recursive Sequential Data. NIPS Tran The Truyen, Dinh Q. Phung, Hung Bui, Svetha Venkatesh
2006	A	`conf`	Recognising Behaviours of Multiple People with Hierarchical Probabilistic Model and Statistical Data Association. BMVC Nam Thanh Nguyen, Svetha Venkatesh, Hung Bui
2005	—	`conf`	Learning and Detecting Activities from Movement Trajectories Using the Hierarchical Hidden Markov Models. CVPR (2) Nam Thanh Nguyen, Dinh Q. Phung, Svetha Venkatesh, Hung Bui