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2020 – today
- 2024
[c82]Shivakumar Mahesh, Anshuka Rangi, Haifeng Xu, Long Tran-Thanh:
Attacking Multi-Player Bandits and How to Robustify Them. AAMAS 2024: 1337-1345- [c81]Le Cong Dinh, David Henry Mguni, Long Tran-Thanh, Jun Wang, Yaodong Yang:
A Summary of Online Markov Decision Processes with Non-oblivious Strategic Adversary. AAMAS 2024: 2830-2832 - [c80]Minh Nguyen, Nghi Bui, Truong Son Hy, Long Tran-Thanh, Tien Nguyen:
HierarchyNet: Learning to Summarize Source Code with Heterogeneous Representations. EACL (Findings) 2024: 2355-2367 - [c79]Phurinut Srisawad, Juergen Branke, Long Tran-Thanh:
Identifying the Best Arm in the Presence of Global Environment Shifts. ECAI 2024: 2154-2161 - [c78]Long Tran-Thanh, Tran Cao Son, Dylan Flynn, Marcello Balduccini:
A Simulation for Supply Chains Contract Execution. LPNMR 2024: 331-344 - [i43]Nam Phuong Tran, The-Anh Ta, Shuqing Shi, Debmalya Mandal, Yali Du, Long Tran-Thanh:
Learning the Expected Core of Strictly Convex Stochastic Cooperative Games. CoRR abs/2402.07067 (2024) - [i42]Abhimanyu Pallavi Sudhir
, Long Tran-Thanh:
Betting on what is neither verifiable nor falsifiable. CoRR abs/2402.14021 (2024) - [i41]Nam Phuong Tran, The-Anh Ta, Debmalya Mandal, Long Tran-Thanh:
Symmetric Linear Bandits with Hidden Symmetry. CoRR abs/2405.13899 (2024) - [i40]Phurinut Srisawad, Juergen Branke, Long Tran-Thanh:
Identifying the Best Arm in the Presence of Global Environment Shifts. CoRR abs/2408.12581 (2024) - 2023
- [j11]Le Cong Dinh, David Henry Mguni, Long Tran-Thanh, Jun Wang, Yaodong Yang:
Online Markov decision processes with non-oblivious strategic adversary. Auton. Agents Multi Agent Syst. 37(1): 15 (2023) - [j10]Nhat Van-Quoc Truong, Le Cong Dinh, Sebastian Stein, Long Tran-Thanh, Nicholas R. Jennings:
Efficient and adaptive incentive selection for crowdsourcing contests. Appl. Intell. 53(8): 9204-9234 (2023) - [c77]Shivakumar Mahesh, Nicholas Bishop, Le Cong Dinh, Long Tran-Thanh:
Playing Repeated Coopetitive Polymatrix Games with Small Manipulation Cost. GameSec 2023: 257-276 - [c76]Hoang Pham, The-Anh Ta, Shiwei Liu, Lichuan Xiang, Dung Le, Hongkai Wen, Long Tran-Thanh:
Towards Data-Agnostic Pruning At Initialization: What Makes a Good Sparse Mask? NeurIPS 2023 - [c75]Nam Phuong Tran, Long Tran-Thanh:
Invariant Lipschitz Bandits: A Side Observation Approach. ECML/PKDD (4) 2023: 524-539 - [i39]Le Cong Dinh, Tri-Dung Nguyen, Alain B. Zemkoho, Long Tran-Thanh:
Achieving Better Regret against Strategic Adversaries. CoRR abs/2302.06652 (2023) - [i38]Viet Bach Nguyen, Truong Son-Hy, Long Tran-Thanh, Nhung Nghiem:
Predicting COVID-19 pandemic by spatio-temporal graph neural networks: A New Zealand's study. CoRR abs/2305.07731 (2023) - [i37]Mustafa Yasir, John Palowitch, Anton Tsitsulin, Long Tran-Thanh, Bryan Perozzi:
Examining the Effects of Degree Distribution and Homophily in Graph Learning Models. CoRR abs/2307.08881 (2023) - [i36]Khoi Do, Duong Nguyen, Hoa Nguyen, Long Tran-Thanh, Quoc-Viet Pham:
Revisiting LARS for Large Batch Training Generalization of Neural Networks. CoRR abs/2309.14053 (2023) - 2022
- [c74]Nicholas Bishop, Hau Chan, Debmalya Mandal, Long Tran-Thanh:
Sequential Blocked Matching. AAAI 2022: 4834-4842 - [c73]Anshuka Rangi, Long Tran-Thanh, Haifeng Xu, Massimo Franceschetti:
Saving Stochastic Bandits from Poisoning Attacks via Limited Data Verification. AAAI 2022: 8054-8061 - [c72]Minh-Hieu Phan, The-Anh Ta, Son Lam Phung, Long Tran-Thanh, Abdesselam Bouzerdoum:
Class Similarity Weighted Knowledge Distillation for Continual Semantic Segmentation. CVPR 2022: 16845-16854 - [c71]Truong Son Hy, Viet Bach Nguyen, Long Tran-Thanh, Risi Kondor:
Temporal Multiresolution Graph Neural Networks For Epidemic Prediction. Healthcare AI and COVID-19 Workshop 2022: 21-32 - [c70]Anshuka Rangi, Haifeng Xu, Long Tran-Thanh, Massimo Franceschetti:
Understanding the Limits of Poisoning Attacks in Episodic Reinforcement Learning. IJCAI 2022: 3394-3400 - [c69]Yichen Xiao, Han-Ching Ou, Haipeng Chen, Van Thieu Nguyen, Long Tran-Thanh:
Sequential Vaccine Allocation with Delayed Feedback. IJCAI 2022: 5199-5205 - [c68]Hung Tran-The, Sunil Gupta, Santu Rana, Tuan Truong, Long Tran-Thanh, Svetha Venkatesh:
Expected Improvement for Contextual Bandits. NeurIPS 2022 - [c67]Thai Le, Long Tran-Thanh, Dongwon Lee:
Socialbots on Fire: Modeling Adversarial Behaviors of Socialbots via Multi-Agent Hierarchical Reinforcement Learning. WWW 2022: 545-554 - [i35]Truong Son-Hy, Viet Bach Nguyen, Long Tran-Thanh, Risi Kondor:
Temporal Multiresolution Graph Neural Networks For Epidemic Prediction. CoRR abs/2205.14831 (2022) - [i34]Anshuka Rangi, Haifeng Xu, Long Tran-Thanh, Massimo Franceschetti:
Understanding the Limits of Poisoning Attacks in Episodic Reinforcement Learning. CoRR abs/2208.13663 (2022) - [i33]Minh-Duong Nguyen, Quoc-Viet Pham, Dinh Thai Hoang, Long Tran-Thanh, Diep N. Nguyen, Won-Joo Hwang:
Label driven Knowledge Distillation for Federated Learning with non-IID Data. CoRR abs/2209.14520 (2022) - [i32]Shivakumar Mahesh, Anshuka Rangi, Haifeng Xu, Long Tran-Thanh:
Multi-Player Bandits Robust to Adversarial Collisions. CoRR abs/2211.07817 (2022) - [i31]Nam Phuong Tran, The-Anh Ta, Long Tran-Thanh:
Invariant Lipschitz Bandits: A Side Observation Approach. CoRR abs/2212.07524 (2022) - 2021
- [j9]Andre P. Ortega, Sarvapali D. Ramchurn, Long Tran-Thanh, Geoff V. Merrett:
Partner selection in self-organised wireless sensor networks for opportunistic energy negotiation: A multi-armed bandit based approach. Ad Hoc Networks 112: 102354 (2021) - [j8]Mashrur Rashik, Md. Musfiqur Rahman, Md. Mosaddek Khan, Md. Mamun-Or-Rashid, Long Tran-Thanh, Nicholas R. Jennings:
Speeding up distributed pseudo-tree optimization procedures with cross edge consistency to solve DCOPs. Appl. Intell. 51(3): 1733-1746 (2021) - [c66]Le Cong Dinh, Tri-Dung Nguyen, Alain B. Zemkoho, Long Tran-Thanh:
Last Round Convergence and No-Dynamic Regret in Asymmetric Repeated Games. ALT 2021: 553-577 - [c65]Nicholas Bishop, Le Cong Dinh, Long Tran-Thanh:
How to Guide a Non-Cooperative Learner to Cooperate: Exploiting No-Regret Algorithms in System Design. AAMAS 2021: 1464-1466 - [i30]Anshuka Rangi, Massimo Franceschetti, Long Tran-Thanh:
Sequential Choice Bandits with Feedback for Personalizing users' experience. CoRR abs/2101.01572 (2021) - [i29]Anshuka Rangi, Long Tran-Thanh, Haifeng Xu, Massimo Franceschetti:
Secure-UCB: Saving Stochastic Bandits from Poisoning Attacks via Limited Data Verification. CoRR abs/2102.07711 (2021) - [i28]Lei Xun, Long Tran-Thanh, Bashir M. Al-Hashimi, Geoff V. Merrett:
Incremental Training and Group Convolution Pruning for Runtime DNN Performance Scaling on Heterogeneous Embedded Platforms. CoRR abs/2105.03600 (2021) - [i27]Lei Xun, Long Tran-Thanh, Bashir M. Al-Hashimi, Geoff V. Merrett:
Optimising Resource Management for Embedded Machine Learning. CoRR abs/2105.03608 (2021) - [i26]Nicholas Bishop, Hau Chan, Debmalya Mandal, Long Tran-Thanh:
Sequential Blocked Matching. CoRR abs/2108.00073 (2021) - [i25]Le Cong Dinh, David Henry Mguni, Long Tran-Thanh, Jun Wang, Yaodong Yang:
Online Markov Decision Processes with Non-oblivious Strategic Adversary. CoRR abs/2110.03604 (2021) - [i24]Thai Le, Long Tran-Thanh, Dongwon Lee:
Adversarial Socialbot Learning via Multi-Agent Deep Hierarchical Reinforcement Learning. CoRR abs/2110.10655 (2021) - [i23]Shivakumar Mahesh, Nicholas Bishop, Le Cong Dinh, Long Tran-Thanh:
Playing Repeated Coopetitive Polymatrix Games with Small Manipulation Cost. CoRR abs/2110.13532 (2021) - 2020
- [c64]Minming Li, Long Tran-Thanh, Xiaowei Wu:
Defending with Shared Resources on a Network. AAAI 2020: 2111-2118 - [c63]Dong Quan Vu, Patrick Loiseau, Alonso Silva, Long Tran-Thanh:
Path Planning Problems with Side Observations - When Colonels Play Hide-and-Seek. AAAI 2020: 2252-2259 - [c62]Steven Jecmen, Arunesh Sinha, Zun Li, Long Tran-Thanh:
Bounding Regret in Empirical Games. AAAI 2020: 4280-4287 - [c61]Saaduddin Mahmud, Moumita Choudhury, Md. Mosaddek Khan, Long Tran-Thanh, Nicholas R. Jennings:
AED: An Anytime Evolutionary DCOP Algorithm. AAMAS 2020: 825-833 - [c60]Guillermo Romero Moreno, Long Tran-Thanh, Markus Brede:
Continuous Influence Maximisation for the Voter Dynamics: Is Targeting High-Degree Nodes a Good Strategy? AAMAS 2020: 1981-1983 - [c59]Ronald Gualán, Víctor Saquicela, Long Tran-Thanh:
Comparison of classical and machine-learning methods on spatio-temporal modeling of daily Ozone concentrations. CLEI 2020: 56-65 - [c58]Lei Xun, Long Tran-Thanh, Bashir M. Al-Hashimi, Geoff V. Merrett:
Optimising Resource Management for Embedded Machine Learning. DATE 2020: 1556-1561 - [c57]Saaduddin Mahmud, Md. Mosaddek Khan, Moumita Choudhury, Long Tran-Thanh, Nicholas R. Jennings:
Learning Optimal Temperature Region for Solving Mixed Integer Functional DCOPs. IJCAI 2020: 268-275 - [c56]Hau Chan, Long Tran-Thanh, Vignesh Viswanathan:
Fighting Wildfires under Uncertainty - A Sequential Resource Allocation Approach. IJCAI 2020: 4322-4329 - [c55]Balint Gucsi, Danesh S. Tarapore, William Yeoh, Christopher Amato, Long Tran-Thanh:
To Ask or Not to Ask: A User Annoyance Aware Preference Elicitation Framework for Social Robots. IROS 2020: 7935-7940 - [c54]Nick Bishop, Hau Chan, Debmalya Mandal, Long Tran-Thanh:
Adversarial Blocking Bandits. NeurIPS 2020 - [c53]Nick Bishop, Long Tran-Thanh, Enrico H. Gerding:
Optimal Learning from Verified Training Data. NeurIPS 2020 - [i22]Saaduddin Mahmud, Md. Mosaddek Khan, Moumita Choudhury, Long Tran-Thanh, Nicholas R. Jennings:
Learning Optimal Temperature Region for Solving Mixed Integer Functional DCOPs. CoRR abs/2002.12001 (2020) - [i21]Le Cong Dinh, Long Tran-Thanh, Tri-Dung Nguyen, Alain B. Zemkoho:
Last Round Convergence and No-Instant Regret in Repeated Games with Asymmetric Information. CoRR abs/2003.11727 (2020) - [i20]Thomas O. M. Davies, Jack Aspinall, Bryan Wilder, Long Tran-Thanh:
Fuzzy c-Means Clustering for Persistence Diagrams. CoRR abs/2006.02796 (2020) - [i19]Le Cong Dinh, Nick Bishop, Long Tran-Thanh:
Exploiting No-Regret Algorithms in System Design. CoRR abs/2007.11172 (2020) - [i18]Guillermo Romero Moreno, Edoardo Manino, Long Tran-Thanh, Markus Brede:
Zealotry and Influence Maximization in the Voter Model: When to Target Zealots? CoRR abs/2008.10012 (2020)
2010 – 2019
- 2019
- [j7]Edoardo Manino, Long Tran-Thanh, Nicholas R. Jennings:
On the efficiency of data collection for multiple Naïve Bayes classifiers. Artif. Intell. 275: 356-378 (2019) - [c52]Youzhi Zhang, Qingyu Guo, Bo An, Long Tran-Thanh, Nicholas R. Jennings:
Optimal Interdiction of Urban Criminals with the Aid of Real-Time Information. AAAI 2019: 1262-1269 - [c51]Qingyu Guo, Jiarui Gan, Fei Fang, Long Tran-Thanh, Milind Tambe, Bo An:
On the Inducibility of Stackelberg Equilibrium for Security Games. AAAI 2019: 2020-2028 - [c50]Shahrzad Gholami, Amulya Yadav, Long Tran-Thanh, Bistra Dilkina, Milind Tambe:
Don't Put All Your Strategies in One Basket: Playing Green Security Games with Imperfect Prior Knowledge. AAMAS 2019: 395-403 - [c49]Guillermo Romero Moreno, Long Tran-Thanh, Markus Brede:
Shielding and Shadowing: A Tale of Two Strategies for Opinion Control in the Voting Dynamics. COMPLEX NETWORKS (1) 2019: 682-693 - [c48]Jiarui Gan, Haifeng Xu, Qingyu Guo, Long Tran-Thanh, Zinovi Rabinovich, Michael J. Wooldridge:
Imitative Follower Deception in Stackelberg Games. EC 2019: 639-657 - [c47]Taha D. Günes, Long Tran-Thanh, Timothy J. Norman:
Identifying vulnerabilities in trust and reputation systems. IJCAI 2019: 308-314 - [c46]Anshuka Rangi, Massimo Franceschetti, Long Tran-Thanh:
Unifying the Stochastic and the Adversarial Bandits with Knapsack. IJCAI 2019: 3311-3317 - [c45]The Anh Han, Long Tran-Thanh, Simon Lynch, Theodor Cimpeanu, Francisco C. Santos:
Promoting Cooperation through External Interference. ALIFE 2019: 331-332 - [c44]Jiarui Gan, Qingyu Guo, Long Tran-Thanh, Bo An, Michael J. Wooldridge:
Manipulating a Learning Defender and Ways to Counteract. NeurIPS 2019: 8272-8281 - [c43]Edoardo Manino, Long Tran-Thanh, Nicholas R. Jennings:
Streaming Bayesian Inference for Crowdsourced Classification. NeurIPS 2019: 12762-12772 - [c42]Nhat Van-Quoc Truong, Sebastian Stein, Long Tran-Thanh, Nicholas R. Jennings:
What Prize Is Right? How to Learn the Optimal Structure for Crowdsourcing Contests. PRICAI (1) 2019: 85-97 - [c41]Paolo Serafino, Carmine Ventre, Long Tran-Thanh, Jie Zhang, Bo An, Nick R. Jennings:
Social Cost Guarantees in Smart Route Guidance. PRICAI (2) 2019: 482-495 - [c40]Tin Leelavimolsilp, Viet Hung Nguyen, Sebastian Stein, Long Tran-Thanh:
Selfish Mining in Proof-of-Work Blockchain with Multiple Miners: An Empirical Evaluation. PRIMA 2019: 219-234 - [i17]Jiarui Gan, Haifeng Xu, Qingyu Guo, Long Tran-Thanh, Zinovi Rabinovich, Michael J. Wooldridge:
Imitative Follower Deception in Stackelberg Games. CoRR abs/1903.02917 (2019) - [i16]Tin Leelavimolsilp, Long Tran-Thanh, Sebastian Stein, Viet Hung Nguyen:
An Empirical Evaluation of Selfish Mining and Strategic Mining in Proof-of-Work Blockchain with Multiple Miners. CoRR abs/1905.06853 (2019) - [i15]Dong Quan Vu, Patrick Loiseau, Alonso Silva, Long Tran-Thanh:
Colonel Blotto Games and Hide-and-Seek Games as Path Planning Problems with Side Observations. CoRR abs/1905.11151 (2019) - [i14]Jiarui Gan, Qingyu Guo, Long Tran-Thanh, Bo An, Michael J. Wooldridge:
Manipulating a Learning Defender and Ways to Counteract. CoRR abs/1905.11759 (2019) - [i13]Paolo Serafino, Carmine Ventre, Long Tran-Thanh, Jie Zhang, Bo An, Nick R. Jennings:
Social Cost Guarantees in Smart Route Guidance. CoRR abs/1906.06617 (2019) - [i12]Saaduddin Mahmud, Moumita Choudhury, Md. Mosaddek Khan, Long Tran-Thanh, Nicholas R. Jennings:
AED: An Anytime Evolutionary DCOP Algorithm. CoRR abs/1909.06254 (2019) - [i11]Edoardo Manino, Long Tran-Thanh, Nicholas R. Jennings:
Streaming Bayesian Inference for Crowdsourced Classification. CoRR abs/1911.05712 (2019) - [i10]Minming Li, Long Tran-Thanh, Xiaowei Wu:
Defending with Shared Resources on a Network. CoRR abs/1911.08196 (2019) - 2018
- [j6]Md. Mosaddek Khan, Long Tran-Thanh, Sarvapali D. Ramchurn, Nicholas R. Jennings:
Speeding Up GDL-Based Message Passing Algorithms for Large-Scale DCOPs. Comput. J. 61(11): 1639-1666 (2018) - [c39]Hau Chan, Long Tran-Thanh, Bryan Wilder, Eric Rice, Phebe Vayanos, Milind Tambe:
Utilizing Housing Resources for Homeless Youth Through the Lens of Multiple Multi-Dimensional Knapsacks. AIES 2018: 41-47 - [c38]Taha D. Gunes, Long Tran-Thanh, Timothy J. Norman:
Strategic Attacks on Trust Models via Bandit Optimization. TRUST@AAMAS 2018: 87-95 - [c37]Aaron Schlenker, Omkar Thakoor, Haifeng Xu, Fei Fang, Milind Tambe, Long Tran-Thanh, Phebe Vayanos, Yevgeniy Vorobeychik:
Deceiving Cyber Adversaries: A Game Theoretic Approach. AAMAS 2018: 892-900 - [c36]Tiep Le, Atena M. Tabakhi, Long Tran-Thanh, William Yeoh, Tran Cao Son:
Preference Elicitation with Interdependency and User Bother Cost. AAMAS 2018: 1459-1467 - [c35]Md. Mosaddek Khan, Long Tran-Thanh, Nicholas R. Jennings:
A Generic Domain Pruning Technique for GDL-Based DCOP Algorithms in Cooperative Multi-Agent Systems. AAMAS 2018: 1595-1603 - [c34]Md. Mosaddek Khan, Long Tran-Thanh, William Yeoh, Nicholas R. Jennings:
A Near-Optimal Node-to-Agent Mapping Heuristic for GDL-Based DCOP Algorithms in Multi-Agent Systems. AAMAS 2018: 1604-1612 - [c33]Qingyu Guo, Jiarui Gan, Fei Fang, Long Tran-Thanh, Milind Tambe, Bo An:
Inducible Equilibrium for Security Games. AAMAS 2018: 1947-1949 - [c32]Nhat V. Q. Truong, Sebastian Stein, Long Tran-Thanh, Nicholas R. Jennings:
Adaptive Incentive Selection for Crowdsourcing Contests. AAMAS 2018: 2100-2102 - [c31]The Anh Han, Simon Lynch, Long Tran-Thanh, Francisco C. Santos:
Fostering Cooperation in Structured Populations Through Local and Global Interference Strategies. IJCAI 2018: 289-295 - [c30]Zheyuan Ryan Shi, Ziye Tang, Long Tran-Thanh, Rohit Singh, Fei Fang:
Designing the Game to Play: Optimizing Payoff Structure in Security Games. IJCAI 2018: 512-518 - [c29]Edoardo Manino, Long Tran-Thanh, Nicholas R. Jennings:
On the Efficiency of Data Collection for Crowdsourced Classification. IJCAI 2018: 1568-1575 - [i9]Tin Leelavimolsilp, Long Tran-Thanh, Sebastian Stein:
On the Preliminary Investigation of Selfish Mining Strategy with Multiple Selfish Miners. CoRR abs/1802.02218 (2018) - [i8]Zheyuan Ryan Shi, Ziye Tang, Long Tran-Thanh, Rohit Singh, Fei Fang:
Designing the Game to Play: Optimizing Payoff Structure in Security Games. CoRR abs/1805.01987 (2018) - [i7]Qingyu Guo, Jiarui Gan, Fei Fang, Long Tran-Thanh, Milind Tambe, Bo An:
On the Inducibility of Stackelberg Equilibrium for Security Games. CoRR abs/1811.03823 (2018) - [i6]Anshuka Rangi, Massimo Franceschetti, Long Tran-Thanh:
Unifying the stochastic and the adversarial Bandits with Knapsack. CoRR abs/1811.12253 (2018) - 2017
- [j5]Monica Anderson, Roman Barták, John S. Brownstein, David L. Buckeridge, Hoda Eldardiry, Christopher W. Geib, Maria L. Gini, Aaron Isaksen, Sarah Keren, Robert Laddaga, Viliam Lisý, Rodney Martin, David R. Martinez, Martin Michalowski, Loizos Michael, Reuth Mirsky, Thanh Hai Nguyen, Michael J. Paul, Enrico Pontelli, Scott Sanner, Arash Shaban-Nejad, Arunesh Sinha, Shirin Sohrabi, Kumar Sricharan, Biplav Srivastava, Mark Stefik, William W. Streilein, Nathan R. Sturtevant, Kartik Talamadupula, Michael Thielscher, Julian Togelius, Tran Cao Son, Long Tran-Thanh, Neal Wagner, Byron C. Wallace, Szymon Wilk, Jichen Zhu:
Reports of the Workshops of the Thirty-First AAAI Conference on Artificial Intelligence. AI Mag. 38(3): 72-82 (2017) - [c28]Marcin Waniek, Long Tran-Thanh, Tomasz P. Michalak, Nicholas R. Jennings:
The Dollar Auction with Spiteful Players. AAAI 2017: 736-742 - [c27]Taha D. Günes, Timothy J. Norman, Long Tran-Thanh:
Budget Limited Trust-Aware Decision Making. AAMAS Workshops (Visionary Papers) 2017: 101-110 - [c26]Qingyu Guo, Bo An, Long Tran-Thanh:
Playing Repeated Network Interdiction Games with Semi-Bandit Feedback. IJCAI 2017: 3682-3690 - [c25]Youzhi Zhang, Bo An, Long Tran-Thanh, Zhen Wang, Jiarui Gan, Nicholas R. Jennings:
Optimal Escape Interdiction on Transportation Networks. IJCAI 2017: 3936-3944 - 2016
- [c24]Haifeng Xu, Long Tran-Thanh, Nicholas R. Jennings:
Playing Repeated Security Games with No Prior Knowledge. AAMAS 2016: 104-112 - [c23]Qingyu Guo, Bo An, Yevgeniy Vorobeychik, Long Tran-Thanh, Jiarui Gan, Chunyan Miao:
Coalitional Security Games. AAMAS 2016: 159-167 - [c22]Marcin Waniek, Long Tran-Thanh, Tomasz P. Michalak:
Repeated Dollar Auctions: A Multi-Armed Bandit Approach. AAMAS 2016: 579-587 - [c21]Ngoc Cuong Truong, Tim Baarslag, Sarvapali D. Ramchurn, Long Tran-Thanh:
Interactive Scheduling of Appliance Usage in the Home. IJCAI 2016: 869-877 - [i5]Nhat V. Q. Truong, Sebastian Stein, Long Tran-Thanh, Nicholas R. Jennings:
Incentive Engineering Framework for Crowdsourcing Systems. CoRR abs/1609.01348 (2016) - [i4]Edoardo Manino, Long Tran-Thanh, Nicholas R. Jennings:
Efficiency of active learning for the allocation of workers on crowdsourced classification tasks. CoRR abs/1610.06106 (2016) - 2015
- [c20]Long Tran-Thanh, Trung Dong Huynh, Avi Rosenfeld, Sarvapali D. Ramchurn, Nicholas R. Jennings:
Crowdsourcing Complex Workflows under Budget Constraints. AAAI 2015: 1298-1304 - [c19]The Anh Han, Long Tran-Thanh, Nicholas R. Jennings:
The Cost of Interference in Evolving Multiagent Systems. AAMAS 2015: 1719-1720 - [c18]Long Tran-Thanh, Yingce Xia, Tao Qin, Nicholas R. Jennings:
Efficient Algorithms with Performance Guarantees for the Stochastic Multiple-Choice Knapsack Problem. IJCAI 2015: 403-410 - [c17]Jaya Kawale, Hung Hai Bui, Branislav Kveton, Long Tran-Thanh, Sanjay Chawla:
Efficient Thompson Sampling for Online Matrix-Factorization Recommendation. NIPS 2015: 1297-1305 - 2014
- [j4]Long Tran-Thanh, Sebastian Stein, Alex Rogers, Nicholas R. Jennings:
Efficient crowdsourcing of unknown experts using bounded multi-armed bandits. Artif. Intell. 214: 89-111 (2014) - [c16]Long Tran-Thanh, Trung Dong Huynh, Avi Rosenfeld, Sarvapali D. Ramchurn, Nicholas R. Jennings:
BudgetFix: budget limited crowdsourcing for interdependent task allocation with quality guarantees. AAMAS 2014: 477-484 - [c15]Victor Naroditskiy, Sebastian Stein, Mirco Tonin, Long Tran-Thanh, Michael Vlassopoulos, Nicholas R. Jennings:
Referral Incentives in Crowdfunding. HCOMP 2014: 171-183 - [c14]Long Tran-Thanh, Lampros C. Stavrogiannis, Victor Naroditskiy, Valentin Robu, Nicholas R. Jennings, Peter B. Key:
Efficient Regret Bounds for Online Bid Optimisation in Budget-Limited Sponsored Search Auctions. UAI 2014: 809-818 - [i3]Long Tran-Thanh, Jia Yuan Yu:
Functional Bandits. CoRR abs/1405.2432 (2014) - 2013
- [c13]Long Tran-Thanh, Matteo Venanzi, Alex Rogers, Nicholas R. Jennings:
Efficient budget allocation with accuracy guarantees for crowdsourcing classification tasks. AAMAS 2013: 901-908 - [c12]Ngoc Cuong Truong, Long Tran-Thanh, Enrico Costanza, Sarvapali D. Ramchurn:
Towards appliance usage prediction for home energy management. e-Energy 2013: 287-288 - [c11]Long Tran-Thanh, Tri-Dung Nguyen, Talal Rahwan, Alex Rogers, Nicholas R. Jennings:
An Efficient Vector-Based Representation for Coalitional Games. IJCAI 2013: 383-389 - [c10]Ngoc Cuong Truong, James McInerney, Long Tran-Thanh, Enrico Costanza, Sarvapali D. Ramchurn:
Forecasting Multi-Appliance Usage for Smart Home Energy Management. IJCAI 2013: 2908-2914 - [i2]Sasan Maleki, Long Tran-Thanh, Greg Hines, Talal Rahwan, Alex Rogers:
Bounding the Estimation Error of Sampling-based Shapley Value Approximation With/Without Stratifying. CoRR abs/1306.4265 (2013) - 2012
- [b1]Long Tran-Thanh:
Budget-limited multi-armed bandits. University of Southampton, UK, 2012 - [j3]Long Tran-Thanh, Alex Rogers, Nicholas R. Jennings:
Long-term information collection with energy harvesting wireless sensors: a multi-armed bandit based approach. Auton. Agents Multi Agent Syst. 25(2): 352-394 (2012) - [c9]Long Tran-Thanh, Archie C. Chapman, Alex Rogers, Nicholas R. Jennings:
Knapsack Based Optimal Policies for Budget-Limited Multi-Armed Bandits. AAAI 2012: 1134-1140 - [c8]Ruben Stranders, Long Tran-Thanh, Francesco Maria Delle Fave, Alex Rogers, Nicholas R. Jennings:
DCOPs and bandits: exploration and exploitation in decentralised coordination. AAMAS 2012: 289-296 - [c7]Long Tran-Thanh, Sebastian Stein, Alex Rogers, Nicholas R. Jennings:
Efficient Crowdsourcing of Unknown Experts using Multi-Armed Bandits. ECAI 2012: 768-773 - [i1]Long Tran-Thanh, Archie C. Chapman, Alex Rogers, Nicholas R. Jennings:
Knapsack based Optimal Policies for Budget-Limited Multi-Armed Bandits. CoRR abs/1204.1909 (2012) - 2011
- [c6]Long Tran-Thanh, Maria Polukarov, Archie C. Chapman, Alex Rogers, Nicholas R. Jennings:
On the Existence of Pure Strategy Nash Equilibria in Integer-Splittable Weighted Congestion Games. SAGT 2011: 236-253 - 2010
- [j2]Johnsen Kho, Long Tran-Thanh, Alex Rogers, Nicholas R. Jennings:
An Agent-Based Distributed Coordination Mechanism for Wireless Visual Sensor Nodes Using Dynamic Programming. Comput. J. 53(8): 1277-1290 (2010) - [j1]János Levendovszky, Long Tran-Thanh, Gergely Treplán, Gábor Kiss:
Fading-aware reliable and energy efficient routing in wireless sensor networks. Comput. Commun. 33(Supplement-1): S102-S109 (2010) - [c5]Long Tran-Thanh, Archie C. Chapman, Enrique Munoz de Cote, Alex Rogers, Nicholas R. Jennings:
Epsilon-First Policies for Budget-Limited Multi-Armed Bandits. AAAI 2010: 1211-1216 - [c4]Gábor Kiss, János Levendovszky, Sándor Molnár, Long Tran-Thanh:
Delay Characteristics and Server Update Optimization of Multiplayer Gaming in Mobile Environment. ICC 2010: 1-6 - [c3]Long Tran-Thanh, János Levendovszky:
Optimal Time Dependent Data Collection Schemes in Wireless Sensor Networks. WCNC 2010: 1-6
2000 – 2009
- 2009
- [c2]Johnsen Kho, Long Tran-Thanh, Alex Rogers, Nicholas R. Jennings:
Decentralised control of adaptive sampling and routing in wireless visual sensor networks. AAMAS (2) 2009: 1237-1238 - [c1]Long Tran-Thanh, János Levendovszky:
A novel reliability based routing protocol for power aware communications in wireless sensor networks. WCNC 2009: 2308-2313
Coauthor Index
Nicholas R. Jennings
aka: Nick R. Jennings
aka: Nick R. Jennings
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