Distributed Real-Time Economic Dispatch in Smart Grids: A State-Based Potential Game Approach. - Yile Liang; Feng Liu 014; Shengwei Mei (IEEE Trans. Smart Grid, 2018)

Align Reviews with Topics in Attention Network for Rating Prediction. - Yile Liang; Tieyun Qian; Huilin Yu (DASFAA (3), 2019)

Solving Cold Start Problem in Recommendation with Attribute Graph Neural Networks. - Tieyun Qian; Yile Liang; Qing Li 001 (CoRR, 2019)

A Generalized Nash Equilibrium Approach for Autonomous Energy Management of Residential Energy Hubs. - Yile Liang; Wei Wei 007; Cheng Wang 017 (IEEE Trans. Ind. Informatics, 2019)

Where to Go Next: Modeling Long- and Short-Term User Preferences for Point-of-Interest Recommendation. - Ke Sun 010; Tieyun Qian; Tong Chen 005; Yile Liang; Quoc Viet Hung Nguyen; Hongzhi Yin (AAAI, 2020)

Adversarial Generation of Target Review for Rating Prediction. - Huilin Yu; Tieyun Qian; Yile Liang; Bing Liu 001 (DASFAA (2), 2020)

AGTR: Adversarial Generation of Target Review for Rating Prediction. - Huilin Yu; Tieyun Qian; Yile Liang; Bing Liu 001 (Data Sci. Eng., 2020)

ARTAN: Align reviews with topics in attention network for rating prediction. - Yile Liang; Tieyun Qian; Huilin Yu (Neurocomputing, 2020)

Data-Driven Wind Generation Admissibility Assessment of Integrated Electric-Heat Systems: A Dynamic Convex Hull-Based Approach. - Cheng Wang 017; Zhihao Gong; Yile Liang; Wei Wei 007; Tianshu Bi (IEEE Trans. Smart Grid, 2020)

Enhancing Domain-Level and User-Level Adaptivity in Diversified Recommendation. - Yile Liang; Tieyun Qian; Qing Li 001; Hongzhi Yin (SIGIR, 2021)

Recommending Accurate and Diverse Items Using Bilateral Branch Network. - Yile Liang; Tieyun Qian (CoRR, 2021)

Intent Disentanglement and Feature Self-supervision for Novel Recommendation. - Tieyun Qian; Yile Liang; Qing Li 001; Xuan Ma; Ke Sun 006; Zhiyong Peng 001 (CoRR, 2021)

Enhancing Graph Convolution Network for Novel Recommendation. - Xuan Ma; Tieyun Qian; Yile Liang; Ke Sun 010; Hang Yun; Mi Zhang 006 (DASFAA (2), 2022)

Investigating Accuracy-Novelty Performance for Graph-based Collaborative Filtering. - Minghao Zhao 002; Le Wu; Yile Liang; Lei Chen 051; Jian Zhang 023; Qilin Deng; Kai Wang 064; Xudong Shen; Tangjie Lv; Runze Wu 001 (SIGIR, 2022)

Dynamic multi-objective balancing for online food delivery via fuzzy logic system-based supply-demand relationship identification. - Jie Zheng 001; Ling Wang 001; Jingfang Chen 001; Xing Wang 015; Yile Liang; Haining Duan; Zixuan Li; Xuetao Ding (Comput. Ind. Eng., 2022)

Attribute Graph Neural Networks for Strict Cold Start Recommendation. - Tieyun Qian; Yile Liang; Qing Li 001; Hui Xiong 001 (IEEE Trans. Knowl. Data Eng., 2022)

RL4RS Dataset. - Kai Wang 064; Zhene Zou; Yue Shang; Qilin Deng; Minghao Zhao 002; Yile Liang; Runze Wu 001; Xudong Shen; Jianrong Tao; Tangjie Lyu; Changjie Fan (Zenodo, 2022)

Enhancing Dynamic On-demand Food Order Dispatching via Future-informed and Spatial-temporal Extended Decisions. - Yile Liang; Donghui Li; Jiuxia Zhao; Xuetao Ding; Huanjia Lian; Jinghua Hao; Renqing He (CIKM, 2023)

Attribute Graph Neural Networks for Strict Cold Start Recommendation : Extended Abstract. - Tieyun Qian; Yile Liang; Qing Li 001; Hui Xiong 001 (ICDE, 2023)

RL4RS: A Real-World Dataset for Reinforcement Learning based Recommender System. - Kai Wang 064; Zhene Zou; Minghao Zhao 002; Qilin Deng; Yue Shang; Yile Liang; Runze Wu 001; Xudong Shen; Tangjie Lyu; Changjie Fan (SIGIR, 2023)

Intent Disentanglement and Feature Self-Supervision for Novel Recommendation. - Tieyun Qian; Yile Liang; Qing Li 001; Xuan Ma; Ke Sun 010; Zhiyong Peng 001 (IEEE Trans. Knowl. Data Eng., 2023)

A Predictive-Reactive Optimization Framework With Feedback-Based Knowledge Distillation for On-Demand Food Delivery. - Jie Zheng 001; Ling Wang 001; Jingfang Chen 001; Zi-Xiao Pan; Donghui Li; Yile Liang; Xuetao Ding (IEEE Trans. Intell. Transp. Syst., 2023)

Harvesting Efficient On-Demand Order Pooling from Skilled Couriers: Enhancing Graph Representation Learning for Refining Real-time Many-to-One Assignments. - Yile Liang; Jiuxia Zhao; Donghui Li; Jie Feng 002; Chen Zhang; Xuetao Ding; Jinghua Hao; Renqing He (KDD, 2024)

Harvesting Efficient On-Demand Order Pooling from Skilled Couriers: Enhancing Graph Representation Learning for Refining Real-time Many-to-One Assignments. - Yile Liang; Jiuxia Zhao; Donghui Li; Jie Feng; Chen Zhang; Xuetao Ding; Jinghua Hao; Renqing He (CoRR, 2024)

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization. - Zongkai Liu; Qian Lin; Chao Yu 004; Xiawei Wu; Yile Liang; Donghui Li; Xuetao Ding (CoRR, 2024)

Meituan's Real-Time Intelligent Dispatching Algorithms Build the World's Largest Minute-Level Delivery Network. - Yile Liang; Haocheng Luo; Haining Duan; Donghui Li; Hongsen Liao; Jie Feng; Jiuxia Zhao; Hao Ren; Xuetao Ding; Ying Cha; Qingte Zhou; Chenqi Situ; et al. (INFORMS J. Appl. Anal., 2024)

Order Dispatching Via GNN-Based Optimization Algorithm for On-Demand Food Delivery. - Jingfang Chen 001; Ling Wang 001; Yile Liang; Yang Yu 005; Jie Feng; Jiuxia Zhao; Xuetao Ding (IEEE Trans. Intell. Transp. Syst., 2024)

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization. - Zongkai Liu; Qian Lin; Chao Yu; Xiawei Wu; Yile Liang; Donghui Li; Xuetao Ding (AAAI, 2025)