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ORCIDHung Hai Bui
Hung Bui 0001
Person information
- affiliation: Adobe Research, San Jose, USA
- affiliation: SRI International, Menlo Park, California, USA
Other persons with the same name
- Hung Bui — disambiguation page
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2020 – today
- 2023
[j16]Hung Bui, Nguyen Minh Le, Dat Quoc Nguyen, Linh Pham, Dinh Q. Phung:
Building and Nurturing AI Development in Vietnam. Commun. ACM 66(7): 75-76 (2023)- [c69]Dang Nguyen, Trang Nguyen, Khai Nguyen, Dinh Q. Phung, Hung Hai Bui, Nhat Ho:
On Cross-Layer Alignment for Model Fusion of Heterogeneous Neural Networks. ICASSP 2023: 1-5 - [c68]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:
A Vietnamese Spelling Correction System. IUI Companion 2023: 158-161 - [i23]Dat Quoc Nguyen, Linh The Nguyen, Chi Tran, Dung Ngoc Nguyen, Nhung Nguyen, Thien Huu Nguyen, Dinh Q. Phung, Hung Hai Bui:
PhoGPT: Generative Pre-training for Vietnamese. CoRR abs/2311.02945 (2023) - 2022
- [c67]Khai Nguyen, Dang Nguyen, Quoc Dinh Nguyen, Tung Pham, Hung Bui, Dinh Phung, Trung Le, Nhat Ho:
On Transportation of Mini-batches: A Hierarchical Approach. ICML 2022: 16622-16655 - [c66]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:
A Vietnamese-English Neural Machine Translation System. INTERSPEECH 2022: 5543-5544 - [c65]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:
Vietnamese Speech-based Question Answering over Car Manuals. IUI Companion 2022: 117-119 - 2021
- [j15]Viet Huynh, Nhat Ho, Nhan Dam, XuanLong Nguyen, Mikhail Yurochkin, Hung Bui, Dinh Q. Phung:
On efficient multilevel Clustering via Wasserstein distances. J. Mach. Learn. Res. 22: 145:1-145:43 (2021) - [c64]Khai Nguyen, Nhat Ho, Tung Pham, Hung Bui:
Distributional Sliced-Wasserstein and Applications to Generative Modeling. ICLR 2021 - [c63]Khai Nguyen, Son Nguyen, Nhat Ho, Tung Pham, Hung Bui:
Improving Relational Regularized Autoencoders with Spherical Sliced Fused Gromov Wasserstein. ICLR 2021 - [c62]Trung Le, Tuan Nguyen, Nhat Ho, Hung Bui, Dinh Phung:
LAMDA: Label Matching Deep Domain Adaptation. ICML 2021: 6043-6054 - [c61]Khang Le, Huy Nguyen, Quang Minh Nguyen, Tung Pham, Hung Bui, Nhat Ho:
On Robust Optimal Transport: Computational Complexity and Barycenter Computation. NeurIPS 2021: 21947-21959 - [c60]Trung Phung, Trung Le, Long Vuong, Toan Tran, Anh Tran, Hung Bui, Dinh Q. Phung:
On Learning Domain-Invariant Representations for Transfer Learning with Multiple Sources. NeurIPS 2021: 27720-27733 - [i22]Khai Nguyen, Quoc Nguyen, Nhat Ho, Tung Pham, Hung Bui, Dinh Phung, Trung Le:
BoMb-OT: On Batch of Mini-batches Optimal Transport. CoRR abs/2102.05912 (2021) - [i21]Khang Le, Huy Nguyen, Quang Nguyen, Nhat Ho, Tung Pham, Hung Bui:
On Robust Optimal Transport: Computational Complexity, Low-rank Approximation, and Barycenter Computation. CoRR abs/2102.06857 (2021) - [i20]Trung Le, Dat Do, Tuan Nguyen, Huy Nguyen, Hung Bui, Nhat Ho, Dinh Q. Phung:
On Label Shift in Domain Adaptation via Wasserstein Distance. CoRR abs/2110.15520 (2021) - [i19]Dang Nguyen, Khai Nguyen, Dinh Phung, Hung Bui, Nhat Ho:
Model Fusion of Heterogeneous Neural Networks via Cross-Layer Alignment. CoRR abs/2110.15538 (2021) - [i18]Trung Phung, Trung Le, Long Vuong, Toan Tran, Anh Tran, Hung Bui, Dinh Phung:
On Learning Domain-Invariant Representations for Transfer Learning with Multiple Sources. CoRR abs/2111.13822 (2021) - 2020
- [c59]Khiem Pham, Khang Le, Nhat Ho, Tung Pham, Hung Bui:
On Unbalanced Optimal Transport: An Analysis of Sinkhorn Algorithm. ICML 2020: 7673-7682 - [i17]Khiem Pham, Khang Le, Nhat Ho, Tung Pham, Hung Bui:
On Unbalanced Optimal Transport: An Analysis of Sinkhorn Algorithm. CoRR abs/2002.03293 (2020) - [i16]Khai Nguyen, Nhat Ho, Tung Pham, Hung Bui:
Distributional Sliced-Wasserstein and Applications to Generative Modeling. CoRR abs/2002.07367 (2020) - [i15]Khai Nguyen, Son Nguyen, Nhat Ho, Tung Pham, Hung Bui:
Improving Relational Regularized Autoencoders with Spherical Sliced Fused Gromov Wasserstein. CoRR abs/2010.01787 (2020)
2010 – 2019
- 2019
- [c58]Nhan Dam, Quan Hoang, Trung Le, Tu Dinh Nguyen, Hung Bui, Dinh Phung
:
Three-Player Wasserstein GAN via Amortised Duality. IJCAI 2019: 2202-2208 - [c57]Trung Le, Quan Hoang, Hung Vu, Tu Dinh Nguyen, Hung Bui, Dinh Q. Phung:
Learning Generative Adversarial Networks from Multiple Data Sources. IJCAI 2019: 2823-2829 - [i14]Viet Huynh, Nhat Ho, Nhan Dam, XuanLong Nguyen, Mikhail Yurochkin, Hung Bui, Dinh Q. Phung:
On Efficient Multilevel Clustering via Wasserstein Distances. CoRR abs/1909.08787 (2019) - 2018
- [c56]Ershad Banijamali, Rui Shu, Mohammad Ghavamzadeh, Hung Bui, Ali Ghodsi:
Robust Locally-Linear Controllable Embedding. AISTATS 2018: 1751-1759 - [c55]Tong Yu, Branislav Kveton, Zheng Wen, Hung Bui, Ole J. Mengshoel:
SpectralLeader: Online Spectral Learning for Single Topic Models. ECML/PKDD (2) 2018: 379-395 - 2017
- [j14]Truyen Tran, Dinh Quoc Phung, Hung Bui, Svetha Venkatesh:
Hierarchical semi-Markov conditional random fields for deep recursive sequential data. Artif. Intell. 246: 53-85 (2017) - [c54]Nhat Ho, XuanLong Nguyen, Mikhail Yurochkin, Hung Hai Bui, Viet Huynh, Dinh Q. Phung:
Multilevel Clustering via Wasserstein Means. ICML 2017: 1501-1509 - [c53]Rui Shu, Hung Hai Bui, Mohammad Ghavamzadeh:
Bottleneck Conditional Density Estimation. ICML 2017: 3164-3172 - [c52]Tu Dinh Nguyen, Trung Le, Hung Bui, Dinh Q. Phung:
Large-scale Online Kernel Learning with Random Feature Reparameterization. IJCAI 2017: 2543-2549 - [c51]Vu Nguyen, Dinh Q. Phung, Trung Le, Hung Bui:
Discriminative Bayesian Nonparametric Clustering. IJCAI 2017: 2550-2556 - [i13]Tong Yu, Branislav Kveton, Zheng Wen, Hung Bui, Ole J. Mengshoel:
SpectralFPL: Online Spectral Learning for Single Topic Models. CoRR abs/1709.07172 (2017) - [i12]Ershad Banijamali, Rui Shu, Mohammad Ghavamzadeh, Hung Bui, Ali Ghodsi:
Robust Locally-Linear Controllable Embedding. CoRR abs/1710.05373 (2017) - 2016
- [c50]Suvash Sedhain, Hung Bui, Jaya Kawale, Nikos Vlassis, Branislav Kveton, Aditya Krishna Menon, Trung Bui, Scott Sanner:
Practical Linear Models for Large-Scale One-Class Collaborative Filtering. IJCAI 2016: 3854-3860 - [c49]Branislav Kveton, Hung Bui, Mohammad Ghavamzadeh, Georgios Theocharous, S. Muthukrishnan, Siqi Sun:
Graphical Model Sketch. ECML/PKDD (1) 2016: 81-97 - [c48]Viet Huynh, Dinh Q. Phung, Svetha Venkatesh, XuanLong Nguyen, Matthew D. Hoffman, Hung Hai Bui:
Scalable Nonparametric Bayesian Multilevel Clustering. UAI 2016 - [i11]Branislav Kveton, Hung Bui, Mohammad Ghavamzadeh, Georgios Theocharous, S. Muthukrishnan, Siqi Sun:
Graphical Model Sketch. CoRR abs/1602.03105 (2016) - [i10]Rui Shu, Hung Hai Bui, Mohammad Ghavamzadeh:
Bottleneck Conditional Density Estimation. CoRR abs/1611.08568 (2016) - 2015
- [j13]Christopher W. Geib, Vikas Agrawal, Gita Sukthankar, Lokendra Shastri, Hung Bui:
Architectures for Activity Recognition and Context-Aware Computing. AI Mag. 36(2): 3-9 (2015) - [c47]Jaya Kawale, Hung Hai Bui, Branislav Kveton, Long Tran-Thanh, Sanjay Chawla:
Efficient Thompson Sampling for Online Matrix-Factorization Recommendation. NIPS 2015: 1297-1305 - [c46]Vu Nguyen, Dinh Q. Phung, Svetha Venkatesh, Hung Hai Bui:
A Bayesian Nonparametric Approach to Multilevel Regression. PAKDD (1) 2015: 330-342 - [c45]Viet Huynh, Dinh Q. Phung, XuanLong Nguyen, Svetha Venkatesh, Hung Hai Bui:
Learning Conditional Latent Structures from Multiple Data Sources. PAKDD (1) 2015: 343-354 - 2014
- [c44]Tien-Vu Nguyen, Dinh Quoc Phung, XuanLong Nguyen, Svetha Venkatesh, Hung Bui:
Bayesian Nonparametric Multilevel Clustering with Group-Level Contexts. ICML 2014: 288-296 - [c43]Hung Hai Bui, Tuyen N. Huynh, David A. Sontag:
Lifted Tree-Reweighted Variational Inference. UAI 2014: 92-101 - [i9]Vu Nguyen, Dinh Q. Phung, XuanLong Nguyen, Svetha Venkatesh, Hung Hai Bui:
Bayesian Nonparametric Multilevel Clustering with Group-Level Contexts. CoRR abs/1401.1974 (2014) - [i8]Hung Hai Bui, Tuyen N. Huynh, David A. Sontag:
Lifted Tree-Reweighted Variational Inference. CoRR abs/1406.4200 (2014) - [i7]Truyen Tran, Dinh Q. Phung, Svetha Venkatesh, Hung Hai Bui:
MCMC for Hierarchical Semi-Markov Conditional Random Fields. CoRR abs/1408.1162 (2014) - [i6]Tran The Truyen, Hung Bui, Svetha Venkatesh:
Boosted Markov Networks for Activity Recognition. CoRR abs/1408.1167 (2014) - [i5]Tran The Truyen, Hung Bui, Svetha Venkatesh:
Human Activity Learning and Segmentation using Partially Hidden Discriminative Models. CoRR abs/1408.3081 (2014) - 2013
- [j12]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:
The AAAI-13 Conference Workshops. AI Mag. 34(4): 9- (2013) - [c42]Hung Hai Bui:
Organizers. AAAI Workshop: Plan, Activity, and Intent Recognition 2013 - [c41]Hung Bui, Tuyen N. Huynh, Sebastian Riedel:
Automorphism Groups of Graphical Models and Lifted Variational Inference. UAI 2013 - [i4]Hung Bui, Tuyen N. Huynh, Sebastian Riedel:
Automorphism Groups of Graphical Models and Lifted Variational Inference. CoRR abs/1309.6822 (2013) - 2012
- [c40]Hung Hai Bui, Tuyen N. Huynh, Rodrigo de Salvo Braz:
Exact Lifted Inference with Distinct Soft Evidence on Every Object. AAAI 2012: 1875-1881 - [c39]Rodrigo de Salvo Braz, Shahin Saadati, Hung Bui, Ciaran O'Reilly:
Lifted Arbitrary Constraint Solving for Lifted Probabilistic Inference. StarAI@UAI 2012 - [c38]Hung Hai Bui, Tuyen N. Huynh, Sebastian Riedel:
Automorphism Groups of Graphical Models and Lifted Variational Inference. StarAI@UAI 2012 - [c37]Richard G. Freedman, Rodrigo de Salvo Braz, Hung Bui, Sriraam Natarajan:
Initial Empirical Evaluation of Anytime Lifted Belief Propagation. StarAI@UAI 2012 - [i3]Hung Hai Bui, Tuyen N. Huynh, Sebastian Riedel:
Automorphism Groups of Graphical Models and Lifted Variational Inference. CoRR abs/1207.4814 (2012) - 2011
- [c36]Jaesik Choi, Rodrigo de Salvo Braz, Hung Hai Bui:
Efficient Methods for Lifted Inference with Aggregate Factors. AAAI 2011: 1030-1036 - [i2]Hung Hai Bui, Svetha Venkatesh, Geoff A. W. West:
Policy Recognition in the Abstract Hidden Markov Model. CoRR abs/1106.0672 (2011) - 2010
- [j11]Neil Yorke-Smith, Hung Hai Bui:
Efficient variable elimination for semi-structured simple temporal networks with continuous domains. Knowl. Eng. Rev. 25(3): 337-351 (2010) - [j10]Duc-Son Pham, Hung Hai Bui, Svetha Venkatesh:
Bayesian Minimax Estimation of the Normal Model With Incomplete Prior Covariance Matrix Specification. IEEE Trans. Inf. Theory 56(12): 6433-6449 (2010) - [i1]Tran The Truyen, Dinh Q. Phung, Hung Hai Bui, Svetha Venkatesh:
Hierarchical Semi-Markov Conditional Random Fields for Recursive Sequential Data. CoRR abs/1009.2009 (2010)
2000 – 2009
- 2009
- [j9]Thi V. Duong, Dinh Q. Phung, Hung Bui, Svetha Venkatesh:
Efficient duration and hierarchical modeling for human activity recognition. Artif. Intell. 173(7-8): 830-856 (2009) - [c35]Omid Madani, Hung Bui, Eric Yeh:
Prediction and Discovery of Users' Desktop Behavior. AAAI Spring Symposium: Human Behavior Modeling 2009: 49-55 - [c34]Omid Madani, Hung Bui, Eric Yeh:
Efficient Online Learning and Prediction of Users' Desktop Actions. IJCAI 2009: 1457-1462 - [c33]Rodrigo de Salvo Braz, Sriraam Natarajan, Hung Bui, Jude W. Shavlik, Stuart Russell:
Anytime Lifted Belief Propagation. MLG/SRL@ILP 2009 - 2008
- [c32]Hung Hai Bui, Dinh Q. Phung, Svetha Venkatesh, Hai Phan:
The Hidden Permutation Model and Location-Based Activity Recognition. AAAI 2008: 1345-1350 - [c31]Hung Hai Bui, Federico Cesari, Daniel Elenius, David N. Morley, Sriraam Natarajan, Shahin Saadati, Eric Yeh, Neil Yorke-Smith:
A context-aware personal desktop assistant. AAMAS (Demos) 2008: 1679-1680 - [c30]Sriraam Natarajan, Hung Hai Bui, Prasad Tadepalli, Kristian Kersting, Weng-Keen Wong:
Logical Hierarchical Hidden Markov Models for Modeling User Activities. ILP 2008: 192-209 - [c29]Tran The Truyen, Dinh Q. Phung, Hung Bui, Svetha Venkatesh:
Hierarchical Semi-Markov Conditional Random Fields for Recursive Sequential Data. NIPS 2008: 1657-1664 - [c28]Tran The Truyen, Hung Hai Bui, Dinh Q. Phung, Svetha Venkatesh:
Learning Discriminative Sequence Models from Partially Labelled Data for Activity Recognition. PRICAI 2008: 903-912 - [c27]Christopher I. Connolly, J. Brian Burns, Hung Hai Bui:
Recovering Social Networks From Massive Track Datasets. WACV 2008: 1-8 - 2006
- [c26]Nam Thanh Nguyen, Svetha Venkatesh, Hung Bui:
Recognising Behaviours of Multiple People with Hierarchical Probabilistic Model and Statistical Data Association. BMVC 2006: 1239-1248 - [c25]Tran The Truyen, Dinh Q. Phung, Svetha Venkatesh, Hung Hai Bui:
AdaBoost.MRF: Boosted Markov Random Forests and Application to Multilevel Activity Recognition. CVPR (2) 2006: 1686-1693 - [c24]Thi V. Duong, Dinh Q. Phung, Hung Hai Bui, Svetha Venkatesh:
Human Behavior Recognition with Generic Exponential Family Duration Modeling in the Hidden Semi-Markov Model. ICPR (3) 2006: 202-207 - 2005
- [j8]Patrick Peursum, Hung Hai Bui, Svetha Venkatesh, Geoff A. W. West:
Robust Recognition and Segmentation of Human Actions Using HMMs with Missing Observations. EURASIP J. Adv. Signal Process. 2005(13): 2110-2126 (2005) - [j7]Brett Adams, Svetha Venkatesh, Hung Hai Bui, Chitra Dorai:
A Probabilistic Framework for Extracting Narrative Act Boundaries and Semantics in Motion Pictures. Multim. Tools Appl. 27(2): 195-213 (2005) - [c23]Thi V. Duong, Hung Hai Bui, Dinh Q. Phung, Svetha Venkatesh:
Activity Recognition and Abnormality Detection with the Switching Hidden Semi-Markov Model. CVPR (1) 2005: 838-845 - [c22]Nam Thanh Nguyen, Dinh Q. Phung, Svetha Venkatesh, Hung Bui:
Learning and Detecting Activities from Movement Trajectories Using the Hierarchical Hidden Markov Models. CVPR (2) 2005: 955-960 - [c21]Dinh Q. Phung, Thi V. Duong, Svetha Venkatesh, Hung Hai Bui:
Topic transition detection using hierarchical hidden Markov and semi-Markov models. ACM Multimedia 2005: 11-20 - 2004
- [j6]Mihai M. Lazarescu, Svetha Venkatesh, Hung Hai Bui:
Using multiple windows to track concept drift. Intell. Data Anal. 8(1): 29-59 (2004) - [j5]Patrick Peursum, Svetha Venkatesh, Geoff A. W. West, Hung Hai Bui:
Using Interaction Signatures to Find and Label Chairs and Floors. IEEE Pervasive Comput. 3(4): 58-65 (2004) - [c20]Hung Hai Bui, Dinh Q. Phung, Svetha Venkatesh:
Learning Hierarchical Hidden Markov Models with General State Hierarchy. AAAI 2004: 324-329 - [c19]Dinh Q. Phung, Svetha Venkatesh, Hung Hai Bui:
Automatically learning structural units in educational videos with the hierarchical hidden markov models. ICIP 2004: 1605-1608 - [c18]Patrick Peursum, Hung Hai Bui, Svetha Venkatesh, Geoff A. W. West:
Human Action Segmentation via Controlled Use of Missing Data in HMMs. ICPR (4) 2004: 440-445 - [c17]Graeme S. Chambers, Svetha Venkatesh, Geoff A. W. West, Hung Hai Bui:
Segmentation of Intentional Human Gestures for Sports Video Annotation. MMM 2004: 124-129 - [c16]Patrick Peursum, Hung Hai Bui, Svetha Venkatesh, Geoff A. W. West:
Classifying Human Actions Using an Incomplete Real-Time Pose Skeleton. PRICAI 2004: 971-972 - [c15]Sebastian Lühr, Svetha Venkatesh, Geoff A. W. West, Hung Hai Bui:
Explicit State Duration HMM for Abnormality Detection in Sequences of Human Activity. PRICAI 2004: 983-984 - [c14]Nam Thanh Nguyen, Svetha Venkatesh, Geoff A. W. West, Hung Hai Bui:
Learning People Movement Model from Multiple Cameras for Behaviour Recognition. SSPR/SPR 2004: 315-324 - [c13]Dinh Q. Phung, Hung Hai Bui, Svetha Venkatesh:
Content Structure Discovery in Educational Videos Using Shared Structures in the Hierarchical Hidden Markov Models. SSPR/SPR 2004: 1155-1163 - 2003
- [c12]Nam Thanh Nguyen, Hung Hai Bui, Svetha Venkatesh, Geoff A. W. West:
Recognising and Monitoring High-Level Behaviours in Complex Spatial Environments. CVPR (2) 2003: 620-625 - [c11]Brett Adams, Chitra Dorai, Svetha Venkatesh, Hung Hai Bui:
Indexing narrative structure and semantics in motion pictures with a probabilistic framework. ICME 2003: 453-456 - [c10]Hung Hai Bui:
A General Model for Online Probabilistic Plan Recognition. IJCAI 2003: 1309-1318 - [c9]Patrick Peursum, Svetha Venkatesh, Geoff A. W. West, Hung Hai Bui:
Object Labelling from Human Action Recognition. PerCom 2003: 399-406 - [c8]Sebastian Lühr, Hung Hai Bui, Svetha Venkatesh, Geoff A. W. West:
Recognition of Human Activity through Hierarchical Stochastic Learning. PerCom 2003: 416- - 2002
- [j4]Hung Hai Bui, Svetha Venkatesh, Geoff A. W. West:
Policy Recognition in the Abstract Hidden Markov Model. J. Artif. Intell. Res. 17: 451-499 (2002) - [c7]Nam Thanh Nguyen, Svetha Venkatesh, Geoff A. W. West, Hung Hai Bui:
Hierarchical Monitoring of People's Behaviors in Complex Environments Using Multiple Cameras. ICPR (1) 2002: 13-16 - [c6]Graeme S. Chambers, Svetha Venkatesh, Geoff A. W. West, Hung Hai Bui:
Hierarchical Recognition of Intentional Human Gestures for Sports Video Annotation. ICPR (2) 2002: 1082-1085 - 2001
- [j3]Hung Hai Bui, Svetha Venkatesh, Geoff A. W. West:
Tracking and Surveillance in Wide-Area Spatial Environments Using the Abstract Hidden Markov Model. Int. J. Pattern Recognit. Artif. Intell. 15(1): 177-195 (2001) - 2000
- [c5]Hung Hai Bui, Svetha Venkatesh, Geoff A. W. West:
On the Recognition of Abstract Markov Policies. AAAI/IAAI 2000: 524-530 - [c4]Hung Hai Bui, Svetha Venkatesh, Geoff A. W. West:
A Probabilistic Framework for Tracking in Wide-Area Environments. ICPR 2000: 4702-4705
1990 – 1999
- 1999
- [j2]Hung Hai Bui, Svetha Venkatesh, Geoff A. W. West:
Layered dynamic probabilistic networks for spatio-temporal modelling. Intell. Data Anal. 3(5): 339-361 (1999) - [j1]Hung Hai Bui, Svetha Venkatesh, Dorota H. Kieronska:
Learning Other Agents' Preferences in Multi-Agent Negotiation Using the Bayesian Classifier. Int. J. Cooperative Inf. Syst. 8(4): 275-294 (1999) - 1997
- [c3]Hung Hai Bui, Dorota H. Kieronska, Svetha Venkatesh:
Optimal Communication Among Team Members. Australian Joint Conference on Artificial Intelligence 1997: 116-126 - [c2]Hung Hai Bui, Svetha Venkatesh, Dorota H. Kieronska:
A Framework for Coordination and Learning among Teams of Agents. Agents and Multi-Agent Systems Formalisms, Methodologies, and Applications 1997: 164-178 - 1996
- [c1]Hung Hai Bui, Dorota H. Kieronska, Svetha Venkatesh:
Learning other Agents' Preferences in Multiagent Negotiation. AAAI/IAAI, Vol. 1 1996: 114-119
Coauthor Index
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