Browse by UCL people
Group by: Type | Date
Number of items: 124.
Article
Chen, Y;
Tian, Z;
Zhang, H;
Wang, J;
Zhang, D;
(2020)
Strongly Constrained Discrete Hashing.
IEEE Transactions on Image Processing
, 29
pp. 3596-3611.
10.1109/TIP.2020.2963952.
|
 |
|
Cowen-Rivers, Alexander I;
Lyu, Wenlong;
Tutunov, Rasul;
Wang, Zhi;
Grosnit, Antoine;
Griffiths, Ryan Rhys;
Maravel, Alexandre Max;
... Bou-Ammar, Haitham; + view all
(2022)
HEBO: Pushing The Limits of Sample-Efficient Hyperparameter Optimisation.
Journal of Artificial Intelligence Research
, 74
pp. 1269-1349.
10.1613/jair.1.13643.
|
|
Cui, X;
Sun, B;
Zhu, Y;
Yang, N;
Zhang, H;
Cui, W;
Fan, D;
(2024)
Enhancing efficiency and propulsion in bio-mimetic robotic fish through end-to-end deep reinforcement learning.
Physics of Fluids
, 36
(3)
, Article 031910. 10.1063/5.0192993.
|
|
Deng, Xiaotie;
Li, Ningyuan;
Mguni, David;
Wang, Jun;
Yang, Yaodong;
(2023)
On the complexity of computing Markov perfect equilibrium in general-sum stochastic games.
National Science Review
, 10
(1)
, Article nwac256. 10.1093/nsr/nwac256.
|
|
|
Dinh, LC;
Mguni, DH;
Tran-Thanh, L;
Wang, J;
Yang, Y;
(2023)
Online Markov decision processes with non-oblivious strategic adversary.
Autonomous Agents and Multi-Agent Systems
, 37
(1)
, Article 15. 10.1007/s10458-023-09599-5.
|
|
Grosnit, Antoine;
Cowen-Rivers, Alexander;
Tutunov, Rasul;
Griffiths, Ryan-Rhys;
Wang, Jun;
Bou-Ammar, Haitham;
(2021)
Are we Forgetting about Compositional Optimisers in Bayesian Optimisation?
Journal of Machine Learning Research
, 22
pp. 1-78.
|
|
Han, M;
Tian, Y;
Zhang, L;
Wang, J;
Pan, W;
(2021)
Reinforcement learning control of constrained dynamic systems with uniformly ultimate boundedness stability guarantee.
Automatica
, 129
, Article 109689. 10.1016/j.automatica.2021.109689.
|
|
|
Han, M;
Zhang, L;
Wang, J;
Pan, W;
(2020)
Actor-Critic Reinforcement Learning for Control With Stability Guarantee.
IEEE Robotics and Automation Letters
, 5
(4)
pp. 6217-6224.
10.1109/LRA.2020.3011351.
|
|
|
He, X;
Wu, J;
Huang, Z;
Hu, Z;
Wang, J;
Sangiovanni-Vincentelli, A;
Lv, C;
(2024)
Fear-Neuro-Inspired Reinforcement Learning for Safe Autonomous Driving.
IEEE Transactions on Pattern Analysis and Machine Intelligence
, 46
(1)
pp. 267-279.
10.1109/TPAMI.2023.3322426.
|
|
Huang, J;
Chen, B;
Yan, Z;
Ounis, I;
Wang, J;
(2023)
GEO: A Computational Design Framework for Automotive Exterior Facelift.
ACM Transactions on Knowledge Discovery from Data
, 17
(6)
, Article 82. 10.1145/3578521.
|
|
|
Huang, Zeren;
Wang, Kerong;
Liu, Furui;
Zhen, Hui-Ling;
Zhang, Weinan;
Yuan, Mingxuan;
Hao, Jianye;
... Wang, Jun; + view all
(2022)
Learning to select cuts for efficient mixed-integer programming.
Pattern Recognition
, 123
, Article 108353. 10.1016/j.patcog.2021.108353.
|
|
Kankanhalli, MS;
Wang, J;
Jain, R;
(2006)
Experiential sampling in multimedia systems.
IEEE Transactions on Multimedia
, 8
(5)
pp. 937-946.
10.1109/TMM.2006.879876.
|
 |
|
Kankanhalli, MS;
Wang, J;
Jain, R;
(2006)
Experiential sampling on multiple data streams.
IEEE Transactions on Multimedia
, 8
(5)
pp. 947-955.
10.1109/TMM.2006.879875.
|
|
|
Khan, Asif;
Cowen-Rivers, Alexander I;
Grosnit, Antoine;
Deik, Derrick-Goh-Xin;
Robert, Philippe A;
Greiff, Victor;
Smorodina, Eva;
... Bou-Ammar, Haitham; + view all
(2023)
Toward real-world automated antibody design with combinatorial Bayesian optimization.
Cell Reports Methods
, 3
(1)
, Article 100374. 10.1016/j.crmeth.2022.100374.
|
|
Li, H;
Huang, W;
Duan, Z;
Mguni, DH;
Shao, K;
Wang, J;
Deng, X;
(2024)
A survey on algorithms for Nash equilibria in finite normal-form games.
Computer Science Review
, 51
, Article 100613. 10.1016/j.cosrev.2023.100613.
|
|
Li, Y;
Sun, F;
Hu, J;
Liu, C;
Wu, F;
Li, K;
Wen, Y;
... Yang, Y; + view all
(2023)
Self-Supervised MAFENN for Classifying Low-labeled Distorted Images over Mobile Fading Channels.
IEEE Transactions on Mobile Computing
10.1109/TMC.2023.3343939.
(In press).
|
|
Lin, G;
Chen, F;
Hu, P;
Chen, X;
Chen, J;
Wang, J;
Shi, Z;
(2023)
BI-GreenNet: Learning Green's Functions by Boundary Integral Network.
Communications in Mathematics and Statistics
, 11
pp. 103-129.
10.1007/s40304-023-00338-6.
|
|
Lin, G;
Hu, P;
Chen, F;
Chen, X;
Chen, J;
Wang, J;
Shi, Z;
(2023)
BINet: Learn to Solve Partial Differential Equations with Boundary Integral Networks.
CSIAM Transactions on Applied Mathematics
, 4
(2)
pp. 275-305.
10.4208/csiam-am.SO-2022-0014.
|
|
Meng, L;
Wen, M;
Le, C;
Li, X;
Xing, D;
Zhang, W;
Wen, Y;
... Xu, B; + view all
(2023)
Offline Pre-trained Multi-agent Decision Transformer.
Machine Intelligence Research
, 20
(2)
pp. 233-248.
10.1007/s11633-022-1383-7.
|
|
Sanjaya, R;
Wang, J;
Yang, Y;
(2022)
Measuring the Non-Transitivity in Chess.
Algorithms
, 15
(5)
, Article 152. 10.3390/a15050152.
|
|
Song, Y;
Jiang, H;
Tian, Z;
Zhang, H;
Zhang, Y;
Zhu, J;
Dai, Z;
... Wang, J; + view all
(2024)
An Empirical Study on Google Research Football Multi-agent Scenarios.
Machine Intelligence Research
10.1007/s11633-023-1426-8.
(In press).
|
|
Sun, F;
Li, Y;
Wen, Y;
Hu, J;
Wang, J;
Yang, Y;
Li, K;
(2022)
Multi-Agent Feedback Enabled Neural Networks for Intelligent Communications.
IEEE Transactions on Wireless Communications
10.1109/TWC.2022.3147499.
(In press).
|
|
|
Wang, J;
Zhang, W;
Yuan, S;
(2017)
Display Advertising with Real-Time Bidding (RTB) and Behavioural Targeting.
Foundations and Trends in Information Retrieval
, 11
(4-5)
pp. 297-435.
10.1561/1500000049.
|
|
|
Wang, Z;
Li, X;
Sun, L;
Zhang, H;
Liu, H;
Wang, J;
(2024)
Learning State-Specific Action Masks for Reinforcement Learning.
Algorithms
, 17
(2)
, Article 60. 10.3390/a17020060.
|
|
|
Wen, M;
Lin, R;
Wang, H;
Yang, Y;
Wen, Y;
Mai, L;
Wang, J;
... Zhang, W; + view all
(2023)
Large sequence models for sequential decision-making: a survey.
Frontiers of Computer Science
, 17
, Article 176349. 10.1007/s11704-023-2689-5.
|
|
Yang, M;
Cai, G;
Liu, F;
Jin, J;
Dong, Z;
He, X;
Hao, J;
... Chen, X; + view all
(2023)
Debiased Recommendation with User Feature Balancing.
ACM Transactions on Information Systems
, 41
(4)
, Article 114. 10.1145/3580594.
|
|
Zhang, H;
Guo, Z;
Zhang, W;
Cai, H;
Wang, C;
Yu, Y;
Li, W;
(2019)
Layout Design for Intelligent Warehouse by Evolution With Fitness Approximation.
IEEE Access
, 7
pp. 166310-166317.
10.1109/ACCESS.2019.2953486.
|
|
|
Zhouyin, Z;
Chen, X;
Zhang, P;
Wang, J;
Wang, L;
(2023)
Automatic differentiable nonequilibrium Green's function formalism: An end-to-end differentiable quantum transport simulator.
Physical Review B
, 108
(19)
, Article 195143. 10.1103/PhysRevB.108.195143.
|
Book
|
Grace, Y;
Sloan, M;
Wang, J;
(2016)
Dynamic Information Retrieval Modeling.
[Book].
(1st ed.).
Morgan & Claypool Publishers: Williston, VT, USA.
|
Proceedings paper
|
Akbari, M;
Cetoli, A;
Bragaglia, S;
O’Harney, AD;
Sloan, M;
Wang, J;
(2019)
Modeling user return time using inhomogeneous poisson process.
In:
ECIR 2019: Advances in Information Retrieval.
(pp. pp. 37-44).
Springer: Cologne, Germany.
|
|
Cai, H;
Chen, T;
Zhang, W;
Yu, Y;
Wang, J;
(2018)
Efficient architecture search by network transformation.
In:
(Proceedings) 32nd AAAI Conference on Artificial Intelligence, AAAI 2018.
(pp. pp. 2787-2794).
AAAI: New Orleans, LA, USA.
|
|
|
Cai, H;
Ren, K;
Zhag, W;
Malialis, K;
Wang, J;
Yu, Y;
Guo, D;
(2017)
Real-Time Bidding by Reinforcement Learning in Display Advertising.
In: de Rijke, M and Shokouhi, M and Tomkins, A and Zhang, M, (eds.)
WSDM '17: Proceedings of the Tenth ACM International Conference on Web Search and Data Mining.
(pp. pp. 661-670).
ACM (Association for Computing Machinery): New York, USA.
|
|
|
Cao, L;
Wang, J;
Yang, B;
Su, D;
Yu, D;
(2023)
Trinet: Stabilizing Self-Supervised Learning From Complete or Slow Collapse.
In:
Proceedings of ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
IEEE: Rhodes, Greece.
|
|
Chen, Y;
Deng, X;
Li, C;
Mguni, D;
Wang, J;
Yan, X;
Yang, Y;
(2022)
On the Convergence of Fictitious Play: A Decomposition Approach.
In:
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence 2022.
(pp. pp. 179-185).
IJCAI: International Joint Conferences on Artificial Intelligence Organization
|
|
Chen, Yong;
Zhang, Hui;
Tian, Zhibao;
Wang, Jun;
Zhang, Dell;
Li, Xuelong;
(2023)
Enhanced Discrete Multi-modal Hashing: More Constraints yet Less Time to Learn (Extended Abstract).
In:
2023 IEEE 39th International Conference on Data Engineering (ICDE).
(pp. pp. 3857-3858).
IEEE: Anaheim, CA, USA.
|
|
Chen, D;
Jin, J;
Zhang, W;
Pan, F;
Niu, L;
Yu, C;
Wang, J;
... Gai, K; + view all
(2019)
Learning to Advertise for Organic Traffic Maximization in E-Commerce Product Feeds.
In: Zhu, W and Tao, D and Cheng, X and Cui, P and Rundensteiner, E and Carmel, D and He, Q and Yu, JX, (eds.)
CIKM '19: Proceedings of the 28th ACM International Conference on Information and Knowledge Management.
(pp. pp. 2527-2535).
Association for Computing Machinery (ACM): New York, NY, USA.
|
|
|
Chen, X;
Du, Y;
Xia, L;
Wang, J;
(2021)
Reinforcement recommendation with user multi-aspect preference.
In:
WWW '21: Proceedings of the Web Conference 2021.
(pp. pp. 425-435).
ACM: Association for Computing Machinery: New York, NY, USA.
|
|
|
Dai, X;
Hou, J;
Liu, Q;
Xi, Y;
Tang, R;
Zhang, W;
He, X;
... Yu, Y; + view all
(2020)
U-rank: Utility-oriented Learning to Rank with Implicit Feedback.
In: D'Aquin, M and Dietze, S and Hauff, C and Curry, E and Cudre Mauroux, P, (eds.)
CIKM '20: Proceedings of the 29th ACM International Conference on Information & Knowledge Management.
(pp. pp. 2373-2380).
Association for Computing Machinery (ACM): New York, NY, USA.
|
|
|
Dai, X;
Lin, J;
Zhang, W;
Li, S;
Liu, W;
Tang, R;
He, X;
... Yu, Y; + view all
(2021)
An adversarial imitation click model for information retrieval.
In:
WWW '21: Proceedings of the Web Conference 2021.
(pp. pp. 1809-1820).
Association for Computing Machinery
|
|
|
Du, D;
Han, S;
Qi, N;
Ammar, HB;
Wang, J;
Pan, W;
(2023)
Reinforcement Learning for Safe Robot Control using Control Lyapunov Barrier Functions.
In:
Proceedings of the 2023 IEEE International Conference on Robotics and Automation (ICRA).
(pp. pp. 9442-9448).
IEEE: London, UK.
|
|
Du, Y;
Ma, C;
Liu, Y;
Lin, R;
Dong, H;
Wang, J;
Yang, Y;
(2022)
Scalable Model-based Policy Optimization for Decentralized Networked Systems.
In:
IEEE International Conference on Intelligent Robots and Systems.
(pp. pp. 9019-9026).
IEEE: Kyoto, Japan.
|
|
Du, Yali;
Yan, Xue;
Chen, Xu;
Wang, Jun;
Zhang, Haifeng;
(2021)
Estimating α-Rank from A Few Entries with Low Rank Matrix Completion.
In: Meila, Marina and Zhang, Tong, (eds.)
Proceedings of the 38th International Conference on Machine Learning.
Proceedings of Machine Learning Research (PMLR): Virtual conference.
|
|
Du, M;
Cowen-Rivers, AI;
Wen, Y;
Sakulwongtana, P;
Wang, J;
Brorsson, M;
State, R;
(2020)
Know your enemies and know yourself in the real-time bidding function optimisation.
In:
Proceedings of the 2019 International Conference on Data Mining Workshops (ICDMW).
(pp. pp. 973-981).
IEEE: Beijing, China.
|
|
|
Duan, Z;
Huang, W;
Zhang, D;
Du, Y;
Wang, J;
Yang, Y;
Deng, X;
(2023)
Is Nash Equilibrium Approximator Learnable?
In:
Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems.
(pp. pp. 233-241).
International Foundation for Autonomous Agents and Multiagent Systems
|
|
|
Feng, X;
Chen, C;
Li, D;
Zhao, M;
Hao, J;
Wang, J;
(2021)
CMML: Contextual Modulation Meta Learning for Cold-Start Recommendation.
In:
International Conference on Information and Knowledge Management, Proceedings.
(pp. pp. 484-493).
ACM: Association for Computing Machinery: New York, NY, United States.
|
|
|
Feng, X;
Slumbers, O;
Wan, Z;
Liu, B;
McAleer, S;
Wen, Y;
Wang, J;
(2021)
Neural Auto-Curricula in Two-Player Zero-Sum Games.
In:
Advances in Neural Information Processing Systems.
(pp. pp. 3504-3517).
|
|
Gorla, J;
Lathia, N;
Robertson, S;
Wang, J;
(2013)
Probabilistic group recommendation via information matching.
In:
WWW 2013 Proceedings.
(pp. pp. 495-504).
ACM
|
|
|
Grosnit, Antoine;
Malherbe, Cedric;
Tutunov, Rasul;
Wan, Xingchen;
Wang, Jun;
Ammar, Haitham Bou;
(2022)
BOiLS: Bayesian Optimisation for Logic Synthesis.
In: Bolchini, C and Verbauwhede, I and Vatajelu, I, (eds.)
2022 Design, Automation & Test in Europe Conference & Exhibition (DATE).
(pp. pp. 1193-1196).
IEEE: Antwerp, Belgium.
|
|
Guo, J;
Lu, S;
Cai, H;
Zhang, W;
Yu, Y;
Wang, J;
(2018)
Long text generation via adversarial training with leaked information.
In:
(Proceedings) 32nd AAAI Conference on Artificial Intelligence, AAAI 2018.
(pp. pp. 5141-5148).
AAAI: New Orleans, LA, USA.
|
|
|
Huang, R;
Lam, MWY;
Wang, J;
Su, D;
Yu, D;
Ren, Y;
Zhao, Z;
(2022)
FastDiff: A Fast Conditional Diffusion Model for High-Quality Speech Synthesis.
In:
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence (IJCAI-22).
(pp. pp. 4157-4163).
IJCAI:International Joint Conferences on Artificial Intelligence Organization: Vienna.
|
|
Huang, W;
Li, K;
Shao, K;
Zhou, T;
Taylor, ME;
Luo, J;
Wang, D;
... Deng, X; + view all
(2022)
Multiagent Q-learning with Sub-Team Coordination.
In:
Advances in Neural Information Processing Systems.
|
|
Jin, J;
Chen, X;
Zhang, W;
Yang, M;
Wang, Y;
Du, Y;
Yu, Y;
(2023)
Replace Scoring with Arrangement: A Contextual Set-to-Arrangement Framework for Learning-to-Rank.
In: Frommholz, I and Hopfgartner, F and Lee, M and Oakes, M, (eds.)
CIKM '23: Proceedings of the 32nd ACM International Conference on Information and Knowledge Management.
(pp. pp. 1004-1013).
Association for Computing Machinery (ACM): New York, NY, USA.
|
|
Jin, J;
Fang, Y;
Zhang, W;
Ren, K;
Zhou, G;
Xu, J;
Yu, Y;
... Gai, K; + view all
(2020)
A Deep Recurrent Survival Model for Unbiased Ranking.
In:
SIGIR '20: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval.
(pp. pp. 29-38).
Association for Computing Machinery (ACM)
|
|
|
Jin, J;
Song, C;
Li, H;
Gai, K;
Wang, J;
Zhang, W;
(2018)
Real-time bidding with multi-agent reinforcement learning in display advertising.
In:
(Proceedings) CIKM 2018.
(pp. pp. 2193-2202).
ArXiv
|
|
|
Jin, J;
Zhou, M;
Zhang, W;
Li, M;
Guo, Z;
Qin, Z;
Jiao, Y;
... Ye, J; + view all
(2019)
CoRide: Joint Order Dispatching and Fleet Management for Multi-Scale Ride-Hailing Platforms.
In:
CIKM '19: Proceedings of the 28t ACM International Conference on Information and Knowledge Management.
(pp. pp. 1983-1992).
ACM: Beijing, China.
|
|
|
Jin, X;
Sloan, M;
Wang, J;
(2013)
Interactive exploratory search for multi page search results.
In:
WWW 2013 - Proceedings of the 22nd International Conference on World Wide Web.
(pp. 655 -665).
ACM
|
|
|
Kan, R;
Zhang, W;
Zhang, H;
Rong, Y;
Wang, J;
(2016)
User Response Learning for Directly Optimizing Campaign Performance in Display Advertising.
In:
Proceedings of the 25th ACM International on Conference on Information and Knowledge Management.
(pp. pp. 679-688).
Association for Computing Machinery (ACM): New York, NY, USA.
|
|
Kuba, JG;
Chen, R;
Wen, M;
Wen, Y;
Sun, F;
Wang, J;
Yang, Y;
(2022)
Trust Region Policy Optimisation in Multi-Agent Reinforcement Learning.
In:
ICLR 2022 - 10th International Conference on Learning Representations.
(pp. p. 1046).
The International Conference on Learning Representations (ICLR): Virtual.
|
|
Kuba, JG;
Wen, M;
Meng, L;
Gu, S;
Zhang, H;
Mguni, DH;
Wang, J;
(2021)
Settling the Variance of Multi-Agent Policy Gradients.
In:
Advances in Neural Information Processing Systems 34 (NeurIPS 2021).
(pp. pp. 13458-13470).
NeurIPS Proceedings
|
|
Lai, H;
Zhang, W;
He, X;
Yu, C;
Tian, Z;
Yu, Y;
Wang, J;
(2023)
Sim-to-Real Transfer for Quadrupedal Locomotion via Terrain Transformer.
In:
ICRA 2023: IEEE International Conference on Robotics and Automation.
(pp. pp. 5141-5147).
IEEE
|
|
Lam, MWY;
Wang, J;
Su, D;
Yu, D;
(2022)
BDDM: Bilateral Denoising Diffusion Models for Fast and High-Quality Speech Synthesis.
In:
ICLR 2022 - 10th International Conference on Learning Representations.
ICLR
|
|
Lam, MWY;
Wang, J;
Su, D;
Yu, D;
(2021)
Effective Low-Cost Time-Domain Audio Separation Using Globally Attentive Locally Recurrent Networks.
In:
Proceedings of the 2021 IEEE Spoken Language Technology Workshop (SLT).
(pp. pp. 801-808).
IEEE
|
|
Lam, MWY;
Wang, J;
Su, D;
Yuy, D;
(2021)
Sandglasset: A Light Multi-Granularity Self-Attentive Network for Time-Domain Speech Separation.
In:
Proceedings of the ICASSP 2021 - IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
(pp. pp. 5759-5763).
IEEE
|
|
Li, X;
Han, X;
Zhou, Z;
Yuan, M;
Zeng, J;
Wang, J;
(2021)
Grassland: A Rapid Algebraic Modeling System for Million-variable Optimization.
In: Demartini, G and Zuccon, G and Culpepper, JS and Huang, Z and Tong, H, (eds.)
CIKM '21: Proceedings of the 30th ACM International Conference on Information & Knowledge Management.
(pp. pp. 3925-3934).
Association for Computing Machinery (ACM): New York, NY, USA.
|
|
|
Li, Yang;
Yu, Cheng;
Sun, Guangzhi;
Jiang, Hua;
Sun, Fanglei;
Zu, Weiqin;
Wen, Ying;
... Wang, Jun; + view all
(2022)
Cross-Utterance Conditioned VAE for Non-Autoregressive Text-to-Speech.
In: Muresan, Smaranda and Nakov, Preslav and Villavicencio, Aline, (eds.)
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics.
(pp. pp. 391-400).
Association for Computational Linguistics (ACL): Dublin, Ireland.
|
|
Li, M;
Wu, L;
Ammar, HB;
Wang, J;
(2019)
Multi-View Reinforcement Learning.
In: Wallach, H and Larochelle, H and Beygelzimer, A and d'Alche-Buc, F and Fox, E and Garnett, R, (eds.)
Advances in Neural Information Processing Systems 32 (NIPS 2019).
Neural Information Processing Systems (NIPS): Vancouver, Canada.
|
|
|
Liu, B;
Feng, X;
Ren, J;
Mai, L;
Zhu, R;
Zhang, H;
Wang, J;
(2022)
A Theoretical Understanding of Gradient Bias in Meta-Reinforcement Learning.
In: Koyejo, S and Mohamed, S and Agarwal, A and Belgrave, D and Cho, K and Oh, A, (eds.)
Advances in Neural Information Processing Systems 35 (NeurIPS 2022).
NeurIPS Proceedings: New Orleans, LA, USA.
|
|
Lou, X;
Guo, J;
Zhang, J;
Wang, J;
Huang, K;
Du, Y;
(2023)
PECAN: Leveraging Policy Ensemble for Context-Aware Zero-Shot Human-AI Coordination.
In:
Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems.
(pp. pp. 679-688).
International Foundation for Autonomous Agents and Multiagent Systems
|
|
|
Luo, R;
Wang, J;
Yang, Y;
Zhu, Z;
Wang, J;
(2018)
Thermostat-assisted continuously-tempered Hamiltonian Monte Carlo for Bayesian learning.
In: Bengio, S and Wallach, H and Larochelle, H and Grauman, K and CesaBianchi, N and Garnett, R, (eds.)
Advances In Neural Information Processing Systems 31 (Nips 2018).
Neural Information Processing Systems Foundation, Inc.: Montreal, Canada.
|
|
|
Lyu, X;
Wang, J;
Zeng, T;
Li, X;
Chen, J;
Wang, X;
Xu, Z;
(2023)
TSS-Net: Two-stage with Sample selection and Semi-supervised Net for deep learning with noisy labels.
In:
Proceedings of SPIE - The International Society for Optical Engineering.
(pp. 125092F).
SPIE: Guangzhou, China.
|
|
Malherbe, C;
Grosnit, A;
Tutunov, R;
Wang, J;
Bou-Ammar, H;
(2022)
Optimistic tree search strategies for black-box combinatorial optimization.
In:
Proceedings of the Advances in Neural Information Processing Systems 35 (NeurIPS 2022).
NeurIPS
|
|
Mguni, D;
Jafferjee, T;
Wang, J;
Perez-Nieves, N;
Song, W;
Tong, F;
Taylor, ME;
... Yang, Y; + view all
(2023)
Learning to Shape Rewards Using a Game of Two Partners.
In: Williams, B and Chen, Y and Neville, J, (eds.)
Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI 2023).
(pp. pp. 11604-11612).
Association for the Advancement of Artifcial Intelligence: Washington, D.C., USA.
|
|
Mguni, D;
Jafferjee, T;
Wang, J;
Slumbers, O;
Perez-Nieves, N;
Tong, F;
Yang, L;
... Wang, J; + view all
(2022)
LIGS: Learnable Intrinsic-Reward Generation Selection for Multi-Agent Learning.
In:
ICLR 2022 - 10th International Conference on Learning Representations.
ICLR
|
|
Mguni, David;
Wu, Yutong;
Du, Yali;
Yang, Yaodong;
Wang, Ziyi;
Li, Minne;
Wen, Ying;
... Wang, Jun; + view all
(2021)
Learning in Nonzero-Sum Stochastic Games with Potentials.
In: Meila, M and Zhang, T, (eds.)
Proceedings of Machine Learning Research (PMLR).
MLResearchPress
|
|
|
Ng, I;
Zhu, S;
Fang, Z;
Li, H;
Chen, Z;
Wang, J;
(2022)
Masked Gradient-Based Causal Structure Learning.
In: Banerjee, Arindam and Zhou, Zhi-Hua and Papalexakis, Evangelos E. and Riondato, Matteo, (eds.)
Proceedings of the 2022 SIAM International Conference on Data Mining (SDM).
(pp. pp. 424-432).
Society for Industrial and Applied Mathematics
|
|
Nieves, Nicolas Perez;
Yang, Yaodong;
Slumbers, Oliver;
Mguni, David Henry;
Wen, Ying;
Wang, Jun;
(2021)
Modelling Behavioural Diversity for Learning in Open-Ended Games.
In: Meila, M and Zhang, T, (eds.)
Proceedings of Machine Learning Research (PMLR).
MLResearchPress
|
|
|
Peng, Z;
Jin, J;
Luo, L;
Yang, Y;
Luo, R;
Wang, J;
Zhang, W;
... Gai, K; + view all
(2020)
Learning to Infer User Hidden States for Online Sequential Advertising.
In: D'Aquin, M and Dietze, S and Hauff, C and Curry, E and Cudre Mauroux, P, (eds.)
CIKM '20: Proceedings of the 29th ACM International Conference on Information & Knowledge Management.
(pp. pp. 2677-2684).
Association for Computing Machinery (ACM): New York, NY, USA.
|
|
Qu, Y;
Cai, H;
Zhang, W;
Wen, Y;
Wang, J;
(2017)
Product-Based Neural Networks for User Response Prediction.
In: Bonchi, F and Domingo-Ferrer, J and Baeza-Yates, R and Zhou, ZH and Wu, Z, (eds.)
Proceedings of the 16th International Conference on Data Mining (ICDM).
(pp. pp. 1149-1154).
IEEE: Danvers (MA), USA.
|
|
|
Ren, H;
Sootla, A;
Jafferjee, T;
Shen, J;
Wang, J;
Bou-Ammar, H;
(2022)
Reinforcement Learning in Presence of Discrete Markovian Context Evolution.
In:
ICLR 2022 - 10th International Conference on Learning Representations.
ICLR
|
|
Ruan, J;
Du, Y;
Xiong, X;
Xing, D;
Li, X;
Meng, L;
Zhang, H;
... Xu, B; + view all
(2022)
GCS: Graph-Based Coordination Strategy for Multi-Agent Reinforcement Learning.
In:
AAMAS '22: Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems.
(pp. pp. 1128-1136).
ACM Press: New York, NY, USA.
|
|
Sloan, M;
Wang, J;
(2013)
Iterative Expectation for Multi Period Information Retrieval.
In:
WSDM Workshop on Web Search Click Data.
|
|
|
Slumbers, O;
Mguni, DH;
Blumberg, SB;
McAleer, S;
Yang, Y;
Wang, J;
(2023)
A Game-Theoretic Framework for Managing Risk in Multi-Agent Systems.
In:
Proceedings of the 40th International Conference on Machine Learning.
(pp. pp. 32059-32087).
PMLR 202: Honolulu, Hawaii, USA.
|
|
|
Song, W;
Wallwork, JG;
Tian, Z;
Piggott, MD;
Zhang, M;
Gao, J;
Sun, F;
... Wang, J; + view all
(2022)
M2N: Mesh Movement Networks for PDE Solvers.
In:
Advances in Neural Information Processing Systems.
|
|
Sootla, A;
Cowen-Rivers, AI;
Wang, J;
Ammar, HB;
(2022)
Enhancing Safe Exploration Using Safety State Augmentation.
In:
Advances in Neural Information Processing Systems.
|
|
Sootla, Aivar;
Cowen-Rivers, Alexander I;
Jafferjee, Taher;
Wang, Ziyan;
Mguni, David;
Wang, Jun;
Bou-Ammar, Haitham;
(2022)
Sauté RL: Almost Surely Safe Reinforcement Learning Using State Augmentation.
In: Chaudhuri, Kamalika and Jegelka, Stefanie and Song, Le and Szepesvari, Csaba and Niu, Gang and Sabato, Sivan, (eds.)
Volume 162: International Conference on Machine Learning, 17-23 July 2022, Baltimore, Maryland, USA.
(pp. pp. 20423-20443).
Journal of Machine Learning Research: Baltimore, MA, USA.
|
|
Tian, Y;
Wang, Q;
Huang, Z;
Li, W;
Dai, D;
Yang, M;
Wang, J;
(2020)
Off-Policy Reinforcement Learning for Efficient and Effective GAN Architecture Search.
In:
Computer Vision – ECCV 2020. ECCV 2020.
(pp. pp. 175-192).
Springer: Cham, Switzerland.
|
|
|
Tian, Z;
Wen, Y;
Gong, Z;
Punakkath, F;
Zou, S;
Wang, J;
(2019)
A regularized opponent model with maximum entropy objective.
In: Kraus, S, (ed.)
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence (IJCAI-19).
(pp. pp. 602-608).
International Joint Conferences on Artifical Intelligence (IJCAI): Macao, China.
|
|
Wang, H;
Sit, MK;
He, C;
Wen, Y;
Zhang, W;
Wang, J;
Yang, Y;
(2023)
GEAR: A GPU-Centric Experience Replay System for Large Reinforcement Learning Models.
In:
Proceedings of Machine Learning Research (PMLR).
(pp. pp. 36380-36390).
ML Research Press
|
|
|
Wang, J;
Lam, MWY;
Su, D;
Yu, D;
(2021)
Contrastive separative coding for self-supervised representation learning.
In:
Proceedings of the ICASSP - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
(pp. pp. 3865-3869).
IEEE
|
|
Wang, X;
Du, Y;
Zhu, S;
Ke, L;
Chen, Z;
Hao, J;
Wang, J;
(2021)
Ordering-Based Causal Discovery with Reinforcement Learning.
In:
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence (IJCAI-21).
(pp. pp. 3566-3573).
IJCAI International Joint Conferences on Artificial Intelligence Organization: Montreal, QC, Canada.
|
|
|
Wang, J;
Yu, L;
Zhang, W;
Gong, Y;
Xu, Y;
Wang, B;
Zhang, P;
(2017)
IRGAN: A minimax game for unifying generative and discriminative information retrieval models.
In:
SIGIR '17 - Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval.
(pp. pp. 515-524).
ACM: New York, NY, USA.
|
|
|
Wang, J;
Zhang, W;
(2016)
Bid-aware Gradient Descent for Unbiased Learning with Censored Data in Display Advertising.
In: Krishnapuram, B and Shah, M and Smola, A and Aggarwal, C and Shen, D and Rastogi, R, (eds.)
KDD '16: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.
(pp. pp. 665-674).
Association for Computing Machinery (ACM): New York, NY, USA.
|
|
|
Wang, W;
Jin, J;
Hao, J;
Chen, C;
Yu, C;
Zhang, W;
Wang, J;
... Gai, K; + view all
(2019)
Learning Adaptive Display Exposure for Real-Time Advertising.
In: Zhu, W and Tao, D and Cheng, X and Cui, P and Rundensteiner, E and Carmel, D and He, Q and Yu, JX, (eds.)
CIKM '19: Proceedings of the 28th ACM International Conference on Information and Knowledge Management.
(pp. pp. 2595-2603).
Association for Computing Machinery (ACM): New York, NY, USA.
|
|
|
Wang, X;
Yu, L;
Ren, K;
Tao, G;
Zhang, W;
Yu, Y;
Wang, J;
(2017)
Dynamic Attention Deep Model for Article Recommendation by Learning Human Editors' Demonstration.
In:
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.
(pp. pp. 2051-2059).
ACM
|
|
|
Wen, M;
Kuba, JG;
Lin, R;
Zhang, W;
Wen, Y;
Wang, J;
Yang, Y;
(2022)
Multi-Agent Reinforcement Learning is A Sequence Modeling Problem.
In:
Advances in Neural Information Processing Systems.
|
|
Wen, Y;
Chen, H;
Yang, Y;
Li, M;
Tian, Z;
Chen, X;
Wang, J;
(2023)
A Game-Theoretic Approach to Multi-agent Trust Region Optimization.
In: Yokoo, M and Qiao, H and Vorobeychik, Y and Hao, J, (eds.)
International Conference on Distributed Artificial Intelligence DAI 2022: Distributed Artificial Intelligence.
(pp. pp. 74-87).
Springer, Cham
|
|
Wen, Y;
Yang, Y;
Luo, R;
Wang, J;
Pan, W;
(2019)
Probabilistic recursive reasoning for multi-agent reinforcement learning.
In:
Proceedings of the 7th International Conference on Learning Representations (ICLR 2019).
International Conference on Learning Representations (ICLR): New Orleans, LA, USA.
|
|
|
Wen, Y;
zhang, W;
Luo, R;
Wang, J;
(2016)
Learning text representation using recurrent convolutional neural network with highway layers.
In:
Proceedings of the SIGIR 2016 Workshop on Neural Information Retrieval.
Association for Computing Machinery (ACM): Pisa, Italy.
|
|
Wu, Shuang;
Shi, Ling;
Wang, Jun;
Tian, Guangjian;
(2022)
Understanding Policy Gradient Algorithms: A Sensitivity-Based Approach.
In: Chaudhuri, K and Jegelka, S and Song, L and Szepesvari, C and Niu, G and Sabato, S, (eds.)
Proceedings of the 39th International Conference on Machine Learning.
(pp. pp. 24131-24149).
Proceedings of Machine Learning Research (PMLR): Baltimore, MD, USA.
|
|
Yan, Xue;
Du, Yali;
Ru, Binxin;
Wang, Jun;
Zhang, Haifeng;
Chen, Xu;
(2022)
Learning to Identify Top Elo Ratings: A Dueling Bandits Approach.
In:
Proceedings of the AAAI Conference on Artificial Intelligence.
(pp. pp. 8797-8805).
AAAI: Online.
|
|
Yang, M;
Cai, X;
Liu, F;
Zhang, W;
Wang, J;
(2023)
Specify Robust Causal Representation from Mixed Observations.
In:
Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.
(pp. pp. 2978-2987).
ACM (Association for Computing Machinery)
|
|
|
Yang, M;
Dai, Q;
Dong, Z;
Chen, X;
He, X;
Wang, J;
(2021)
Top-N Recommendation with Counterfactual User Preference Simulation.
In: Demartini, G and Zuccon, G and Culpepper, JS and Huang, Z and Tong, H, (eds.)
CIKM '21: Proceedings of the 30th ACM International Conference on Information & Knowledge Management.
(pp. pp. 2342-2351).
Association for Computing Machinery (ACM): New York, NY, USA.
|
|
|
Yang, M;
Wang, J;
Ton, JF;
(2023)
Rectifying Unfairness in Recommendation Feedback Loop.
In:
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '23).
(pp. pp. 28-37).
ACM (Association for Computing Machinery)
|
|
Yang, Mengyue;
Liu, Furui;
Chen, Zhitang;
Shen, Xinwei;
Hao, Jianye;
Wang, Jun;
(2021)
CausalVAE: Disentangled Representation Learning via Neural Structural Causal Models.
In:
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
(pp. pp. 9588-9597).
IEEE: Nashville, TN, USA.
|
|
|
Yang, Y;
Luo, R;
Li, M;
Zhou, M;
Zhang, W;
Wang, J;
(2018)
Mean Field Multi-Agent Reinforcement Learning.
In: Dy, J and Krause, A, (eds.)
Proceedings of the 35th International Conference on Machine Learning.
(pp. pp. 5571-5580).
PMLR
|
|
|
Yang, Y;
Wen, Y;
Yu, L;
Zhang, W;
Bai, Y;
Wang, J;
(2018)
A Study of AI Population Dynamics with Million-agent Reinforcement Learning.
In:
Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems.
(pp. pp. 2133-2135).
ACM
|
|
|
Yao, Y;
Ren, J;
Xie, X;
Liu, W;
Liu, Y-J;
Wang, J;
(2020)
Attention-aware Multi-stroke Style Transfer.
In:
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
(pp. pp. 1467-1475).
IEEE: Long Beach, CA, USA.
|
|
|
Yu, C;
Li, D;
Hao, J;
Wang, J;
Burgess, N;
(2022)
Learning State Representations via Retracing in Reinforcement Learning.
In:
ICLR 2022 - 10th International Conference on Learning Representations.
ICLR
|
|
Yu, C;
Li, Y;
Zu, W;
Sun, F;
Tian, Z;
Wang, J;
(2023)
Cross-utterance Conditioned Coherent Speech Editing.
In:
Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH.
(pp. pp. 2108-2112).
ISCA: Dublin, Ireland.
|
|
|
Yu, L;
Zhang, W;
Wang, J;
Yu, Y;
(2017)
Seqgan: sequence generative adversarial nets with policy gradient.
In:
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17).
(pp. pp. 2852-2858).
Association for the Advancement of Artificial Intelligence (AAAI)
(In press).
|
|
Yu, Y;
Wang, J;
(2018)
Learning multi-touch conversion attribution with dual-attention mechanisms for online advertising.
In:
(Proceedings) Proceedings of the 27th ACM International Conference on Information and Knowledge Management (CIKM '18).
(pp. pp. 1433-1442).
ACM: Torino, Italy.
|
|
|
Yuan, S;
Wang, J;
Zhao, X;
(2013)
Real-time bidding for online advertising: measurement and analysis.
In: Saka, E and Shen, D and Yan, J and Li, Y, (eds.)
ADKDD '13: Proceedings of the Seventh International Workshop on Data Mining for Online Advertising.
Association for Computing Machinery (ACM): New York, NY, United States.
|
|
|
Zhang, W;
Wang, J;
Chen, B;
Zhao, X;
(2013)
To personalize or not: A risk management perspective.
In:
(pp. pp. 229-236).
|
|
|
Zhang, Z;
Fang, M;
Chen, L;
Namazi-Rad, MR;
Wang, J;
(2023)
How Do Large Language Models Capture the Ever-changing World Knowledge? A Review of Recent Advances.
In:
EMNLP 2023 - 2023 Conference on Empirical Methods in Natural Language Processing, Proceedings.
(pp. pp. 8289-8311).
Association for Computational Linguistics (ACL): Singapore, Singapore.
|
|
|
Zhang, D;
Wang, J;
Yilmaz, E;
Wang, X;
Zhou, Y;
(2016)
Bayesian Performance Comparison of Text Classifiers.
In: Perego, R and Sebastiani, F and Lucchese, C, (eds.)
Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval.
(pp. pp. 15-24).
Association for Computing Machinery (ACM): New York, NY, USA.
|
|
|
Zhang, H;
Wang, J;
Zhou, Z;
Zhang, W;
Wen, Y;
Yu, Y;
Li, W;
(2018)
Learning to design games: Strategic environments in reinforcement learning.
In:
(pp. pp. 3068-3074).
ArXiv
|
|
|
Zhang, H;
Zhang, W;
Wang, J;
Rong, Y;
(2017)
Managing Risk of Bidding in Display Advertising.
In:
WSDM '17 Proceedings of the Tenth ACM International Conference on Web Search and Data Mining.
(pp. pp. 581-590).
Association for Computing Machinery (ACM): New York, NY, USA.
|
|
Zhao, X;
Zhang, W;
Wang, J;
(2013)
Interactive collaborative filtering.
In:
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management.
(pp. 1411 - 1420).
ACM: New York, NY, USA.
|
|
|
Zheng, L;
Yang, J;
Cai, H;
Zhang, W;
Wang, J;
Yu, Y;
(2018)
MAgent: A many-agent reinforcement learning platform for artificial collective intelligence.
In:
(Proceedings) 32nd AAAI Conference on Artificial Intelligence, AAAI 2018.
(pp. pp. 8222-8223).
AAAI: New Orleans, LA, USA.
|
|
|
Zhou, H;
Yang, M;
Wang, J;
Pan, W;
(2019)
BayesNAS: A Bayesian Approach for Neural Architecture Search.
In:
Proceedings of the 36th International Conference on Machine Learning.
(pp. pp. 7603-7613).
Proceedings of Machine Learning Research (PMLR): Long Beach, CA, USA.
|
|
|
Zhou, T;
Li, Z;
Cheng, G;
Wang, J;
Wei, Y;
(2020)
GREASE: A Generative Model for Relevance Search over Knowledge Graphs.
In:
Proceedings of the 13th International Conference on Web Search and Data Mining.
(pp. pp. 780-788).
The Association for Computing Machinery
|
|
|
Zhu, Y;
Lu, S;
Zheng, L;
Guo, J;
Zhang, W;
Wang, J;
Yu, Y;
(2018)
Texygen: A Benchmarking Platform for Text Generation Models.
In:
Proceedings of the 41st International ACM SIGIR Conference on Research & Development in Information Retrieval (SIGIR '18).
(pp. pp. 1097-1100).
ACM: New York (NY), USA.
|
Thesis
|
Wang, J;
(2008)
Relevance Models for Collaborative Filtering.
UNSPECIFIED thesis , UNSPECIFIED.
|
|
Wang, J;
(2002)
Detecting and tracking human faces in compressed domain for content based video indexing.
Masters thesis , UNSPECIFIED.
|
