AG百家乐代理-红桃KAG百家乐娱乐城_百家乐筹码片_新全讯网网址xb112 (中国)·官方网站

師資

EN       返回上一級       師資搜索
孔芳
助理教授
kongf@sustech.edu.cn

研究領域

在線學習,強化學習,機器學習


教育經歷

2020.9-2024.6 上海交通大學,計算機科學與技術,工學博士

2016.9-2020.6 山東大學,軟件工程,工學學士


科研經歷

2023.2-2023.8 香港中文大學,科研助理

2022.7-2024.7 騰訊WXG,研究型實習生

2021.12-2022.5 微軟亞洲研究院,研究型實習生

2021.6-2021.8 阿里巴巴達摩院,研究型實習生


學術成果

  1. Yu Xia*, Fang Kong*, Tong Yu, Liya Guo, Ryan A. Rossi, Sungchul Kim, Shuai Li, “Convergence-Aware Online Model Selection with Time-Increasing Bandits”, The Web Conference (WWW), 2024.

  2. Fang Kong, Shuai Li, “Improved Bandits in Many-to-one Matching Markets with Incentive Compatibility”, Proceedings of the 38th Annual AAAI Conference on Artificial Intelligence (AAAI), 2024. 

  3. Fang Kong*, Xiangcheng Zhang*, Baoxiang Wang, Shuai Li, “Improved Regret Bounds for Linear Adversarial MDPs via Linear Optimization”, Transactions on Machine Learning Research (TMLR), 2024.

  4. Fang Kong, Canzhe Zhao, Shuai Li, “Best-of-three-worlds Analysis for Linear Bandits with Follow-the-regularized-leader Algorithm”, Proceedings of the 36th Conference on Learning Theory (COLT), 2023.

  5. Fang Kong, Jize Xie, Baoxiang Wang, Tao Yao, Shuai Li. “Online Influence Maximization under Decreasing Cascade Model”, Proceedings of the 22nd International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2023.

  6. Yichi Zhou, Fang Kong, Shuai Li, “Stochastic No-Regret Learning for General Games with Variance Reduction”, International Conference on Learning Representations (ICLR), 2023.

  7. Fang Kong, Shuai Li, “Player-optimal Stable Regret for Bandit Learning in Matching Markets”, Proceedings of the 2023 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA). 2023.

  8. Fang Kong, Yichi Zhou, Shuai Li, “Simultaneously Learning Stochastic and Adversarial Bandits with General Graph Feedback”, International Conference on Machine Learning (ICML), 2022.

  9. Fang Kong, Junming Yin, Shuai Li, “Thompson Sampling for Bandit Learning in Matching Markets”, International Joint Conference on Artificial Intelligence (IJCAI), 2022.

  10. Fang Kong, Yueran Yang, Wei Chen, Shuai Li, “The Hardness Analysis of Thompson Sampling for Combinatorial Semi-bandits with Greedy Oracle”, Proceedings of the Conference on Neural Information Processing Systems (NeurIPS), 2021.

  11. Fang Kong, Yueran Yang, Wei Chen, Shuai Li, “Combinatorial Online Learning based on Optimizing Feedbacks (in Chinese)”, Big Data Research, 2021.

  12. Shuai Li, Fang Kong, Kejie Tang, Qizhi Li, Wei Chen, “Online Influence Maximization under Linear Threshold Model”, Proceedings of the Conference on Neural Information Processing Systems (NeurIPS), 2020.

  13. Fang Kong, Qizhi Li, Shuai Li, “A Survey on Online Influence Maximization” (in Chinese), Computer Science, 2020.



百家乐官网庄闲几率| 百家乐官网游戏程序出售| 威尼斯人娱乐城吃饭| 迪威网上娱乐| 百家乐最低下注| 库车县| 百家乐在线娱乐网| 沅陵县| 现场百家乐能赢吗| 百家乐官网赌博详解| 上游棋牌大厅| 百家乐路纸表格| 百家乐官网真人游戏网| 赌场百家乐是如何玩| 百家乐官网有多少种游戏| 送彩金百家乐平台| 百家乐官网连黑记录| 实战百家乐的玩法技巧和规则| 机器百家乐官网心得| 同花順国际娱乐城| 百家乐款| 哪个百家乐官网投注比较好| 四海资迅| 郑州市太阳城宾馆| 百家乐mediacorp| 圣淘沙百家乐官网的玩法技巧和规则 | 百家乐官网高额投注| 金冠娱乐城怎么样| 电子百家乐技巧| 百家乐官网娱乐真人娱乐| 澳门博彩股份有限公司| 百家乐这样赢保单分析| 百家乐登封代理| 现金百家乐官网破解| 深水埗区| 娱乐城送体验金| 大发888信誉娱乐城管理| 澳门赌百家乐的玩法技巧和规则| 线上百家乐官网信誉| 大发888娱乐城出纳柜台| 东京太阳城王子酒店|