Ben London

According to our database, Ben London authored at least 24 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Practical Bandits: An Industry Perspective.

Bram van den Akker, Olivier Jeunen, Ying Li, Ben London, Zahra Nazari, Devesh Parekh

Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

2023

Offline Recommender System Evaluation under Unobserved Confounding.

Olivier Jeunen, Ben London

CoRR, 2023

Double Clipping: Less-Biased Variance Reduction in Off-Policy Evaluation.

Jan Malte Lichtenberg, Alexander Buchholz, Giuseppe Di Benedetto, Matteo Ruffini, Ben London

CoRR, 2023

Tutorials at The Web Conference 2023.

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

Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

Contextual Position Bias Estimation Using a Single Stochastic Logging Policy.

Giuseppe Di Benedetto, Alexander Buchholz, Ben London, Matej Jakimov, Yannik Stein, Jan Malte Lichtenberg, Vito Bellini, Matteo Ruffini, Thorsten Joachims

Proceedings of the Workshop on Learning and Evaluating Recommendations with Impressions co-located with the 17th ACM Conference on Recommender Systems (RecSys 2023), 2023

Boosted Off-Policy Learning.

Ben London, Levi Lu, Ted Sandler, Thorsten Joachims

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Off-policy evaluation for learning-to-rank via interpolating the item-position model and the position-based model.

Alexander Buchholz, Ben London, Giuseppe Di Benedetto, Thorsten Joachims

CoRR, 2022

2021

Recommendations as Treatments.

Thorsten Joachims, Ben London, Yi Su, Adith Swaminathan, Lequn Wang

AI Mag., 2021

2019

Train and Test Tightness of LP Relaxations in Structured Prediction.

Ofer Meshi, Ben London, Adrian Weller, David A. Sontag

J. Mach. Learn. Res., 2019

Bayesian Counterfactual Risk Minimization.

Ben London, Ted Sandler

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Sustainability at scale: towards bridging the intention-behavior gap with sustainable recommendations.

Sabina Tomkins, Steven Isley, Ben London, Lise Getoor

Proceedings of the 12th ACM Conference on Recommender Systems, 2018

2017

A PAC-Bayesian Analysis of Randomized Learning with Application to Stochastic Gradient Descent.

Ben London

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016

Collective Graph Identification.

Galileo Mark S. Namata Jr., Ben London, Lise Getoor

ACM Trans. Knowl. Discov. Data, 2016

Stability and Generalization in Structured Prediction.

Ben London, Bert Huang, Lise Getoor

J. Mach. Learn. Res., 2016

2015

On the Stability of Structured Prediction.

Benjamin Alexei London

PhD thesis, 2015

Budgeted Online Collective Inference.

Jay Pujara, Ben London, Lise Getoor

Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

The Benefits of Learning with Strongly Convex Approximate Inference.

Ben London, Bert Huang, Lise Getoor

Proceedings of the 32nd International Conference on Machine Learning, 2015

2014

PAC-Bayesian Collective Stability.

Ben London, Bert Huang, Ben Taskar, Lise Getoor

Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

Collective Classification of Network Data.

Ben London, Lise Getoor

Proceedings of the Data Classification: Algorithms and Applications, 2014

2013

Multi-relational Learning Using Weighted Tensor Decomposition with Modular Loss

Ben London, Theodoros Rekatsinas, Bert Huang, Lise Getoor

CoRR, 2013

Graph-based Generalization Bounds for Learning Binary Relations

Ben London, Bert Huang, Lise Getoor

CoRR, 2013

Hinge-loss Markov Random Fields: Convex Inference for Structured Prediction.

Stephen H. Bach, Bert Huang, Ben London, Lise Getoor

Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

Collective Stability in Structured Prediction: Generalization from One Example.

Ben London, Bert Huang, Ben Taskar, Lise Getoor

Proceedings of the 30th International Conference on Machine Learning, 2013

Collective Activity Detection Using Hinge-loss Markov Random Fields.

Ben London, Sameh Khamis, Stephen H. Bach, Bert Huang, Lise Getoor, Larry S. Davis

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2013