Decentralised control of adaptive sampling and routing in wireless visual sensor networks. - Johnsen Kho; Long Tran-Thanh; Alex Rogers; Nicholas R. Jennings (AAMAS (2), 2009)

A novel reliability based routing protocol for power aware communications in wireless sensor networks. - Long Tran-Thanh; János Levendovszky (WCNC, 2009)

Epsilon-First Policies for Budget-Limited Multi-Armed Bandits. - Long Tran-Thanh; Archie C. Chapman; Enrique Munoz de Cote; Alex Rogers; Nicholas R. Jennings (AAAI, 2010)

Delay Characteristics and Server Update Optimization of Multiplayer Gaming in Mobile Environment. - Gábor Kiss; János Levendovszky; Sándor Molnár; Long Tran-Thanh (ICC, 2010)

Optimal Time Dependent Data Collection Schemes in Wireless Sensor Networks. - Long Tran-Thanh; János Levendovszky (WCNC, 2010)

An Agent-Based Distributed Coordination Mechanism for Wireless Visual Sensor Nodes Using Dynamic Programming. - Johnsen Kho; Long Tran-Thanh; Alex Rogers; Nicholas R. Jennings (Comput. J., 2010)

Fading-aware reliable and energy efficient routing in wireless sensor networks. - János Levendovszky; Long Tran-Thanh; Gergely Treplán; Gábor Kiss (Comput. Commun., 2010)

On the Existence of Pure Strategy Nash Equilibria in Integer-Splittable Weighted Congestion Games. - Long Tran-Thanh; Maria Polukarov; Archie C. Chapman; Alex Rogers; Nicholas R. Jennings (SAGT, 2011)

Knapsack Based Optimal Policies for Budget-Limited Multi-Armed Bandits. - Long Tran-Thanh; Archie C. Chapman; Alex Rogers; Nicholas R. Jennings (AAAI, 2012)

DCOPs and bandits: exploration and exploitation in decentralised coordination. - Ruben Stranders; Long Tran-Thanh; Francesco Maria Delle Fave; Alex Rogers; Nicholas R. Jennings (AAMAS, 2012)

Efficient Crowdsourcing of Unknown Experts using Multi-Armed Bandits. - Long Tran-Thanh; Sebastian Stein 001; Alex Rogers; Nicholas R. Jennings (ECAI, 2012)

Long-term information collection with energy harvesting wireless sensors: a multi-armed bandit based approach. - Long Tran-Thanh; Alex Rogers; Nicholas R. Jennings (Auton. Agents Multi Agent Syst., 2012)

Budget-limited multi-armed bandits. - Long Tran-Thanh (2012)

Efficient budget allocation with accuracy guarantees for crowdsourcing classification tasks. - Long Tran-Thanh; Matteo Venanzi; Alex Rogers; Nicholas R. Jennings (AAMAS, 2013)

Towards appliance usage prediction for home energy management. - Ngoc Cuong Truong; Long Tran-Thanh; Enrico Costanza; Sarvapali D. Ramchurn (e-Energy, 2013)

An Efficient Vector-Based Representation for Coalitional Games. - Long Tran-Thanh; Tri-Dung Nguyen; Talal Rahwan; Alex Rogers; Nicholas R. Jennings (IJCAI, 2013)

Forecasting Multi-Appliance Usage for Smart Home Energy Management. - Ngoc Cuong Truong; James McInerney; Long Tran-Thanh; Enrico Costanza; Sarvapali D. Ramchurn (IJCAI, 2013)

Bounding the Estimation Error of Sampling-based Shapley Value Approximation With/Without Stratifying. - Sasan Maleki; Long Tran-Thanh; Greg Hines; Talal Rahwan; Alex Rogers (CoRR, 2013)

BudgetFix: budget limited crowdsourcing for interdependent task allocation with quality guarantees. - Long Tran-Thanh; Trung Dong Huynh; Avi Rosenfeld; Sarvapali D. Ramchurn; Nicholas R. Jennings (AAMAS, 2014)

Referral Incentives in Crowdfunding. - Victor Naroditskiy; Sebastian Stein 001; Mirco Tonin; Long Tran-Thanh; Michael Vlassopoulos; Nicholas R. Jennings (HCOMP, 2014)

Efficient Regret Bounds for Online Bid Optimisation in Budget-Limited Sponsored Search Auctions. - Long Tran-Thanh; Lampros C. Stavrogiannis; Victor Naroditskiy; Valentin Robu; Nicholas R. Jennings; Peter B. Key (UAI, 2014)

Efficient crowdsourcing of unknown experts using bounded multi-armed bandits. - Long Tran-Thanh; Sebastian Stein 001; Alex Rogers; Nicholas R. Jennings (Artif. Intell., 2014)

Functional Bandits. - Long Tran-Thanh; Jia Yuan Yu (CoRR, 2014)

Crowdsourcing Complex Workflows under Budget Constraints. - Long Tran-Thanh; Trung Dong Huynh; Avi Rosenfeld; Sarvapali D. Ramchurn; Nicholas R. Jennings (AAAI, 2015)

The Cost of Interference in Evolving Multiagent Systems. - The Anh Han; Long Tran-Thanh; Nicholas R. Jennings (AAMAS, 2015)

Efficient Algorithms with Performance Guarantees for the Stochastic Multiple-Choice Knapsack Problem. - Long Tran-Thanh; Yingce Xia; Tao Qin 001; Nicholas R. Jennings (IJCAI, 2015)

Efficient Thompson Sampling for Online Matrix-Factorization Recommendation. - Jaya Kawale; Hung Hai Bui; Branislav Kveton; Long Tran-Thanh; Sanjay Chawla (NIPS, 2015)

Coalitional Security Games. - Qingyu Guo; Bo An 001; Yevgeniy Vorobeychik; Long Tran-Thanh; Jiarui Gan; Chunyan Miao (AAMAS, 2016)

Repeated Dollar Auctions: A Multi-Armed Bandit Approach. - Marcin Waniek; Long Tran-Thanh; Tomasz P. Michalak (AAMAS, 2016)

Playing Repeated Security Games with No Prior Knowledge. - Haifeng Xu; Long Tran-Thanh; Nicholas R. Jennings (AAMAS, 2016)

Interactive Scheduling of Appliance Usage in the Home. - Ngoc Cuong Truong; Tim Baarslag; Sarvapali D. Ramchurn; Long Tran-Thanh (IJCAI, 2016)

Efficiency of active learning for the allocation of workers on crowdsourced classification tasks. - Edoardo Manino; Long Tran-Thanh; Nicholas R. Jennings (CoRR, 2016)

Incentive Engineering Framework for Crowdsourcing Systems. - Nhat V. Q. Truong; Sebastian Stein 001; Long Tran-Thanh; Nicholas R. Jennings (CoRR, 2016)

The Dollar Auction with Spiteful Players. - Marcin Waniek; Long Tran-Thanh; Tomasz P. Michalak; Nicholas R. Jennings (AAAI, 2017)

Budget Limited Trust-Aware Decision Making. - Taha D. Günes; Timothy J. Norman; Long Tran-Thanh (AAMAS Workshops (Visionary Papers), 2017)

Playing Repeated Network Interdiction Games with Semi-Bandit Feedback. - Qingyu Guo; Bo An 001; Long Tran-Thanh (IJCAI, 2017)

Optimal Escape Interdiction on Transportation Networks. - Youzhi Zhang 001; Bo An 001; Long Tran-Thanh; Zhen Wang; Jiarui Gan; Nicholas R. Jennings (IJCAI, 2017)

Reports of the Workshops of the Thirty-First AAAI Conference on Artificial Intelligence. - Monica Anderson 001; 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; et al. (AI Mag., 2017)

Utilizing Housing Resources for Homeless Youth Through the Lens of Multiple Multi-Dimensional Knapsacks. - Hau Chan; Long Tran-Thanh; Bryan Wilder; Eric Rice; Phebe Vayanos; Milind Tambe (AIES, 2018)

Strategic Attacks on Trust Models via Bandit Optimization. - Taha D. Gunes; Long Tran-Thanh; Timothy J. Norman (TRUST@AAMAS, 2018)

Inducible Equilibrium for Security Games. - Qingyu Guo; Jiarui Gan; Fei Fang 001; Long Tran-Thanh; Milind Tambe; Bo An 001 (AAMAS, 2018)

A Generic Domain Pruning Technique for GDL-Based DCOP Algorithms in Cooperative Multi-Agent Systems. - Md. Mosaddek Khan; Long Tran-Thanh; Nicholas R. Jennings (AAMAS, 2018)

A Near-Optimal Node-to-Agent Mapping Heuristic for GDL-Based DCOP Algorithms in Multi-Agent Systems. - Md. Mosaddek Khan; Long Tran-Thanh; William Yeoh 001; Nicholas R. Jennings (AAMAS, 2018)

Preference Elicitation with Interdependency and User Bother Cost. - Tiep Le; Atena M. Tabakhi; Long Tran-Thanh; William Yeoh 001; Tran Cao Son (AAMAS, 2018)

Deceiving Cyber Adversaries: A Game Theoretic Approach. - Aaron Schlenker; Omkar Thakoor; Haifeng Xu; Fei Fang 001; Milind Tambe; Long Tran-Thanh; Phebe Vayanos; Yevgeniy Vorobeychik (AAMAS, 2018)

Adaptive Incentive Selection for Crowdsourcing Contests. - Nhat V. Q. Truong; Sebastian Stein 001; Long Tran-Thanh; Nicholas R. Jennings (AAMAS, 2018)

Fostering Cooperation in Structured Populations Through Local and Global Interference Strategies. - The Anh Han; Simon Lynch; Long Tran-Thanh; Francisco C. Santos (IJCAI, 2018)

On the Efficiency of Data Collection for Crowdsourced Classification. - Edoardo Manino; Long Tran-Thanh; Nicholas R. Jennings (IJCAI, 2018)

Designing the Game to Play: Optimizing Payoff Structure in Security Games. - Zheyuan Ryan Shi; Ziye Tang; Long Tran-Thanh; Rohit Singh; Fei Fang 001 (IJCAI, 2018)

Speeding Up GDL-Based Message Passing Algorithms for Large-Scale DCOPs. - Md. Mosaddek Khan; Long Tran-Thanh; Sarvapali D. Ramchurn; Nicholas R. Jennings (Comput. J., 2018)

On the Preliminary Investigation of Selfish Mining Strategy with Multiple Selfish Miners. - Tin Leelavimolsilp; Long Tran-Thanh; Sebastian Stein 001 (CoRR, 2018)

On the Inducibility of Stackelberg Equilibrium for Security Games. - Qingyu Guo; Jiarui Gan; Fei Fang 001; Long Tran-Thanh; Milind Tambe; Bo An 001 (AAAI, 2019)

Optimal Interdiction of Urban Criminals with the Aid of Real-Time Information. - Youzhi Zhang 001; Qingyu Guo; Bo An 001; Long Tran-Thanh; Nicholas R. Jennings (AAAI, 2019)

Don't Put All Your Strategies in One Basket: Playing Green Security Games with Imperfect Prior Knowledge. - Shahrzad Gholami; Amulya Yadav; Long Tran-Thanh; Bistra Dilkina; Milind Tambe (AAMAS, 2019)

Shielding and Shadowing: A Tale of Two Strategies for Opinion Control in the Voting Dynamics. - Guillermo Romero Moreno; Long Tran-Thanh; Markus Brede (COMPLEX NETWORKS (1), 2019)

Imitative Follower Deception in Stackelberg Games. - Jiarui Gan; Haifeng Xu; Qingyu Guo; Long Tran-Thanh; Zinovi Rabinovich; Michael J. Wooldridge (EC, 2019)

Identifying vulnerabilities in trust and reputation systems. - Taha D. Günes; Long Tran-Thanh; Timothy J. Norman (IJCAI, 2019)

Unifying the Stochastic and the Adversarial Bandits with Knapsack. - Anshuka Rangi; Massimo Franceschetti; Long Tran-Thanh (IJCAI, 2019)

Promoting Cooperation through External Interference. - The Anh Han; Long Tran-Thanh; Simon Lynch; Theodor Cimpeanu; Francisco C. Santos (ALIFE, 2019)

Manipulating a Learning Defender and Ways to Counteract. - Jiarui Gan; Qingyu Guo; Long Tran-Thanh; Bo An 001; Michael J. Wooldridge (NeurIPS, 2019)

Streaming Bayesian Inference for Crowdsourced Classification. - Edoardo Manino; Long Tran-Thanh; Nicholas R. Jennings (NeurIPS, 2019)

Social Cost Guarantees in Smart Route Guidance. - Paolo Serafino; Carmine Ventre; Long Tran-Thanh; Jie Zhang 008; Bo An 001; Nick R. Jennings (PRICAI (2), 2019)

What Prize Is Right? How to Learn the Optimal Structure for Crowdsourcing Contests. - Nhat Van-Quoc Truong; Sebastian Stein 001; Long Tran-Thanh; Nicholas R. Jennings (PRICAI (1), 2019)

Selfish Mining in Proof-of-Work Blockchain with Multiple Miners: An Empirical Evaluation. - Tin Leelavimolsilp; Viet Hung Nguyen; Sebastian Stein 001; Long Tran-Thanh (PRIMA, 2019)

On the efficiency of data collection for multiple Naïve Bayes classifiers. - Edoardo Manino; Long Tran-Thanh; Nicholas R. Jennings (Artif. Intell., 2019)

An Empirical Evaluation of Selfish Mining and Strategic Mining in Proof-of-Work Blockchain with Multiple Miners. - Tin Leelavimolsilp; Long Tran-Thanh; Sebastian Stein 001; Viet Hung Nguyen (CoRR, 2019)

Colonel Blotto Games and Hide-and-Seek Games as Path Planning Problems with Side Observations. - Dong Quan Vu; Patrick Loiseau; Alonso Silva; Long Tran-Thanh (CoRR, 2019)

Bounding Regret in Empirical Games. - Steven Jecmen; Arunesh Sinha; Zun Li 002; Long Tran-Thanh (AAAI, 2020)

Defending with Shared Resources on a Network. - Minming Li; Long Tran-Thanh; Xiaowei Wu 001 (AAAI, 2020)

Path Planning Problems with Side Observations - When Colonels Play Hide-and-Seek. - Dong Quan Vu; Patrick Loiseau; Alonso Silva; Long Tran-Thanh (AAAI, 2020)

AED: An Anytime Evolutionary DCOP Algorithm. - Saaduddin Mahmud; Moumita Choudhury; Md. Mosaddek Khan; Long Tran-Thanh; Nicholas R. Jennings (AAMAS, 2020)

Continuous Influence Maximisation for the Voter Dynamics: Is Targeting High-Degree Nodes a Good Strategy? - Guillermo Romero Moreno; Long Tran-Thanh; Markus Brede (AAMAS, 2020)

Comparison of classical and machine-learning methods on spatio-temporal modeling of daily Ozone concentrations. - Ronald Gualán; Víctor Saquicela; Long Tran-Thanh (CLEI, 2020)

Optimising Resource Management for Embedded Machine Learning. - Lei Xun; Long Tran-Thanh; Bashir M. Al-Hashimi; Geoff V. Merrett (DATE, 2020)

Fighting Wildfires under Uncertainty - A Sequential Resource Allocation Approach. - Hau Chan; Long Tran-Thanh; Vignesh Viswanathan (IJCAI, 2020)

Learning Optimal Temperature Region for Solving Mixed Integer Functional DCOPs. - Saaduddin Mahmud; Md. Mosaddek Khan; Moumita Choudhury; Long Tran-Thanh; Nicholas R. Jennings (IJCAI, 2020)

To Ask or Not to Ask: A User Annoyance Aware Preference Elicitation Framework for Social Robots. - Balint Gucsi; Danesh S. Tarapore; William Yeoh 001; Christopher Amato; Long Tran-Thanh (IROS, 2020)

Adversarial Blocking Bandits. - Nick Bishop; Hau Chan; Debmalya Mandal; Long Tran-Thanh (NeurIPS, 2020)

Optimal Learning from Verified Training Data. - Nick Bishop; Long Tran-Thanh; Enrico H. Gerding (NeurIPS, 2020)

Last Round Convergence and No-Instant Regret in Repeated Games with Asymmetric Information. - Le Cong Dinh; Long Tran-Thanh; Tri-Dung Nguyen; Alain B. Zemkoho (CoRR, 2020)

Fuzzy c-Means Clustering for Persistence Diagrams. - Thomas O. M. Davies; Jack Aspinall; Bryan Wilder; Long Tran-Thanh (CoRR, 2020)

Exploiting No-Regret Algorithms in System Design. - Le Cong Dinh; Nick Bishop; Long Tran-Thanh (CoRR, 2020)

Zealotry and Influence Maximization in the Voter Model: When to Target Zealots? - Guillermo Romero Moreno; Edoardo Manino; Long Tran-Thanh; Markus Brede (CoRR, 2020)

Last Round Convergence and No-Dynamic Regret in Asymmetric Repeated Games. - Le Cong Dinh; Tri-Dung Nguyen; Alain B. Zemkoho; Long Tran-Thanh (ALT, 2021)

How to Guide a Non-Cooperative Learner to Cooperate: Exploiting No-Regret Algorithms in System Design. - Nicholas Bishop; Le Cong Dinh; Long Tran-Thanh (AAMAS, 2021)

Partner selection in self-organised wireless sensor networks for opportunistic energy negotiation: A multi-armed bandit based approach. - Andre P. Ortega; Sarvapali D. Ramchurn; Long Tran-Thanh; Geoff V. Merrett (Ad Hoc Networks, 2021)

Speeding up distributed pseudo-tree optimization procedures with cross edge consistency to solve DCOPs. - Mashrur Rashik; Md. Musfiqur Rahman; Md. Mosaddek Khan; Md. Mamun-Or-Rashid; Long Tran-Thanh; Nicholas R. Jennings (Appl. Intell., 2021)

Sequential Choice Bandits with Feedback for Personalizing users' experience. - Anshuka Rangi; Massimo Franceschetti; Long Tran-Thanh (CoRR, 2021)

Secure-UCB: Saving Stochastic Bandits from Poisoning Attacks via Limited Data Verification. - Anshuka Rangi; Long Tran-Thanh; Haifeng Xu; Massimo Franceschetti (CoRR, 2021)

Incremental Training and Group Convolution Pruning for Runtime DNN Performance Scaling on Heterogeneous Embedded Platforms. - Lei Xun; Long Tran-Thanh; Bashir M. Al-Hashimi; Geoff V. Merrett (CoRR, 2021)

Adversarial Socialbot Learning via Multi-Agent Deep Hierarchical Reinforcement Learning. - Thai Le; Long Tran-Thanh; Dongwon Lee 001 (CoRR, 2021)

Sequential Blocked Matching. - Nicholas Bishop; Hau Chan; Debmalya Mandal; Long Tran-Thanh (AAAI, 2022)

Saving Stochastic Bandits from Poisoning Attacks via Limited Data Verification. - Anshuka Rangi; Long Tran-Thanh; Haifeng Xu; Massimo Franceschetti (AAAI, 2022)

Class Similarity Weighted Knowledge Distillation for Continual Semantic Segmentation. - Minh-Hieu Phan; The-Anh Ta; Son Lam Phung; Long Tran-Thanh; Abdesselam Bouzerdoum (CVPR, 2022)

Temporal Multiresolution Graph Neural Networks For Epidemic Prediction. - Truong Son Hy; Viet Bach Nguyen; Long Tran-Thanh; Risi Kondor (Healthcare AI and COVID-19 Workshop, 2022)

Understanding the Limits of Poisoning Attacks in Episodic Reinforcement Learning. - Anshuka Rangi; Haifeng Xu; Long Tran-Thanh; Massimo Franceschetti (IJCAI, 2022)

Sequential Vaccine Allocation with Delayed Feedback. - Yichen Xiao; Han-Ching Ou; Haipeng Chen 001; Van Thieu Nguyen; Long Tran-Thanh (IJCAI, 2022)

Expected Improvement for Contextual Bandits. - Hung Tran-The; Sunil Gupta 001; Santu Rana; Tuan Truong; Long Tran-Thanh; Svetha Venkatesh (NeurIPS, 2022)

Socialbots on Fire: Modeling Adversarial Behaviors of Socialbots via Multi-Agent Hierarchical Reinforcement Learning. - Thai Le; Long Tran-Thanh; Dongwon Lee 001 (WWW, 2022)

Label driven Knowledge Distillation for Federated Learning with non-IID Data. - Minh-Duong Nguyen; Quoc-Viet Pham; Dinh Thai Hoang; Long Tran-Thanh; Diep N. Nguyen; Won-Joo Hwang (CoRR, 2022)

Multi-Player Bandits Robust to Adversarial Collisions. - Shivakumar Mahesh; Anshuka Rangi; Haifeng Xu; Long Tran-Thanh (CoRR, 2022)

Invariant Lipschitz Bandits: A Side Observation Approach. - Nam Phuong Tran; The-Anh Ta; Long Tran-Thanh (CoRR, 2022)

Playing Repeated Coopetitive Polymatrix Games with Small Manipulation Cost. - Shivakumar Mahesh; Nicholas Bishop; Le Cong Dinh; Long Tran-Thanh (GameSec, 2023)

Towards Data-Agnostic Pruning At Initialization: What Makes a Good Sparse Mask? - Hoang Pham; The-Anh Ta; Shiwei Liu 003; Lichuan Xiang; Dung Le; Hongkai Wen 001; Long Tran-Thanh (NeurIPS, 2023)

Invariant Lipschitz Bandits: A Side Observation Approach. - Nam Phuong Tran; Long Tran-Thanh (ECML/PKDD (4), 2023)

Achieving Better Regret against Strategic Adversaries. - Le Cong Dinh; Tri-Dung Nguyen; Alain B. Zemkoho; Long Tran-Thanh (CoRR, 2023)

Predicting COVID-19 pandemic by spatio-temporal graph neural networks: A New Zealand's study. - Viet Bach Nguyen; Truong Son-Hy; Long Tran-Thanh; Nhung Nghiem (CoRR, 2023)

Examining the Effects of Degree Distribution and Homophily in Graph Learning Models. - Mustafa Yasir; John Palowitch; Anton Tsitsulin; Long Tran-Thanh; Bryan Perozzi (CoRR, 2023)

Revisiting LARS for Large Batch Training Generalization of Neural Networks. - Hoang Khoi Do; Duong Nguyen; Hoa Nguyen; Long Tran-Thanh; Quoc-Viet Pham (CoRR, 2023)

Efficient and adaptive incentive selection for crowdsourcing contests. - Nhat Van-Quoc Truong; Le Cong Dinh; Sebastian Stein 001; Long Tran-Thanh; Nicholas R. Jennings (Appl. Intell., 2023)

Online Markov decision processes with non-oblivious strategic adversary. - Le Cong Dinh; David Henry Mguni; Long Tran-Thanh; Jun Wang 012; Yaodong Yang 001 (Auton. Agents Multi Agent Syst., 2023)

A Summary of Online Markov Decision Processes with Non-oblivious Strategic Adversary. - Le Cong Dinh; David Henry Mguni; Long Tran-Thanh; Jun Wang 012; Yaodong Yang 001 (AAMAS, 2024)

Attacking Multi-Player Bandits and How to Robustify Them. - Shivakumar Mahesh; Anshuka Rangi; Haifeng Xu; Long Tran-Thanh (AAMAS, 2024)

HierarchyNet: Learning to Summarize Source Code with Heterogeneous Representations. - Minh Nguyen; Nghi Bui; Truong Son Hy; Long Tran-Thanh; Tien Nguyen (EACL (Findings), 2024)

Identifying the Best Arm in the Presence of Global Environment Shifts. - Phurinut Srisawad; Juergen Branke; Long Tran-Thanh (ECAI, 2024)

A Simulation for Supply Chains Contract Execution. - Long Tran-Thanh; Tran Cao Son; Dylan Flynn; Marcello Balduccini (LPNMR, 2024)

Symmetric Linear Bandits with Hidden Symmetry. - Nam Phuong Tran; The-Anh Ta; Debmalya Mandal; Long Tran-Thanh (NeurIPS, 2024)

Learning the Expected Core of Strictly Convex Stochastic Cooperative Games. - Nam Phuong Tran; The-Anh Ta; Shuqing Shi; Debmalya Mandal; Yali Du 001; Long Tran-Thanh (NeurIPS, 2024)

Betting on what is neither verifiable nor falsifiable. - Abhimanyu Pallavi Sudhir; Long Tran-Thanh (CoRR, 2024)

Non-stochastic Budgeted Online Pricing with Semi-Bandit Feedback. - Xiang Liu 014; Hau Chan; Minming Li; Weiwei Wu 001; Long Tran-Thanh (AAAI, 2025)

HRI-SENSE: A Multimodal Dataset on Social and Emotional Responses to Robot Behaviour. - Balint Gucsi; Nguyen Tan Viet Tuyen; Bing Chu; Danesh S. Tarapore; Long Tran-Thanh (HRI, 2025)

DPaI: Differentiable Pruning at Initialization with Node-Path Balance Principle. - Lichuan Xiang; Quan Nguyen-Tri; Lan-Cuong Nguyen; Hoang Pham; Khoat Than; Long Tran-Thanh; Hongkai Wen 001 (ICLR, 2025)

Market-based Architectures in RL and Beyond. - Abhimanyu Pallavi Sudhir; Long Tran-Thanh (AAMAS, 2025)

Provably Improving Generalization of Few-Shot Models with Synthetic Data. - Lan-Cuong Nguyen; Quan Nguyen-Tri; Bang Tran Khanh; Dung D. Le; Long Tran-Thanh; Khoat Than (CoRR, 2025)

Revisiting LARS for Large Batch Training Generalization of Neural Networks. - Hoang Khoi Do; Minh-Duong Nguyen; Nguyen Tien Hoa 001; Long Tran-Thanh; Nguyen Hoang Tran; Quoc-Viet Pham (IEEE Trans. Artif. Intell., 2025)

Learning in Repeated Multi-Objective Stackelberg Games with Payoff Manipulation. - Phurinut Srisawad; Juergen Branke; Long Tran-Thanh (CoRR, 2025)