Ben London

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 19

Top Topics

Structured Prediction

Collective Inference

Top Venues

J. Mach. Learn. Res.

Publications

Alexander Buchholz, Ben London, Giuseppe Di Benedetto, Jan Malte Lichtenberg, Yannik Stein, Thorsten Joachims
Counterfactual Ranking Evaluation with Flexible Click Models. SIGIR (2024)
Bram van den Akker, Olivier Jeunen, Ying Li, Ben London, Zahra Nazari, Devesh Parekh
Practical Bandits: An Industry Perspective. WSDM (2024)
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 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
Tutorials at The Web Conference 2023. WWW (Companion Volume) (2023)
Ben London, Levi Lu, Ted Sandler, Thorsten Joachims
Boosted Off-Policy Learning. AISTATS (2023)
Bram van den Akker, Olivier Jeunen, Ying Li, Ben London, Zahra Nazari, Devesh Parekh
Practical Bandits: An Industry Perspective. CoRR (2023)
Jan Malte Lichtenberg, Alexander Buchholz, Giuseppe Di Benedetto, Matteo Ruffini, Ben London
Double Clipping: Less-Biased Variance Reduction in Off-Policy Evaluation. CoRR (2023)
Olivier Jeunen, Ben London
Offline Recommender System Evaluation under Unobserved Confounding. CoRR (2023)
Giuseppe Di Benedetto, Alexander Buchholz, Ben London, Matej Jakimov, Yannik Stein, Jan Malte Lichtenberg, Vito Bellini, Matteo Ruffini, Thorsten Joachims
Contextual Position Bias Estimation Using a Single Stochastic Logging Policy. LERI@RecSys (2023)
Ben London, Levi Lu, Ted Sandler, Thorsten Joachims
Boosted Off-Policy Learning. CoRR (2022)
Alexander Buchholz, Ben London, Giuseppe Di Benedetto, Thorsten Joachims
Off-policy evaluation for learning-to-rank via interpolating the item-position model and the position-based model. CoRR (2022)
Thorsten Joachims, Ben London, Yi Su, Adith Swaminathan, Lequn Wang
Recommendations as Treatments. AI Mag. 42 (3) (2021)
Ben London, Ted Sandler
Bayesian Counterfactual Risk Minimization. ICML (2019)
Ofer Meshi, Ben London, Adrian Weller, David A. Sontag
Train and Test Tightness of LP Relaxations in Structured Prediction. J. Mach. Learn. Res. 20 (2019)
Sabina Tomkins, Steven Isley, Ben London, Lise Getoor
Sustainability at scale: towards bridging the intention-behavior gap with sustainable recommendations. RecSys (2018)
Ben London, Ted Sandler
Bayesian Counterfactual Risk Minimization. CoRR (2018)
Ben London
A PAC-Bayesian Analysis of Randomized Learning with Application to Stochastic Gradient Descent. CoRR (2017)
Ben London
A PAC-Bayesian Analysis of Randomized Learning with Application to Stochastic Gradient Descent. NIPS (2017)
Ben London, Bert Huang, Lise Getoor
Stability and Generalization in Structured Prediction. J. Mach. Learn. Res. 17 (2016)
Galileo Mark S. Namata Jr., Ben London, Lise Getoor
Collective Graph Identification. ACM Trans. Knowl. Discov. Data 10 (3) (2016)
Ben London, Bert Huang, Lise Getoor
The Benefits of Learning with Strongly Convex Approximate Inference. ICML (2015)
Jay Pujara, Ben London, Lise Getoor
Budgeted Online Collective Inference. UAI (2015)
Ben London, Bert Huang, Ben Taskar, Lise Getoor
PAC-Bayesian Collective Stability. AISTATS (2014)
Stephen H. Bach, Bert Huang, Ben London, Lise Getoor
Hinge-loss Markov Random Fields: Convex Inference for Structured Prediction. CoRR (2013)
Ben London, Theodoros Rekatsinas, Bert Huang, Lise Getoor
Multi-relational Learning Using Weighted Tensor Decomposition with Modular Loss CoRR (2013)
Ben London, Sameh Khamis, Stephen H. Bach, Bert Huang, Lise Getoor, Larry S. Davis
Collective Activity Detection Using Hinge-loss Markov Random Fields. CVPR Workshops (2013)
Stephen H. Bach, Bert Huang, Ben London, Lise Getoor
Hinge-loss Markov Random Fields: Convex Inference for Structured Prediction. UAI (2013)
Ben London, Bert Huang, Ben Taskar, Lise Getoor
Collective Stability in Structured Prediction: Generalization from One Example. ICML (3) (2013)
Ben London, Bert Huang, Lise Getoor
Graph-based Generalization Bounds for Learning Binary Relations CoRR (2013)