Joachims, Thorsten

68 publications

NeurIPS 2025 MultiScale Contextual Bandits for Long Term Objectives Richa Rastogi, Yuta Saito, Thorsten Joachims

ICLR 2025 POTEC: Off-Policy Contextual Bandits for Large Action Spaces via Policy Decomposition Yuta Saito, Jihan Yao, Thorsten Joachims

ICML 2024 Coactive Learning for Large Language Models Using Implicit User Feedback Aaron David Tucker, Kianté Brantley, Adam Cahall, Thorsten Joachims

ICMLW 2024 MultiScale Policy Learning for Alignment with Long Term Objectives Richa Rastogi, Yuta Saito, Thorsten Joachims

ICLRW 2024 Prompt Optimization with Logged Bandit Data Haruka Kiyohara, Yuta Saito, Daniel Yiming Cao, Thorsten Joachims

NeurIPS 2024 REBEL: Reinforcement Learning via Regressing Relative Rewards Zhaolin Gao, Jonathan D. Chang, Wenhao Zhan, Owen Oertell, Gokul Swamy, Kianté Brantley, Thorsten Joachims, J. Andrew Bagnell, Jason D. Lee, Wen Sun

ICMLW 2024 REBEL: Reinforcement Learning via Regressing Relative Rewards Zhaolin Gao, Jonathan Daniel Chang, Wenhao Zhan, Owen Oertell, Gokul Swamy, Kianté Brantley, Thorsten Joachims, J. Andrew Bagnell, Jason D. Lee, Wen Sun

ICMLW 2024 REBEL: Reinforcement Learning via Regressing Relative Rewards Zhaolin Gao, Jonathan Daniel Chang, Wenhao Zhan, Owen Oertell, Gokul Swamy, Kianté Brantley, Thorsten Joachims, J. Andrew Bagnell, Jason D. Lee, Wen Sun

UAI 2023 Bandits with Costly Reward Observations Aaron D. Tucker, Caleb Biddulph, Claire Wang, Thorsten Joachims

AISTATS 2023 Boosted Off-Policy Learning Ben London, Levi Lu, Ted Sandler, Thorsten Joachims

ICML 2023 Off-Policy Evaluation for Large Action Spaces via Conjunct Effect Modeling Yuta Saito, Qingyang Ren, Thorsten Joachims

NeurIPSW 2023 Policy-Gradient Training of Language Models for Ranking Ge Gao, Jonathan Daniel Chang, Claire Cardie, Kianté Brantley, Thorsten Joachims

NeurIPSW 2022 Bandits with Costly Reward Observations Aaron David Tucker, Caleb Biddulph, Claire Wang, Thorsten Joachims

ICML 2022 Improving Screening Processes via Calibrated Subset Selection Lequn Wang, Thorsten Joachims, Manuel Gomez Rodriguez

ICML 2022 Off-Policy Evaluation for Large Action Spaces via Embeddings Yuta Saito, Thorsten Joachims

IJCAI 2021 Controlling Fairness and Bias in Dynamic Learning-to-Rank (Extended Abstract) Marco Morik, Ashudeep Singh, Jessica Hong, Thorsten Joachims

NeurIPS 2021 Fairness in Ranking Under Uncertainty Ashudeep Singh, David Kempe, Thorsten Joachims

ICML 2021 Fairness of Exposure in Stochastic Bandits Lequn Wang, Yiwei Bai, Wen Sun, Thorsten Joachims

NeurIPS 2020 MOReL: Model-Based Offline Reinforcement Learning Rahul Kidambi, Aravind Rajeswaran, Praneeth Netrapalli, Thorsten Joachims

ICML 2019 CAB: Continuous Adaptive Blending for Policy Evaluation and Learning Yi Su, Lequn Wang, Michele Santacatterina, Thorsten Joachims

NeurIPS 2019 Policy Learning for Fairness in Ranking Ashudeep Singh, Thorsten Joachims

ICLR 2018 Deep Learning with Logged Bandit Feedback Thorsten Joachims, Adith Swaminathan, Maarten de Rijke

IJCAI 2018 Unbiased Learning-to-Rank with Biased Feedback Thorsten Joachims, Adith Swaminathan, Tobias Schnabel

ICML 2016 Recommendations as Treatments: Debiasing Learning and Evaluation Tobias Schnabel, Adith Swaminathan, Ashudeep Singh, Navin Chandak, Thorsten Joachims

JMLR 2015 Batch Learning from Logged Bandit Feedback Through Counterfactual Risk Minimization Adith Swaminathan, Thorsten Joachims

JAIR 2015 Coactive Learning Pannaga Shivaswamy, Thorsten Joachims

ICML 2015 Counterfactual Risk Minimization: Learning from Logged Bandit Feedback Adith Swaminathan, Thorsten Joachims

NeurIPS 2015 The Self-Normalized Estimator for Counterfactual Learning Adith Swaminathan, Thorsten Joachims

ICML 2014 Reducing Dueling Bandits to Cardinal Bandits Nir Ailon, Zohar Karnin, Thorsten Joachims

ECML-PKDD 2013 Learning Socially Optimal Information Systems from Egoistic Users Karthik Raman, Thorsten Joachims

NeurIPS 2013 Learning Trajectory Preferences for Manipulators via Iterative Improvement Ashesh Jain, Brian Wojcik, Thorsten Joachims, Ashutosh Saxena

ICML 2013 Stable Coactive Learning via Perturbation Karthik Raman, Thorsten Joachims, Pannaga Shivaswamy, Tobias Schnabel

ICCV 2013 Structured Learning of Sum-of-Submodular Higher Order Energy Functions Alexander Fix, Thorsten Joachims, Sung Min Park, Ramin Zabih

AISTATS 2012 Multi-Armed Bandit Problems with History Pannagadatta Shivaswamy, Thorsten Joachims

ICML 2012 Online Structured Prediction via Coactive Learning Pannaga Shivaswamy, Thorsten Joachims

ICML 2011 Beat the Mean Bandit Yisong Yue, Thorsten Joachims

NeurIPS 2011 Semantic Labeling of 3D Point Clouds for Indoor Scenes Hema S. Koppula, Abhishek Anand, Thorsten Joachims, Ashutosh Saxena

ECML-PKDD 2010 Fast Active Exploration for Link-Based Preference Learning Using Gaussian Processes Zhao Xu, Kristian Kersting, Thorsten Joachims

ICML 2010 Proceedings of the 27th International Conference on Machine Learning (ICML-10), June 21-24, 2010, Haifa, Israel Johannes Fürnkranz, Thorsten Joachims

MLJ 2009 Cutting-Plane Training of Structural SVMs Thorsten Joachims, Thomas Finley, Chun-Nam John Yu

ECML-PKDD 2009 Identifying the Original Contribution of a Document via Language Modeling Benyah Shaparenko, Thorsten Joachims

ICML 2009 Interactively Optimizing Information Retrieval Systems as a Dueling Bandits Problem Yisong Yue, Thorsten Joachims

ICML 2009 Learning Structural SVMs with Latent Variables Chun-Nam John Yu, Thorsten Joachims

ECML-PKDD 2009 Sparse Kernel SVMs via Cutting-Plane Training Thorsten Joachims, Chun-Nam John Yu

MLJ 2009 Sparse Kernel SVMs via Cutting-Plane Training Thorsten Joachims, Chun-Nam John Yu

COLT 2009 The K-Armed Dueling Bandits Problem Yisong Yue, Josef Broder, Robert Kleinberg, Thorsten Joachims

ICML 2008 Learning Diverse Rankings with Multi-Armed Bandits Filip Radlinski, Robert Kleinberg, Thorsten Joachims

ICML 2008 Predicting Diverse Subsets Using Structural SVMs Yisong Yue, Thorsten Joachims

ICML 2008 Training Structural SVMs When Exact Inference Is Intractable Thomas Finley, Thorsten Joachims

AAAI 2006 Minimally Invasive Randomization Fro Collecting Unbiased Preferences from Clickthrough Logs Filip Radlinski, Thorsten Joachims

ICML 2005 A Support Vector Method for Multivariate Performance Measures Thorsten Joachims

ICML 2005 Error Bounds for Correlation Clustering Thorsten Joachims, John E. Hopcroft

JMLR 2005 Large Margin Methods for Structured and Interdependent Output Variables Ioannis Tsochantaridis, Thorsten Joachims, Thomas Hofmann, Yasemin Altun

ICML 2005 Supervised Clustering with Support Vector Machines Thomas Finley, Thorsten Joachims

UAI 2005 Unstructuring User Preferences: Efficient Non-Parametric Utility Revelation Carmel Domshlak, Thorsten Joachims

ICML 2004 Support Vector Machine Learning for Interdependent and Structured Output Spaces Ioannis Tsochantaridis, Thomas Hofmann, Thorsten Joachims, Yasemin Altun

NeurIPS 2003 Learning a Distance Metric from Relative Comparisons Matthew Schultz, Thorsten Joachims

ICML 2003 Transductive Learning via Spectral Graph Partitioning Thorsten Joachims

ICML 2001 Composite Kernels for Hypertext Categorisation Thorsten Joachims, Nello Cristianini, John Shawe-Taylor

ICML 2000 Detecting Concept Drift with Support Vector Machines Ralf Klinkenberg, Thorsten Joachims

ICML 2000 Estimating the Generalization Performance of an SVM Efficiently Thorsten Joachims

ICML 1999 Combining Statistical Learning with a Knowledge-Based Approach - A Case Study in Intensive Care Monitoring Katharina Morik, Peter Brockhausen, Thorsten Joachims

ICML 1999 Expected Error Analysis for Model Selection Tobias Scheffer, Thorsten Joachims

ICML 1999 Transductive Inference for Text Classification Using Support Vector Machines Thorsten Joachims

AAAI 1998 Estimating the Expected Error of Empirical Minimizers for Model Selection Tobias Scheffer, Thorsten Joachims

ECML-PKDD 1998 Text Categorization with Support Vector Machines: Learning with Many Relevant Features Thorsten Joachims

ICML 1997 A Probabilistic Analysis of the Rocchio Algorithm with TFIDF for Text Categorization Thorsten Joachims

IJCAI 1997 Web Watcher: A Tour Guide for the World Wide Web Thorsten Joachims, Dayne Freitag, Tom M. Mitchell