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Ben London 0001
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- affiliation: Amazon Music, WA, USA
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2020 – today
- 2024
- [c14]Alexander Buchholz, Ben London, Giuseppe Di Benedetto, Jan Malte Lichtenberg, Yannik Stein, Thorsten Joachims:
Counterfactual Ranking Evaluation with Flexible Click Models. SIGIR 2024: 1200-1210 - [c13]Bram van den Akker, Olivier Jeunen, Ying Li, Ben London, Zahra Nazari, Devesh Parekh:
Practical Bandits: An Industry Perspective. WSDM 2024: 1132-1135 - [e1]Tommaso Di Noia, Pasquale Lops, Thorsten Joachims, Katrien Verbert, Pablo Castells, Zhenhua Dong, Ben London:
Proceedings of the 18th ACM Conference on Recommender Systems, RecSys 2024, Bari, Italy, October 14-18, 2024. ACM 2024, ISBN 979-8-4007-0505-2 [contents] - 2023
- [c12]Ben London, Levi Lu, Ted Sandler, Thorsten Joachims:
Boosted Off-Policy Learning. AISTATS 2023: 5614-5640 - [c11]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: 55-61 - [c10]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: 648-658 - [i10]Bram van den Akker, Olivier Jeunen, Ying Li, Ben London, Zahra Nazari, Devesh Parekh:
Practical Bandits: An Industry Perspective. CoRR abs/2302.01223 (2023) - [i9]Jan Malte Lichtenberg, Alexander Buchholz, Giuseppe Di Benedetto, Matteo Ruffini, Ben London:
Double Clipping: Less-Biased Variance Reduction in Off-Policy Evaluation. CoRR abs/2309.01120 (2023) - [i8]Olivier Jeunen, Ben London:
Offline Recommender System Evaluation under Unobserved Confounding. CoRR abs/2309.04222 (2023) - 2022
- [i7]Ben London, Levi Lu, Ted Sandler, Thorsten Joachims:
Boosted Off-Policy Learning. CoRR abs/2208.01148 (2022) - [i6]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 abs/2210.09512 (2022) - 2021
- [j4]Thorsten Joachims, Ben London, Yi Su, Adith Swaminathan, Lequn Wang:
Recommendations as Treatments. AI Mag. 42(3): 19-30 (2021)
2010 – 2019
- 2019
- [j3]Ofer Meshi, Ben London, Adrian Weller, David A. Sontag:
Train and Test Tightness of LP Relaxations in Structured Prediction. J. Mach. Learn. Res. 20: 13:1-13:34 (2019) - [c9]Ben London, Ted Sandler:
Bayesian Counterfactual Risk Minimization. ICML 2019: 4125-4133 - 2018
- [c8]Sabina Tomkins, Steven Isley, Ben London, Lise Getoor:
Sustainability at scale: towards bridging the intention-behavior gap with sustainable recommendations. RecSys 2018: 214-218 - [i5]Ben London, Ted Sandler:
Bayesian Counterfactual Risk Minimization. CoRR abs/1806.11500 (2018) - 2017
- [c7]Ben London:
A PAC-Bayesian Analysis of Randomized Learning with Application to Stochastic Gradient Descent. NIPS 2017: 2931-2940 - [i4]Ben London:
A PAC-Bayesian Analysis of Randomized Learning with Application to Stochastic Gradient Descent. CoRR abs/1709.06617 (2017) - 2016
- [j2]Ben London, Bert Huang, Lise Getoor:
Stability and Generalization in Structured Prediction. J. Mach. Learn. Res. 17: 222:1-222:52 (2016) - [j1]Galileo Mark S. Namata Jr., Ben London, Lise Getoor:
Collective Graph Identification. ACM Trans. Knowl. Discov. Data 10(3): 25:1-25:36 (2016) - 2015
- [b1]Benjamin Alexei London:
On the Stability of Structured Prediction. University of Maryland, College Park, MD, USA, 2015 - [c6]Ben London, Bert Huang, Lise Getoor:
The Benefits of Learning with Strongly Convex Approximate Inference. ICML 2015: 410-418 - [c5]Jay Pujara, Ben London, Lise Getoor:
Budgeted Online Collective Inference. UAI 2015: 712-721 - 2014
- [c4]Ben London, Bert Huang, Ben Taskar, Lise Getoor:
PAC-Bayesian Collective Stability. AISTATS 2014: 585-594 - [p1]Ben London, Lise Getoor:
Collective Classification of Network Data. Data Classification: Algorithms and Applications 2014: 399-416 - 2013
- [c3]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: 566-571 - [c2]Ben London, Bert Huang, Ben Taskar, Lise Getoor:
Collective Stability in Structured Prediction: Generalization from One Example. ICML (3) 2013: 828-836 - [c1]Stephen H. Bach, Bert Huang, Ben London, Lise Getoor:
Hinge-loss Markov Random Fields: Convex Inference for Structured Prediction. UAI 2013 - [i3]Ben London, Bert Huang, Lise Getoor:
Graph-based Generalization Bounds for Learning Binary Relations. CoRR abs/1302.5348 (2013) - [i2]Ben London, Theodoros Rekatsinas, Bert Huang, Lise Getoor:
Multi-relational Learning Using Weighted Tensor Decomposition with Modular Loss. CoRR abs/1303.1733 (2013) - [i1]Stephen H. Bach, Bert Huang, Ben London, Lise Getoor:
Hinge-loss Markov Random Fields: Convex Inference for Structured Prediction. CoRR abs/1309.6813 (2013)
Coauthor Index
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