Ben London - RankMe

32 papers A* 3A 9Journal 14Unranked 5

Year	Rank	Type	Title / Venue / Authors
2025	A	`conf`	Efficient Off-Policy Evaluation of Content Blending in Station-Based Music Experiences. RecSys Chelsea Weaver, Arvind Balasubramanian, Juan Borgnino, Ben London
2025	A	`conf`	Off-Policy Evaluation of Candidate Generators in Two-Stage Recommender Systems. RecSys Peiyao Wang, Zhan Shi, Amina Shabbeer, Ben London
2024	A*	`conf`	Counterfactual Ranking Evaluation with Flexible Click Models. SIGIR Alexander Buchholz, Ben London, Giuseppe Di Benedetto, Jan Malte Lichtenberg, Yannik Stein, Thorsten Joachims
2024	A	`conf`	Practical Bandits: An Industry Perspective. WSDM Bram van den Akker, Olivier Jeunen, Ying Li, Ben London, Zahra Nazari, Devesh Parekh
2024	A	`ed.`	Proceedings of the 18th ACM Conference on Recommender Systems, RecSys 2024, Bari, Italy, October 14-18, 2024 RecSys Tommaso Di Noia, Pasquale Lops, Thorsten Joachims, Katrien Verbert, Pablo Castells, Zhenhua Dong, Ben London
2023	A	`conf`	Boosted Off-Policy Learning. AISTATS Ben London, Levi Lu, Ted Sandler, Thorsten Joachims
2023	—	`conf`	Contextual Position Bias Estimation Using a Single Stochastic Logging Policy. LERI@RecSys Giuseppe Di Benedetto, Alexander Buchholz, Ben London, Matej Jakimov, Yannik Stein, Jan Malte Lichtenberg, Vito Bellini, Matteo Ruffini, Thorsten Joachims
2023	J	`jnl`	Double Clipping: Less-Biased Variance Reduction in Off-Policy Evaluation. CoRR Jan Malte Lichtenberg, Alexander Buchholz, Giuseppe Di Benedetto, Matteo Ruffini, Ben London
2023	J	`jnl`	Offline Recommender System Evaluation under Unobserved Confounding. CoRR Olivier Jeunen, Ben London
2023	J	`jnl`	Practical Bandits: An Industry Perspective. CoRR Bram van den Akker, Olivier Jeunen, Ying Li, Ben London, Zahra Nazari, Devesh Parekh
2023	—	`conf`	Tutorials at The Web Conference 2023. WWW (Companion Volume) Valeria Fionda, Olaf Hartig, Reyhaneh Abdolazimi, Sihem Amer-Yahia, Hongzhi Chen, Xiao Chen, Peng Cui, Jeffrey Dalton, Xin Luna Dong, Lisette Espín-Noboa, Wenqi Fan, Manuela Fritz, Quan Gan, Jingtong Gao, Xiaojie Guo, Torsten Hahmann, Jiawei Han, Soyeon Caren Han, Estevam Hruschka, Liang Hu, Jiaxin Huang, Utkarshani Jaimini, Olivier Jeunen, Yushan Jiang, Fariba Karimi, George Karypis, Krishnaram Kenthapadi, Himabindu Lakkaraju, Hady W. Lauw, Thai Le, Trung-Hoang Le, Dongwon Lee, Geon Lee, Liat Levontin, Cheng-Te Li, Haoyang Li, Ying Li, Jay Chiehen Liao, Qidong Liu, Usha Lokala, Ben London, Siqu Long, Hande Küçük-McGinty, Yu Meng, Seungwhan Moon, Usman Naseem, Pradeep Natarajan, Behrooz Omidvar-Tehrani, Zijie Pan, Devesh Parekh, Jian Pei, Tiago Peixoto, Steven Pemberton, Josiah Poon, Filip Radlinski, Federico Rossetto, Kaushik Roy, Aghiles Salah, Mehrnoosh Sameki, Amit P. Sheth, Cogan Shimizu, Kijung Shin, Dongjin Song, Julia Stoyanovich, Dacheng Tao, Johanne R. Trippas, Quoc Truong, Yu-Che Tsai, Adaku Uchendu, Bram van den Akker, Lin Wang, Minjie Wang, Shoujin Wang, Xin Wang, Ingmar Weber, Henry Weld, Lingfei Wu, Da Xu, Yifan Ethan Xu, Shuyuan Xu, Bo Yang, Ke Yang, Elad Yom-Tov, Jaemin Yoo, Zhou Yu, Reza Zafarani, Hamed Zamani, Meike Zehlike, Qi Zhang, Xikun Zhang, Yongfeng Zhang, Yu Zhang, Zheng Zhang, Liang Zhao, Xiangyu Zhao, Wenwu Zhu
2022	J	`jnl`	Boosted Off-Policy Learning. CoRR Ben London, Levi Lu, Ted Sandler, Thorsten Joachims
2022	J	`jnl`	Off-policy evaluation for learning-to-rank via interpolating the item-position model and the position-based model. CoRR Alexander Buchholz, Ben London, Giuseppe Di Benedetto, Thorsten Joachims
2021	J	`jnl`	Recommendations as Treatments. AI Mag. Thorsten Joachims, Ben London, Yi Su, Adith Swaminathan, Lequn Wang
2019	A*	`conf`	Bayesian Counterfactual Risk Minimization. ICML Ben London, Ted Sandler
2019	J	`jnl`	Train and Test Tightness of LP Relaxations in Structured Prediction. J. Mach. Learn. Res. Ofer Meshi, Ben London, Adrian Weller, David A. Sontag
2018	J	`jnl`	Bayesian Counterfactual Risk Minimization. CoRR Ben London, Ted Sandler
2018	A	`conf`	Sustainability at scale: towards bridging the intention-behavior gap with sustainable recommendations. RecSys Sabina Tomkins, Steven Isley, Ben London, Lise Getoor
2017	—	`conf`	A PAC-Bayesian Analysis of Randomized Learning with Application to Stochastic Gradient Descent. NIPS Ben London
2017	J	`jnl`	A PAC-Bayesian Analysis of Randomized Learning with Application to Stochastic Gradient Descent. CoRR Ben London
2016	J	`jnl`	Collective Graph Identification. ACM Trans. Knowl. Discov. Data Galileo Mark S. Namata Jr., Ben London, Lise Getoor
2016	J	`jnl`	Stability and Generalization in Structured Prediction. J. Mach. Learn. Res. Ben London, Bert Huang, Lise Getoor
2015	A	`conf`	Budgeted Online Collective Inference. UAI Jay Pujara, Ben London, Lise Getoor
2015	A*	`conf`	The Benefits of Learning with Strongly Convex Approximate Inference. ICML Ben London, Bert Huang, Lise Getoor
2014	—	`ch.`	Collective Classification of Network Data. Data Classification: Algorithms and Applications Ben London, Lise Getoor
2014	A	`conf`	PAC-Bayesian Collective Stability. AISTATS Ben London, Bert Huang, Ben Taskar, Lise Getoor
2013	—	`conf`	Collective Activity Detection Using Hinge-loss Markov Random Fields. CVPR Workshops Ben London, Sameh Khamis, Stephen H. Bach, Bert Huang, Lise Getoor, Larry S. Davis
2013	—	`conf`	Collective Stability in Structured Prediction: Generalization from One Example. ICML (3) Ben London, Bert Huang, Ben Taskar, Lise Getoor
2013	J	`jnl`	Graph-based Generalization Bounds for Learning Binary Relations CoRR Ben London, Bert Huang, Lise Getoor
2013	A	`conf`	Hinge-loss Markov Random Fields: Convex Inference for Structured Prediction. UAI Stephen H. Bach, Bert Huang, Ben London, Lise Getoor
2013	J	`jnl`	Hinge-loss Markov Random Fields: Convex Inference for Structured Prediction. CoRR Stephen H. Bach, Bert Huang, Ben London, Lise Getoor
2013	J	`jnl`	Multi-relational Learning Using Weighted Tensor Decomposition with Modular Loss CoRR Ben London, Theodoros Rekatsinas, Bert Huang, Lise Getoor