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Thorsten Joachims

30 papers · 2005–2025 · 10 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge 🐝 Cross-Pollinator (4) πŸ—ΊοΈ Taxonomy Completionist (17) πŸƒ Academic Marathon (20) 🧭 Keyword Pioneer 🌍 Conference Polyglot (10) 🌟 Keyword Trendsetter Combo (5) 🌱 Topic Pioneer πŸ† Keyword Champion πŸ’Ž Century Club (30) πŸ“ˆ Trend Setter πŸš€ Conference Pioneer πŸ”₯ Unstoppable (8) πŸ—ƒοΈ Keyword Collector (50)

Conferences

ICML (10) NIPS (7) AISTATS (2) EMNLP (2) ICLR (2) IJCAI (2) JMLR (2) EACL (1) ICCV (1) UAI (1)

Top co-authors

Adith Swaminathan (6) Tobias Schnabel (4) Ashudeep Singh (4) Yuta Saito (3) Lequn Wang (3) Ashutosh Saxena (2) Pannaga Shivaswamy (2) Wen Sun (2) KiantΓ© Brantley (2) Zohar Karnin (1)

Keywords

contextual bandit (5) regret bound (4) multi-armed bandit (4) counterfactual risk minimization (3) bandit feedback (3) propensity scoring (2) off-policy evaluation (2) group fairness (2) policy evaluation (2) policy optimization (2) implicit feedback (2) off-policy learning (2) recommendation system (2) counterfactual learning (2) importance sampling (2) policy learning (2) online learning (2) importance weighting (2) learning to rank (2) inverse propensity score (2)

Papers

POTEC: Off-Policy Contextual Bandits for Large Action Spaces via Policy Decomposition ICLR 2025
REBEL: Reinforcement Learning via Regressing Relative Rewards NIPS 2024
Coactive Learning for Large Language Models using Implicit User Feedback ICML 2024
Off-Policy Evaluation for Large Action Spaces via Conjunct Effect Modeling ICML 2023
Boosted Off-Policy Learning AISTATS 2023
Bandits with costly reward observations UAI 2023
Improving Screening Processes via Calibrated Subset Selection ICML 2022
Off-Policy Evaluation for Large Action Spaces via Embeddings ICML 2022
Fairness in Ranking under Uncertainty NIPS 2021
Controlling Fairness and Bias in Dynamic Learning-to-Rank (Extended Abstract) IJCAI 2021
Fairness of Exposure in Stochastic Bandits ICML 2021
MOReL: Model-Based Offline Reinforcement Learning NIPS 2020
CAB: Continuous Adaptive Blending for Policy Evaluation and Learning ICML 2019
Policy Learning for Fairness in Ranking NIPS 2019
Deep Learning with Logged Bandit Feedback ICLR 2018
Unbiased Learning-to-Rank with Biased Feedback IJCAI 2018
Recommendations as Treatments: Debiasing Learning and Evaluation ICML 2016
Evaluation methods for unsupervised word embeddings EMNLP 2015
The Self-Normalized Estimator for Counterfactual Learning NIPS 2015
Counterfactual Risk Minimization: Learning from Logged Bandit Feedback ICML 2015
Batch Learning from Logged Bandit Feedback through Counterfactual Risk Minimization JMLR 2015
Invited Talk: Learning from Rational Behavior EMNLP 2014
Reducing Dueling Bandits to Cardinal Bandits ICML 2014
Stable Coactive Learning via Perturbation ICML 2013
Learning Trajectory Preferences for Manipulators via Iterative Improvement NIPS 2013
Structured Learning of Sum-of-Submodular Higher Order Energy Functions ICCV 2013
Large-Margin Learning of Submodular Summarization Models EACL 2012
Multi-armed Bandit Problems with History AISTATS 2012
Semantic Labeling of 3D Point Clouds for Indoor Scenes NIPS 2011
Large Margin Methods for Structured and Interdependent Output Variables JMLR 2005