The University of Southampton
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Electronics and Computer Science
Email:
L.Tran-Thanh@soton.ac.uk

Dr Long Tran-Thanh 

Personal homepage

I have joined University of Warwick since July 2020 and this website will not be maintained anymore. Please visit the website of my Human-Agent Learning Lab for more details:

https://human-agentlearning.github.io/

I'm currently an Associate Professor in Computer Science at the University of Warwick and a Visiting Fellow at the University of Southampton.

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Research Awards/Recognitions:

  • IJCAI 2019 Early Career Spotlight Talk (invited)
  • Vice-Chancellor's Award 2018 (Univ. of Southampton)
  • Royal Society Kan Tong Po Visiting Fellowship 2017
  • Visiting Fellowship at the University of Southern California CAIS Center 2017
  • AAAI 2012 Outstanding Paper Award, honourable mention
  • ECAI 2012 Best Student Paper Award, runner-up
  • ECCAI Artificial Intelligence Dissertation Award (for the best European PhD thesis in Artificial Intelligence in 2012), honourable mention
  • CPHC/BCS PhD Dissertation Award (for the best Computer Science PhD thesis in the UK in 2012/2013), runner-up

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Teaching Awards:

  • Dean's Award 2017 (Faculty of Physical Sciences and Engineering, Southampton)
  • Most Engaging Lecturer (Univ. of Southampton) 2016

Research

Research interests

Human-aware AI: My main research focus is on combining machine learning, game theory, optimisation, and incentive engineering to tackle optimisation problems within AI systems caused by strategic and selfish human users.

AI for Social Good: I also apply my core AI research to a number of societal challenges, including:

• Using machine learning (ML) and crowdsourced incentive engineering to develop air pollution monitoring system with low cost mobile sensor devices

• Developing smart devices that can use energy efficient algorithms to learn to detect a number of diseases such as TB, or to predict severe health issues such as asthma attacks.

• Designing intelligent housing management systems for homeless people.

• Applying AI and optimisation techniques for efficient suicide prevention.

• Building intelligent solutions for national/cyber security issues.

I also have 2 projects with my colleagues in Vietnam. One is about building low-cost sensor systems for air pollution monitoring in Saigon (joint work with Hien vo from VGU and Huy-Dzung Han from HUST), and the other one is about building stand-alone intelligent devices for tuberculosis testing (with Cuong Pham from PTIT). Apart from these, I am also interested in applying AI to governance (govtech) and education (edtech).   

Online learning: One of my core research areas is bandit theory. In particular, I investigate multi-armed bandit (MAB) models where pulling an arm (i.e., making a decision) requires a cost and the total spending is limited by a finite budget. To tackle this problem, I have introduced a new model, called the budget-limited MAB, and have also proposed a number of arm pulling algorithms for which I have provided both theoretical and empirical performance analyses. I am also interested in applying this bandit model (or its variances) to other domains of AI, such as: (i) decentralised controlling for UAVs; (ii) information collection in wireless sensor networks; and (iii) budget-limited online keyword bidding.

Game theory: My other core research area is game theory: I mainly focus on large coalition formation games from both game theoretical and decision making perspective. In more detail, I look at systems where the number of participants is very large (typically thousands or more). Within these systems, calculating different solution concepts (e.g., the core, nucleolus, Shapley-value, etc.) are very hard. Given this, my goal is to identify approximation techniques that can efficiently provide high quality results. To do so, with some of my colleagues, we have introduced a novel, vector-based, representation model of the participating agents, with which we can calculate the abovementioned concepts in a significantly more efficient way. We have also analysed the error bounds of approximating the Shapley value in large games.

I also study different games with resource allocation from both aspects of classical and behavioural game theory. In particular, I am interested in calculating different equilibria and price of anarchy. 

From the behavioural game theory perspective, I aim to identify players' favourite strategies when they repeatedly play such games against different opponents (Repeated Colonel Blotto).

Crowdsourcing: More recently, I investigate the performance of different crowdsourcing systems from a theoretical perspective, aiming to provide rigorous performance guarantees for task allocation algorithms. 

Home energy management: I am heavily involved in the research work on home energy management. In particular, we aim to improve the energy consumption profile of home owners, in order to reduce the CO2 emission of the domestic energy sector. To do so, as the first step, we mainly focussed on the accurate learning and prediction of homeowners' habit, such as appliance usage and heating preferences. Our results were published at ACM E-Energy 2013 and IJCAI 2013.

I am also interested in how to keep user annoyance at an efficient level while interacting with them. With my collaborators we have developed a number of techniques to achieve this goal, and our findings were published at IJCAI 2016 and AAMAS 2018.

Other research interests:

The cost of interference to closed evolving systems: We investigate what is the cost to interfere into closed systems, if we want the system to achieve some desirable states. As a first step, we look at evolving evolutionary games, where an external decision maker can invest his resources into the system (e.g., via a reward scheme) such that in the long term, the agents will follow a preferred behaviour. A preliminary result has been presented at COIN 2014 and NAG 2014, and our most recent results just got accepted to Nature’s Scientific Reports.

Non-monetary referral incentives: I am also investigating how non-monetary referral incentivisation work in social networks. You can find a preliminary version of our work here. For more details, you can visit the website of our project, or watch a video about it. 

Algebraic topology for machine learning: With my PhD student Tom Davies we are also investigating how to make the application of persistent diagrams and other techniques from algebraic topology more efficient and automated in machine learning systems. Our first result is a fuzzy clustering method for persistent diagrams.

Teaching

I have taught the following modules at Southampton:

COMP1201 - Algorithmics (module leader)

COMP3222/6246 - Machine Learning Technologies (module leader)

COMP6247 - Reinforcement and Online Learning (module leader)

Publications

Kho, Johnsen, Tran-Thanh, Long, Rogers, Alex and Jennings, Nick (2009) Distributed Adaptive Sampling, Forwarding, and Routing Algorithms for Wireless Visual Sensor Networks. Third International Workshop on Agent Technology for Sensor Networks, a workshop of the 8th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS-09), Budapest, Hungary. 10 - 15 May 2009. pp. 63-70 .

Kho, Johnsen, Tran-Thanh, Long, Rogers, Alex and Jennings, Nicholas R. (2010) An Agent-Based Distributed Coordination Mechanism for Wireless Visual Sensor Nodes Using Dynamic Programming. The Computer Journal, 53 (8), 1277-1290.

Tran-Thanh, Long, Chapman, Archie, Munoz De Cote Flores Luna, Jose Enrique, Rogers, Alex and Jennings, Nicholas R. (2010) Epsilon–First Policies for Budget–Limited Multi-Armed Bandits. Twenty-Fourth AAAI Conference on Artificial Intelligence, Atlanta, USA, Georgia. 10 - 14 Jul 2010. pp. 1211-1216 .

Tran-Thanh, Long (2010) Multi–Armed Bandit Models for Efficient Long–Term Information Collection in Wireless Sensor Networks s.n. (In Press)

Tran-Thanh, Long, Rogers, Alex and Jennings, Nick (2012) Long–term information collection with energy harvesting wireless sensors: a multi–armed bandit based approach. Autonomous Agents and Multi-Agent Systems, 25 (2), 352-394. (doi:10.1007/s10458-011-9179-0).

Tran-Thanh, Long, Polukarov, Maria, Chapman, Archie, Rogers, Alex and Jennings, Nicholas R. (2011) On the Existence of Pure Strategy Nash Equilibria in Integer-Splittable Weighted Congestion Games. 4th International Symposium, SAGT 2011, Amalfi, Italy. pp. 236-253 . (doi:10.1007/978-3-642-24829-0_22).

Stranders, Ruben, Tran-Thanh, Long, Delle Fave, Francesco Maria, Rogers, Alex and Jennings, Nick (2012) DCOPS and bandits: Exploration and exploitation in decentralised coordination. Proc. 11th Int. Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), Valencia, Spain. pp. 289-297 .

Tran-Thanh, Long, Chapman, Archie, Rogers, Alex and Jennings, Nicholas R. (2012) Knapsack based optimal policies for budget-limited multi-armed bandits. Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI-12), Toronto, Canada. 21 Jul 2012. pp. 1134-1140 .

Tran-Thanh, Long (2012) Budget-limited multi-armed bandits. University of Southampton, Faculty of Physical and Applied Sciences, Doctoral Thesis, 173pp.

Truong, Ngoc Cuong, Tran-Thanh, Long, Costanza, Enrico and Ramchurn, Sarvapali D. (2012) Predicting energy consumption activities for home energy management. Agent Technologies for Energy Systems (ATES 2012), Valencia, Spain. 8 pp .

Tran-Thanh, Long, Stein, Sebastian, Rogers, Alex and Jennings, Nicholas R. (2012) Efficient crowdsourcing of unknown experts using multi-armed bandits. 20th European Conference on Artificial Intelligence (ECAI 2012), Montpellier, France. 26 - 30 Aug 2012. pp. 768-773 . (doi:10.3233/978-1-61499-098-7-768).

Tran-Thanh, Long, Venanzi, Matteo, Rogers, Alex and Jennings, Nicholas R. (2013) Efficient Budget Allocation with Accuracy Guarantees for Crowdsourcing Classification Tasks. AAMAS '13 Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems. pp. 901-908 .

Tran-Thanh, Long, Nguyen, Tri-Dung, Rahwan, Talal, Rogers, Alex and Jennings, N. R. (2013) An efficient vector-based representation for coalitional games. IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence. pp. 383-389 .

Truong, Ngoc Cuong, Tran-Thanh, Long, Costanza, Enrico and Ramchurn, D. Sarvapali (2013) Activity prediction for agent-based home energy management. Agent Technologies for Energy Systems (ATES 2013), Minnesota, United States. 05 - 06 May 2013. 8 pp .

Truong, Ngoc Cuong, Tran-Thanh, Long, Costanza, Enrico and Ramchurn, Sarvapali D. (2013) Towards appliance usage prediction for home energy management. ACM E-Energy 2013, Berkeley, United States. 20 - 23 May 2013. 2 pp .

Truong, Ngoc Cuong, McInerney, James, Tran-Thanh, Long, Costanza, Enrico and Ramchurn, Sarvapali D. (2013) Forecasting multi-appliance usage for smart home energy management. 23rd International Joint Conference on Artificial Intelligence (IJCAI 2013), , Beijing, China. 03 - 09 Aug 2013.

Tran-Thanh, Long, Huynh, Trung Dong, Rosenfeld, A, Ramchurn, Sarvapali and Jennings, Nicholas R. (2014) BudgetFix: budget limited crowdsourcing for interdependent task allocation with quality guarantees. In Proceedings of the 13th International Conference on Autonomous Agents and Multiagent Systems: AAMAS '14. ACM Press. pp. 477-484 .

Tran-Thanh, Long, Stein, Sebastian and Rogers, Alex et al. (2014) Efficient crowdsourcing of unknown experts using bounded multi-armed bandits. Artificial Intelligence, 214, 89-111. (doi:10.1016/j.artint.2014.04.005).

Tran-Thanh, Long, Stavrogiannis, Lampros C., Naroditskiy, Victor, Robu, Valentin, Jennings, Nicholas R. and Key, Peter (2014) Efficient regret bounds for online bid optimisation in budget-limited sponsored search auctions. Zhang, Nevin L. and Tian, Jin (eds.) In Uncertainty in Artificial Intelligence: Proceedings of the Thirtieth Conference (2014): July 23-27, 2014, Quebec City, Quebec, Canada. AUAI Press. pp. 809-818 .

Han, TheAnh, Tran-Thanh, Long and Jennings, Nicholas R. (2014) The cost of interference in evolving systems. COIN 2014: The 17th International Workshop on Coordination, Organisations, Institutions and Norms, Paris, France. 05 Jun 2014.

Naroditskiy, Victor, Stein, Sebastian, Tonin, Mirco, Tran-Thanh, Long, Vlassopoulos, Michael and Jennings, N.R. (2014) Referral incentives in crowdfunding. HCOMP2014: Conference on Human Computation & Crowdsourcing, Pittsburgh, United States. 02 - 04 Nov 2014. pp. 171-183 .

Tran-Thanh, Long, Huynh, Trung Dong, Rosenfeld, Avi, Ramchurn, Sarvapali D. and Jennings, Nicholas R. (2015) Crowdsourcing complex workflows under budget constraints. In AAAI'15 Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence. ACM Press. pp. 1298-1304 .

Tran-Thanh, Long, Xia, Yingce, Qin, Tao and Jennings, Nicholas R. (2015) Efficient algorithms with performance guarantees for the stochastic multiple-choice knapsack problem. In IJCAI'15 Proceedings of the 24th International Conference on Artificial Intelligence. ACM Press. pp. 403-409 .

Tran-Thanh, Long, Xu, Haifeng and Jennings, Nicholas R. (2016) Playing repeated security games with no prior knowledge. Proceedings of the 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2016), Singapore, Singapore. 08 - 12 May 2016. 9 pp .

Kawale, Jaya, Bui, Hung, Kveton, Branislav, Tran-Thanh, Long and Chawla, Sanjay (2015) Efficient Thompson sampling for online matrix-factorization recommendation. In NIPS'15: Proceedings of the 28th International Conference on Neural Information Processing Systems - Volume 1. vol. 1, ACM Press. pp. 1297-1305 .

Truong, Ngoc Cuong, Baarslag, Tim, Ramchurn, Gopal and Tran-Thanh, Long (2016) Interactive scheduling of appliance usage in the home. 25th International Joint Conference on Artificial Intelligence (IJCAI-160, New York, United States. 08 - 14 Jul 2016. 7 pp .

Waniek, Marcin, Tran-Thanh, Long, Michalak, Tomasz P. and Jennings, Nicholas (2017) The dollar auction with spiteful players. In Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence and the Twenty-Ninth Innovative Applications of Artificial Intelligence Conference. vol. 1, AAAI. 7 pp .

Guo, Qingyu, An, Bo and Tran-Thanh, Long (2017) Playing repeated network interdiction games with semi-bandit feedback. In Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17). 9 pp . (In Press)

Zhang, Youzhi, An, Bo, Tran-Thanh, Long, Wang, Zhen, Gan, Jiarui and Jennings, Nicholas R. (2017) Optimal escape Interdiction on transportation networks. International Joint Conference on Artificial Intelligence, MCEC (Melbourne Convention and Exhibition Center), Melbourne, Australia. 19 - 25 Aug 2017. 9 pp .

Gunes, Taha, Norman, Timothy and Tran-Thanh, Long (2017) Budget limited trust-aware decision making. In, AAMAS 2017: Autonomous Agents and Multiagent Systems. (Lecture Notes in Computer Science, 10643) Springer International Publishing, pp. 101-110. (doi:10.1007/978-3-319-71679-4_7).

Truong, Nhat, Van Quoc, Stein, Sebastian, Tran-Thanh, Long and Jennings, Nick (2018) Adaptive incentive selection for crowdsourcing contests. 17th International Conference on Autonomous Agents and Multiagent Systems, , Stockholm, Sweden. 11 - 12 Jul 2018. pp. 2100-2102 .

Khan, Md. Mosaddek, Tran-Thanh, Long, Yeoh, William and Jennings, Nicholas (2018) A near-optimal node-to-agent mapping heuristic for GDL-based DCOP algorithms in multi-agent systems. In 17th International Conference on Autonomous Agents and Multiagent Systems. International Foundation for Autonomous Agents and Multiagent Systems. pp. 1613-1621 .

Khan, Md. Mosaddek, Tran-Thanh, Long and Jennings, Nicholas (2018) A generic domain pruning technique for GDL-based DCOP algorithms in cooperative multi-agent systems. In 17th International Conference on Autonomous Agents and Multiagent Systems. vol. 3, International Foundation for Autonomous Agents and Multiagent Systems. pp. 1595-1603 .

Manino, Edoardo, Tran-Thanh, Long and Jennings, Nicholas (2018) On the efficiency of data collection for crowdsourced classification. International Joint Conference on Artificial Intelligence, , Stockholm, Sweden. 13 - 19 Jul 2018. 8 pp .

Güneş, Taha D., Tran-Thanh, Long and Norman, Timothy J. (2018) Strategic attacks on trust models via bandit optimization. CEUR Workshop Proceedings, 2154, 87-95.

Schlenker, Aaron, Thakoor, Omkar, Xu, Haifeng, Fang, Fei, Tambe, Milind, Tran-Thanh, Long, Vayanos, Phebe and Vorobeychik, Yevgeniy (2018) Deceiving cyber adversaries: A game theoretic approach. In 17th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2018. vol. 2, International Foundation for Autonomous Agents and Multiagent Systems. pp. 892-900 .

Le, Tiep, Tabakhi, Atena M., Tran-Thanh, Long, Yeoh, William and Son, Tran Cao (2018) Preference elicitation with interdependency and user bother cost. In 17th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2018. vol. 2, International Foundation for Autonomous Agents and Multiagent Systems. pp. 1459-1467 .

Serb, Alexantrou, Manino, Edoardo, Messaris, Ioannis, Tran-Thanh, Long and Prodromakis, Themis (2017) Hardware-level Bayesian inference. In Neural Information Processing Systems. 7 pp .

Guo, Qingyu, Gan, Jiarui, Fang, Fei, Tran-Thanh, Long, Tambe, Milind and An, Bo (2018) Inducible equilibrium for security games. In 17th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2018. vol. 3, International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS). pp. 1947-1949 .

Han, The Anh and Tran-Thanh, Long (2018) Cost-effective external interference for promoting the evolution of cooperation. Scientific Reports, 8 (1), 1-9, [15997]. (doi:10.1038/s41598-018-34435-2).

Han, The Anh, Lynch, Simon, Tran-Thanh, Long and Santos, Francisco C. (2018) Fostering cooperation in structured populations through local and global interference strategies. In Proceedings of the 27th International Joint Conference on Artificial Intelligence, IJCAI 2018. vol. 2018-July, International Joint Conferences on Artificial Intelligence. pp. 289-295 .

Shi, Zheyuan Ryan, Tang, Ziye, Tran-Thanh, Long, Singh, Rohit and Fang, Fei (2018) Designing the game to play: Optimizing payoff structure in security games. In Proceedings of the 27th International Joint Conference on Artificial Intelligence, IJCAI 2018. vol. 2018-July, International Joint Conferences on Artificial Intelligence. pp. 512-518 .

Chan, Hau, Tran-Thanh, Long, Wilder, Bryan, Rice, Eric, Vayanos, Phebe and Tambe, Milind (2018) Utilizing housing resources for homeless youth through the lens of multiple multi-dimensional knapsacks. In AIES 2018 - Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society. ACM Press. pp. 41-47 . (doi:10.1145/3278721.3278757).

Gualán, Ronald, Gualán, Ronald, Saquicela, Víctor and Tran-Thanh, Long (2019) EDA and a tailored data imputation algorithm for daily ozone concentrations. Botto-Tobar, M., Barba-Maggi, L., Gonzalez-Huerta, J., Villacres-Cevallos, P., Gomez, O.S. and Uvidia-Fassler, M. (eds.) In Information and Communication Technologies of Ecuador (TIC.EC) : TICEC 2018. vol. 884, Springer. pp. 372-386 . (doi:10.1007/978-3-030-02828-2_27).

Gholami, Shahrzad, Yadav, Amulya, Tran-Thanh, Long, Dilkina, Bistra and Tambe, Milind (2019) Don’t put all your strategies in one basket: Playing green security games with imperfect prior knowledge. Agmon, N., Taylor, M.E., Elkind, E. and Veloso, M. (eds.) In Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems. International Foundation for Autonomous Agents and Multiagent Systems. pp. 395-403 .

Guo, Qingyu, Gan, Jiarui, Fang, Fei, Tran-Thanh, Long, Tambe, Milind and An, Bo (2019) On the inducibility of Stackelberg Equilibrium for security games. In 33rd AAAI Conference on Artificial Intelligence. AAAI. 8 pp .

Zhang, Youzhi, Guo, Qingyu, An, Bo, Tran-Thanh, Long and Jennings, Nicholas R. (2019) Optimal interdiction of urban criminals with the aid of real-time information. In 33rd AAAI Conference on Artificial Intelligence. AAAI. 8 pp .

Gunes, Taha, Tran-Thanh, Long and Norman, Timothy (2019) Identifying vulnerabilities in trust and reputation systems. In Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, IJCAI-19, Macao, China, August 10-16, 2019. International Joint Conferences on Artificial Intelligence Organization. pp. 308-314 . (doi:10.24963/ijcai.2019/44).

Gunes, Taha, Tran-Thanh, Long and Norman, Timothy (2019) Attack strategies and analysis for trust and reputation systems. University of Southampton doi:10.5258/SOTON/D0937 [Dataset]

Gan, Jiarui, Xu, Haifeng, Guo, Qingyu, Tran-Thanh, Long, Rabinovich, Zinovi and Wooldridge, Michael (2019) Imitative follower deception in Stackelberg games. In ACM EC 2019 - Proceedings of the 2019 ACM Conference on Economics and Computation. ACM Press. pp. 639-657 . (doi:10.1145/3328526.3329629).

Manino, Edoardo, Tran-Thanh, Long and Jennings, Nicholas (2019) On the efficiency of data collection for multiple Naïve Bayes classifiers. Artificial Intelligence, 275, 356-378. (doi:10.1016/j.artint.2019.06.010).

Truong, Nhat, Van Quoc, Stein, Sebastian, Tran-Thanh, Long and Jennings, Nick (2019) What prize is right? How to learn the optimal structure for crowdsourcing contests. Nayak, Abhaya and Sharma, Alok (eds.) In PRICAI 2019: Trends in Artificial Intelligence. vol. 1160, Springer. pp. 85-97 . (doi:10.1007/978-3-030-29908-8_7).

Romero Moreno, Guillermo, Tran-Thanh, Long and Brede, Markus (2020) Shielding and shadowing: a tale of two strategies for opinion control in the voting dynamics. Cherifi, Hocine, Gaito, Sabrina, Mendes, José Fernendo, Moro, Esteban and Rocha, Luis Mateus (eds.) In Complex Networks and Their Applications VIII: Volume 1: Proceedings of the Eighth International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2019. vol. 881, Springer. pp. 682-693 . (doi:10.1007/978-3-030-36687-2_57).

Serafino, Paolo, Ventre, Carmine, Tran-Thanh, Long, Zhang, Jie, An, Bo and Jennings, Nick (2019) Social cost guarantees in smart route guidance. Nayak, A. and Sharma, A. (eds.) In PRICAI 2019: Trends in Artificial Intelligence. PRICAI 2019. vol. 11671, Springer, Cham. pp. 482-495 . (doi:10.1007/978-3-030-29911-8_37).

Leelavimolsilp, Tin, Nguyen, Viet, Stein, Sebastian and Tran-Thanh, Long (2019) Selfish mining in Proof-of-Work blockchain with multiple miners: An empirical evaluation. Baldoni, Matteo, Dastani, Mehdi, Liao, Beishui, Sakurai, Yuko and Zalila-Wenkstern, Rym (eds.) In PRIMA 2019: Principles and Practice of Multi-Agent Systems. vol. 11873, Springer. pp. 219-234 . (doi:10.1007/978-3-030-33792-6_14).

Manino, Edoardo, Tran-Thanh, Long and Jennings, Nicholas (2019) Streaming Bayesian inference for crowdsourced classification. 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), , Vancouver, Canada. 08 - 14 Dec 2019. 11 pp .

Xun, Lei, Tran-Thanh, Long, Al-Hashimi, Bashir and Merrett, Geoff (2020) Optimising resource management for embedded machine learning. Di Natale, Giorgio, Bolchini, Cristiana and Vatajelu, Elena-Ioana (eds.) In Proceedings of the 2020 Design, Automation and Test in Europe Conference and Exhibition, DATE 2020. pp. 1556-1561 . (doi:10.23919/DATE48585.2020.9116235).

Xun, Lei (2019) Dataset for "Optimising Resource Management for Embedded Machine Learning". University of Southampton doi:10.5258/SOTON/D1154 [Dataset]

Xun, Lei (2020) Dataset for "Incremental Training and Group Convolution Pruning for Runtime DNN Performance Scaling on Heterogeneous Embedded Platforms". University of Southampton doi:10.5258/SOTON/D1245 [Dataset]

Romero Moreno, Guillermo, Manino, Edoardo, Tran-Thanh, Long and Brede, Markus (2020) Zealotry and influence maximization in the voter model: when to target zealots? Barbosa, Hugo, Menezes, Ronaldo, Gomez-Gardenes, Jesus, Gonçalves, Bruno, Mangioni, Giuseppe and Oliveira, Marcos (eds.) In Complex Networks XI - Proceedings of the 11th Conference on Complex Networks, CompleNet 2020: Proceedings of the 11th Conference on Complex Networks CompleNet 2020. Springer. pp. 107-118 . (doi:10.1007/978-3-030-40943-2_10).

Romero Moreno, Guillermo, Tran-Thanh, Long and Brede, Markus (2020) Continuous influence maximisation for the voter dynamics: is targeting high-degree nodes a good strategy? International Conference on Autonomous Agents and Multi-Agent Systems 2020, , Auckland, New Zealand. 09 - 13 May 2020. 3 pp .

Manino, Edoardo (2020) Source code of binary_sims.exe and related datasets. University of Southampton doi:10.5258/SOTON/D1505 [Dataset]

Ortega Alban, Andre Paola, Ramchurn, Sarvapali, Tran-Thanh, Long and Merrett, Geoffrey (2020) Dataset for: Partner selection in self-organised wireless sensor networks for opportunistic energy negotiation: A multi-armed bandit based approach. University of Southampton doi:10.5258/SOTON/D1659 [Dataset]

Bishop, Nicholas, Chan, Hau, Mandal, Debmalya and Tran-Thanh, Long (2020) Adversarial blocking bandits. Larochelle, H., Ranzato, M., Hadsell, R., Balcan, M.F. and Lin, H. (eds.) In Advances in Neural Information Processing Systems 33 (NeurIPS 2020). NeurIPS..

Bishop, Nicholas, Tran-Thanh, Long and Gerding, Enrico (2020) Optimal learning from verified training data. Larochelle, H., Ranzato, M., Hadsell, R., Balcan, M.F. and Lin, H. (eds.) In Advances in Neural Information Processing Systems 33 (NeurIPS 2020). NeurIPS..

Ortega, Andre P., Ramchurn, Sarvapali, Tran-Thanh, Long and Merrett, Geoff (2021) Partner selection in self-organised wireless sensor networks for opportunistic energy negotiation: A multi-armed bandit based approach. Ad Hoc Networks, 112, [102354]. (doi:10.1016/j.adhoc.2020.102354).

Mahmud, Saaduddin, Choudhury, Moumita, Khan, Md. Mosaddek, Tran-Thanh, Long and Jennings, Nicholas R. (2020) AED: An Anytime Evolutionary DCOP Algorithm. An, B, Yorke-Smith, N, Fallah Seghrouch, El and Sukthank, G (eds.) In Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2020. International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS). pp. 825-833 .

Contact

Email: L.Tran-Thanh@soton.ac.uk

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