Hung Hai Bui

According to our database, Hung Hai Bui authored at least 92 papers between 1996 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Building and Nurturing AI Development in Vietnam.

Hung Bui, Nguyen Minh Le, Dat Quoc Nguyen, Linh Pham, Dinh Q. Phung

Commun. ACM, July, 2023

PhoGPT: Generative Pre-training for Vietnamese.

Dat Quoc Nguyen, Linh The Nguyen, Chi Tran, Dung Ngoc Nguyen, Nhung Nguyen, Thien Huu Nguyen, Dinh Q. Phung, Hung Hai Bui

CoRR, 2023

A Vietnamese Spelling Correction System.

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

Proceedings of the Companion Proceedings of the 28th International Conference on Intelligent User Interfaces, 2023

On Cross-Layer Alignment for Model Fusion of Heterogeneous Neural Networks.

Dang Nguyen, Trang Nguyen, Khai Nguyen, Dinh Q. Phung, Hung Hai Bui, Nhat Ho

Proceedings of the IEEE International Conference on Acoustics, 2023

2022

Vietnamese Speech-based Question Answering over Car Manuals.

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

Proceedings of the IUI 2022: 27th International Conference on Intelligent User Interfaces, Helsinki, Finland, March 22 - 25, 2022, 2022

A Vietnamese-English Neural Machine Translation System.

Tuan-Duy H. Nguyen, Duy Phung, Duy Tran-Cong Nguyen, Hieu Minh Tran, Manh Luong, Tin Duy Vo, Hung Hai Bui, Dinh Q. Phung, Dat Quoc Nguyen

Proceedings of the 23rd Annual Conference of the International Speech Communication Association, 2022

On Transportation of Mini-batches: A Hierarchical Approach.

Khai Nguyen, Dang Nguyen, Quoc Dinh Nguyen, Tung Pham, Hung Bui, Dinh Phung, Trung Le, Nhat Ho

Proceedings of the International Conference on Machine Learning, 2022

2021

On efficient multilevel Clustering via Wasserstein distances.

Viet Huynh, Nhat Ho, Nhan Dam, XuanLong Nguyen, Mikhail Yurochkin, Hung Bui, Dinh Q. Phung

J. Mach. Learn. Res., 2021

Model Fusion of Heterogeneous Neural Networks via Cross-Layer Alignment.

Dang Nguyen, Khai Nguyen, Dinh Phung, Hung Bui, Nhat Ho

CoRR, 2021

On Label Shift in Domain Adaptation via Wasserstein Distance.

Trung Le, Dat Do, Tuan Nguyen, Huy Nguyen, Hung Bui, Nhat Ho, Dinh Q. Phung

CoRR, 2021

On Robust Optimal Transport: Computational Complexity, Low-rank Approximation, and Barycenter Computation.

Khang Le, Huy Nguyen, Quang Nguyen, Nhat Ho, Tung Pham, Hung Bui

CoRR, 2021

BoMb-OT: On Batch of Mini-batches Optimal Transport.

Khai Nguyen, Quoc Nguyen, Nhat Ho, Tung Pham, Hung Bui, Dinh Phung, Trung Le

CoRR, 2021

On Learning Domain-Invariant Representations for Transfer Learning with Multiple Sources.

Trung Phung, Trung Le, Long Vuong, Toan Tran, Anh Tran, Hung Bui, Dinh Q. Phung

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

On Robust Optimal Transport: Computational Complexity and Barycenter Computation.

Khang Le, Huy Nguyen, Quang Minh Nguyen, Tung Pham, Hung Bui, Nhat Ho

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

LAMDA: Label Matching Deep Domain Adaptation.

Trung Le, Tuan Nguyen, Nhat Ho, Hung Bui, Dinh Phung

Proceedings of the 38th International Conference on Machine Learning, 2021

Improving Relational Regularized Autoencoders with Spherical Sliced Fused Gromov Wasserstein.

Khai Nguyen, Son Nguyen, Nhat Ho, Tung Pham, Hung Bui

Proceedings of the 9th International Conference on Learning Representations, 2021

Distributional Sliced-Wasserstein and Applications to Generative Modeling.

Khai Nguyen, Nhat Ho, Tung Pham, Hung Bui

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

On Unbalanced Optimal Transport: An Analysis of Sinkhorn Algorithm.

Khiem Pham, Khang Le, Nhat Ho, Tung Pham, Hung Bui

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Learning Generative Adversarial Networks from Multiple Data Sources.

Trung Le, Quan Hoang, Hung Vu, Tu Dinh Nguyen, Hung Bui, Dinh Q. Phung

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Three-Player Wasserstein GAN via Amortised Duality.

Nhan Dam, Quan Hoang, Trung Le, Tu Dinh Nguyen, Hung Bui, Dinh Phung

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

2018

SpectralLeader: Online Spectral Learning for Single Topic Models.

Tong Yu, Branislav Kveton, Zheng Wen, Hung Bui, Ole J. Mengshoel

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

Robust Locally-Linear Controllable Embedding.

Ershad Banijamali, Rui Shu, Mohammad Ghavamzadeh, Hung Bui, Ali Ghodsi

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

SpectralFPL: Online Spectral Learning for Single Topic Models.

Tong Yu, Branislav Kveton, Zheng Wen, Hung Bui, Ole J. Mengshoel

CoRR, 2017

Hierarchical semi-Markov conditional random fields for deep recursive sequential data.

Truyen Tran, Dinh Quoc Phung, Hung Bui, Svetha Venkatesh

Artif. Intell., 2017

Discriminative Bayesian Nonparametric Clustering.

Vu Nguyen, Dinh Q. Phung, Trung Le, Hung Bui

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Large-scale Online Kernel Learning with Random Feature Reparameterization.

Tu Dinh Nguyen, Trung Le, Hung Bui, Dinh Q. Phung

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Bottleneck Conditional Density Estimation.

Rui Shu, Hung Hai Bui, Mohammad Ghavamzadeh

Proceedings of the 34th International Conference on Machine Learning, 2017

Multilevel Clustering via Wasserstein Means.

Nhat Ho, XuanLong Nguyen, Mikhail Yurochkin, Hung Hai Bui, Viet Huynh, Dinh Q. Phung

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

Scalable Nonparametric Bayesian Multilevel Clustering.

Viet Huynh, Dinh Q. Phung, Svetha Venkatesh, XuanLong Nguyen, Matthew D. Hoffman, Hung Hai Bui

Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Graphical Model Sketch.

Branislav Kveton, Hung Bui, Mohammad Ghavamzadeh, Georgios Theocharous, S. Muthukrishnan, Siqi Sun

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

Practical Linear Models for Large-Scale One-Class Collaborative Filtering.

Suvash Sedhain, Hung Bui, Jaya Kawale, Nikos Vlassis, Branislav Kveton, Aditya Krishna Menon, Trung Bui, Scott Sanner

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

2015

Architectures for Activity Recognition and Context-Aware Computing.

Christopher W. Geib, Vikas Agrawal, Gita Sukthankar, Lokendra Shastri, Hung Bui

AI Mag., 2015

A Bayesian Nonparametric Approach to Multilevel Regression.

Vu Nguyen, Dinh Q. Phung, Svetha Venkatesh, Hung Hai Bui

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2015

Learning Conditional Latent Structures from Multiple Data Sources.

Viet Huynh, Dinh Q. Phung, XuanLong Nguyen, Svetha Venkatesh, Hung Hai Bui

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2015

Efficient Thompson Sampling for Online Matrix-Factorization Recommendation.

Jaya Kawale, Hung Hai Bui, Branislav Kveton, Long Tran-Thanh, Sanjay Chawla

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014

MCMC for Hierarchical Semi-Markov Conditional Random Fields.

Truyen Tran, Dinh Q. Phung, Svetha Venkatesh, Hung Hai Bui

CoRR, 2014

Human Activity Learning and Segmentation using Partially Hidden Discriminative Models.

Tran The Truyen, Hung Bui, Svetha Venkatesh

CoRR, 2014

Boosted Markov Networks for Activity Recognition.

Tran The Truyen, Hung Bui, Svetha Venkatesh

CoRR, 2014

Lifted Tree-Reweighted Variational Inference.

Hung Hai Bui, Tuyen N. Huynh, David A. Sontag

Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

Bayesian Nonparametric Multilevel Clustering with Group-Level Contexts.

Tien-Vu Nguyen, Dinh Quoc Phung, XuanLong Nguyen, Svetha Venkatesh, Hung Bui

Proceedings of the 31th International Conference on Machine Learning, 2014

2013

The AAAI-13 Conference Workshops.

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

AI Mag., 2013

Automorphism Groups of Graphical Models and Lifted Variational Inference.

Hung Bui, Tuyen N. Huynh, Sebastian Riedel

Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

Organizers.

Hung Hai Bui

Proceedings of the Plan, 2013

2012

Initial Empirical Evaluation of Anytime Lifted Belief Propagation.

Richard G. Freedman, Rodrigo de Salvo Braz, Hung Bui, Sriraam Natarajan

Proceedings of the 2nd International Workshop on Statistical Relational AI (StaRAI-12), 2012

Lifted Arbitrary Constraint Solving for Lifted Probabilistic Inference.

Rodrigo de Salvo Braz, Shahin Saadati, Hung Bui, Ciaran O'Reilly

Proceedings of the 2nd International Workshop on Statistical Relational AI (StaRAI-12), 2012

Exact Lifted Inference with Distinct Soft Evidence on Every Object.

Hung Hai Bui, Tuyen N. Huynh, Rodrigo de Salvo Braz

Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012

2011

Efficient Methods for Lifted Inference with Aggregate Factors.

Jaesik Choi, Rodrigo de Salvo Braz, Hung Hai Bui

Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011

2010

Bayesian Minimax Estimation of the Normal Model With Incomplete Prior Covariance Matrix Specification.

Duc-Son Pham, Hung Hai Bui, Svetha Venkatesh

IEEE Trans. Inf. Theory, 2010

Efficient variable elimination for semi-structured simple temporal networks with continuous domains.

Neil Yorke-Smith, Hung Hai Bui

Knowl. Eng. Rev., 2010

2009

Efficient duration and hierarchical modeling for human activity recognition.

Thi V. Duong, Dinh Q. Phung, Hung Bui, Svetha Venkatesh

Artif. Intell., 2009

Efficient Online Learning and Prediction of Users' Desktop Actions.

Omid Madani, Hung Bui, Eric Yeh

Proceedings of the IJCAI 2009, 2009

Prediction and Discovery of Users' Desktop Behavior.

Omid Madani, Hung Bui, Eric Yeh

Proceedings of the Human Behavior Modeling, 2009

2008

Recovering Social Networks From Massive Track Datasets.

Christopher I. Connolly, J. Brian Burns, Hung Hai Bui

Proceedings of the 9th IEEE Workshop on Applications of Computer Vision (WACV 2008), 2008

Learning Discriminative Sequence Models from Partially Labelled Data for Activity Recognition.

Tran The Truyen, Hung Hai Bui, Dinh Q. Phung, Svetha Venkatesh

Proceedings of the PRICAI 2008: Trends in Artificial Intelligence, 2008

Hierarchical Semi-Markov Conditional Random Fields for Recursive Sequential Data.

Tran The Truyen, Dinh Q. Phung, Hung Bui, Svetha Venkatesh

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Logical Hierarchical Hidden Markov Models for Modeling User Activities.

Sriraam Natarajan, Hung Hai Bui, Prasad Tadepalli, Kristian Kersting, Weng-Keen Wong

Proceedings of the Inductive Logic Programming, 18th International Conference, 2008

A context-aware personal desktop assistant.

Hung Hai Bui, Federico Cesari, Daniel Elenius, David N. Morley, Sriraam Natarajan, Shahin Saadati, Eric Yeh, Neil Yorke-Smith

Proceedings of the 7th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2008), 2008

The Hidden Permutation Model and Location-Based Activity Recognition.

Hung Hai Bui, Dinh Q. Phung, Svetha Venkatesh, Hai Phan

Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 2008

2006

Human Behavior Recognition with Generic Exponential Family Duration Modeling in the Hidden Semi-Markov Model.

Thi V. Duong, Dinh Q. Phung, Hung Hai Bui, Svetha Venkatesh

Proceedings of the 18th International Conference on Pattern Recognition (ICPR 2006), 2006

AdaBoost.MRF: Boosted Markov Random Forests and Application to Multilevel Activity Recognition.

Tran The Truyen, Dinh Q. Phung, Svetha Venkatesh, Hung Hai Bui

Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2006), 2006

Recognising Behaviours of Multiple People with Hierarchical Probabilistic Model and Statistical Data Association.

Nam Thanh Nguyen, Svetha Venkatesh, Hung Bui

Proceedings of the British Machine Vision Conference 2006, 2006

2005

A Probabilistic Framework for Extracting Narrative Act Boundaries and Semantics in Motion Pictures.

Brett Adams, Svetha Venkatesh, Hung Hai Bui, Chitra Dorai

Multim. Tools Appl., 2005

Robust Recognition and Segmentation of Human Actions Using HMMs with Missing Observations.

Patrick Peursum, Hung Hai Bui, Svetha Venkatesh, Geoff A. W. West

EURASIP J. Adv. Signal Process., 2005

Topic transition detection using hierarchical hidden Markov and semi-Markov models.

Dinh Q. Phung, Thi V. Duong, Svetha Venkatesh, Hung Hai Bui

Proceedings of the 13th ACM International Conference on Multimedia, 2005

Learning and Detecting Activities from Movement Trajectories Using the Hierarchical Hidden Markov Models.

Nam Thanh Nguyen, Dinh Q. Phung, Svetha Venkatesh, Hung Bui

Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2005), 2005

Activity Recognition and Abnormality Detection with the Switching Hidden Semi-Markov Model.

Thi V. Duong, Hung Hai Bui, Dinh Q. Phung, Svetha Venkatesh

Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2005), 2005

2004

Using Interaction Signatures to Find and Label Chairs and Floors.

Patrick Peursum, Svetha Venkatesh, Geoff A. W. West, Hung Hai Bui

IEEE Pervasive Comput., 2004

Using multiple windows to track concept drift.

Mihai M. Lazarescu, Svetha Venkatesh, Hung Hai Bui

Intell. Data Anal., 2004

Content Structure Discovery in Educational Videos Using Shared Structures in the Hierarchical Hidden Markov Models.

Dinh Q. Phung, Hung Hai Bui, Svetha Venkatesh

Proceedings of the Structural, 2004

Learning People Movement Model from Multiple Cameras for Behaviour Recognition.

Nam Thanh Nguyen, Svetha Venkatesh, Geoff A. W. West, Hung Hai Bui

Proceedings of the Structural, 2004

Classifying Human Actions Using an Incomplete Real-Time Pose Skeleton.

Patrick Peursum, Hung Hai Bui, Svetha Venkatesh, Geoff A. W. West

Proceedings of the PRICAI 2004: Trends in Artificial Intelligence, 2004

Explicit State Duration HMM for Abnormality Detection in Sequences of Human Activity.

Sebastian Lühr, Svetha Venkatesh, Geoff A. W. West, Hung Hai Bui

Proceedings of the PRICAI 2004: Trends in Artificial Intelligence, 2004

Segmentation of Intentional Human Gestures for Sports Video Annotation.

Graeme S. Chambers, Svetha Venkatesh, Geoff A. W. West, Hung Hai Bui

Proceedings of the 10th International Multimedia Modeling Conference (MMM 2004), 2004

Human Action Segmentation via Controlled Use of Missing Data in HMMs.

Patrick Peursum, Hung Hai Bui, Svetha Venkatesh, Geoff A. W. West

Proceedings of the 17th International Conference on Pattern Recognition, 2004

Automatically learning structural units in educational videos with the hierarchical hidden markov models.

Dinh Q. Phung, Svetha Venkatesh, Hung Hai Bui

Proceedings of the 2004 International Conference on Image Processing, 2004

Learning Hierarchical Hidden Markov Models with General State Hierarchy.

Hung Hai Bui, Dinh Q. Phung, Svetha Venkatesh

Proceedings of the Nineteenth National Conference on Artificial Intelligence, 2004

2003

Object Labelling from Human Action Recognition.

Patrick Peursum, Svetha Venkatesh, Geoff A. W. West, Hung Hai Bui

Proceedings of the First IEEE International Conference on Pervasive Computing and Communications (PerCom'03), 2003

Recognition of Human Activity through Hierarchical Stochastic Learning.

Sebastian Lühr, Hung Hai Bui, Svetha Venkatesh, Geoff A. W. West

Proceedings of the First IEEE International Conference on Pervasive Computing and Communications (PerCom'03), 2003

A General Model for Online Probabilistic Plan Recognition.

Hung Hai Bui

Proceedings of the IJCAI-03, 2003

Indexing narrative structure and semantics in motion pictures with a probabilistic framework.

Brett Adams, Chitra Dorai, Svetha Venkatesh, Hung Hai Bui

Proceedings of the 2003 IEEE International Conference on Multimedia and Expo, 2003

Recognising and Monitoring High-Level Behaviours in Complex Spatial Environments.

Nam Thanh Nguyen, Hung Hai Bui, Svetha Venkatesh, Geoff A. W. West

Proceedings of the 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2003), 2003

2002

Policy Recognition in the Abstract Hidden Markov Model.

Hung Hai Bui, Svetha Venkatesh, Geoff A. W. West

J. Artif. Intell. Res., 2002

Hierarchical Monitoring of People's Behaviors in Complex Environments Using Multiple Cameras.

Nam Thanh Nguyen, Svetha Venkatesh, Geoff A. W. West, Hung Hai Bui

Proceedings of the 16th International Conference on Pattern Recognition, 2002

Hierarchical Recognition of Intentional Human Gestures for Sports Video Annotation.

Graeme S. Chambers, Svetha Venkatesh, Geoff A. W. West, Hung Hai Bui

Proceedings of the 16th International Conference on Pattern Recognition, 2002

2001

Tracking and Surveillance in Wide-Area Spatial Environments Using the Abstract Hidden Markov Model.

Hung Hai Bui, Svetha Venkatesh, Geoff A. W. West

Int. J. Pattern Recognit. Artif. Intell., 2001

2000

A Probabilistic Framework for Tracking in Wide-Area Environments.

Hung Hai Bui, Svetha Venkatesh, Geoff A. W. West

Proceedings of the 15th International Conference on Pattern Recognition, 2000

On the Recognition of Abstract Markov Policies.

Hung Hai Bui, Svetha Venkatesh, Geoff A. W. West

Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on on Innovative Applications of Artificial Intelligence, July 30, 2000

1999

Learning Other Agents' Preferences in Multi-Agent Negotiation Using the Bayesian Classifier.

Hung Hai Bui, Svetha Venkatesh, Dorota H. Kieronska

Int. J. Cooperative Inf. Syst., 1999

Layered dynamic probabilistic networks for spatio-temporal modelling.

Hung Hai Bui, Svetha Venkatesh, Geoff A. W. West

Intell. Data Anal., 1999

1997

A Framework for Coordination and Learning among Teams of Agents.

Hung Hai Bui, Svetha Venkatesh, Dorota H. Kieronska

Proceedings of the Agents and Multi-Agent Systems Formalisms, 1997

Optimal Communication Among Team Members.

Hung Hai Bui, Dorota H. Kieronska, Svetha Venkatesh

Proceedings of the Advanced Topics in Artificial Intelligence, 1997

1996

Learning other Agents' Preferences in Multiagent Negotiation.

Hung Hai Bui, Dorota H. Kieronska, Svetha Venkatesh

Proceedings of the Thirteenth National Conference on Artificial Intelligence and Eighth Innovative Applications of Artificial Intelligence Conference, 1996