Effective Off-Policy Evaluation and Learning in Contextual Combinatorial Bandits
Abstract
Supplemental Material
- Download
- 3.35 MB
References
Index Terms
- Effective Off-Policy Evaluation and Learning in Contextual Combinatorial Bandits
Recommendations
Variance-Minimizing Augmentation Logging for Counterfactual Evaluation in Contextual Bandits
WSDM '23: Proceedings of the Sixteenth ACM International Conference on Web Search and Data MiningMethods for offline A/B testing and counterfactual learning are seeing rapid adoption in search and recommender systems, since they allow efficient reuse of existing log data. However, there are fundamental limits to using existing log data alone, since ...
Contextual bandits with cross-learning
NIPS'19: Proceedings of the 33rd International Conference on Neural Information Processing SystemsIn the classical contextual bandits problem, in each round t, a learner observes some context c, chooses some action a to perform, and receives some reward ra,t(c). We consider the variant of this problem where in addition to receiving the reward ra,t(c′),...
Combinatorial neural bandits
ICML'23: Proceedings of the 40th International Conference on Machine LearningWe consider a contextual combinatorial bandit problem where in each round a learning agent selects a subset of arms and receives feedback on the selected arms according to their scores. The score of an arm is an unknown function of the arm's feature. ...
Comments
Information & Contributors
Information
Published In

Sponsors
- SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web
- SIGAI: ACM Special Interest Group on Artificial Intelligence
- SIGKDD: ACM Special Interest Group on Knowledge Discovery in Data
- SIGIR: ACM Special Interest Group on Information Retrieval
- SIGCHI: ACM Special Interest Group on Computer-Human Interaction
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Check for updates
Author Tags
Qualifiers
- Research-article
- Research
- Refereed limited
Conference
Acceptance Rates
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 234Total Downloads
- Downloads (Last 12 months)234
- Downloads (Last 6 weeks)17
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign inFull Access
View options
View or Download as a PDF file.
PDFeReader
View online with eReader.
eReaderHTML Format
View this article in HTML Format.
HTML Format