Adith Swaminathan

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 42

Top Topics

Risk Minimization

Recommendation Systems

Robust Estimator

Top Venues

Publications

Allen Nie, Ching-An Cheng, Andrey Kolobov, Adith Swaminathan
The Importance of Directional Feedback for LLM-based Optimizers. CoRR (2024)
Jiacen Xu, Jack W. Stokes, Geoff McDonald, Xuesong Bai, David Marshall, Siyue Wang, Adith Swaminathan, Zhou Li
AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks. CoRR (2024)
Ching-An Cheng, Allen Nie, Adith Swaminathan
Trace is the New AutoDiff - Unlocking Efficient Optimization of Computational Workflows. CoRR (2024)
Christine Herlihy, Jennifer Neville, Tobias Schnabel, Adith Swaminathan
On Overcoming Miscalibrated Conversational Priors in LLM-based Chatbots. CoRR (2024)
Huihan Liu, Alice Chen, Yuke Zhu, Adith Swaminathan, Andrey Kolobov, Ching-An Cheng
Interactive Robot Learning from Verbal Correction. CoRR (2023)
Ching-An Cheng, Andrey Kolobov, Dipendra Misra, Allen Nie, Adith Swaminathan
LLF-Bench: Benchmark for Interactive Learning from Language Feedback. CoRR (2023)
Sean R. Sinclair, Felipe Vieira Frujeri, Ching-An Cheng, Luke Marshall, Hugo De Oliveira Barbalho, Jingling Li, Jennifer Neville, Ishai Menache, Adith Swaminathan
Hindsight Learning for MDPs with Exogenous Inputs. ICML (2023)
Sean R. Sinclair, Felipe Frujeri, Ching-An Cheng, Adith Swaminathan
Hindsight Learning for MDPs with Exogenous Inputs. CoRR (2022)
Ching-An Cheng, Andrey Kolobov, Adith Swaminathan
Heuristic-Guided Reinforcement Learning. NeurIPS (2021)
Ching-An Cheng, Andrey Kolobov, Adith Swaminathan
Heuristic-Guided Reinforcement Learning. CoRR (2021)
Bogdan Mazoure, Paul Mineiro, Pavithra Srinath, Reza Sharifi Sedeh, Doina Precup, Adith Swaminathan
Improving Long-Term Metrics in Recommendation Systems using Short-Horizon Offline RL. CoRR (2021)
Thorsten Joachims, Ben London, Yi Su, Adith Swaminathan, Lequn Wang
Recommendations as Treatments. AI Mag. 42 (3) (2021)
Yao Liu, Adith Swaminathan, Alekh Agarwal, Emma Brunskill
Provably Good Batch Off-Policy Reinforcement Learning Without Great Exploration. NeurIPS (2020)
Ricky Loynd, Roland Fernandez, Asli Celikyilmaz, Adith Swaminathan, Matthew J. Hausknecht
Working Memory Graphs. ICML (2020)
Eric Zhan, Albert Tseng, Yisong Yue, Adith Swaminathan, Matthew J. Hausknecht
Learning Calibratable Policies using Programmatic Style-Consistency. ICML (2020)
Thorsten Joachims, Yves Raimond, Olivier Koch, Maria Dimakopoulou, Flavian Vasile, Adith Swaminathan
REVEAL 2020: Bandit and Reinforcement Learning from User Interactions. RecSys (2020)
Yao Liu, Adith Swaminathan, Alekh Agarwal, Emma Brunskill
Provably Good Batch Reinforcement Learning Without Great Exploration. CoRR (2020)
Aditya Modi, Debadeepta Dey, Alekh Agarwal, Adith Swaminathan, Besmira Nushi, Sean Andrist, Eric Horvitz
Metareasoning in Modular Software Systems: On-the-Fly Configuration Using Reinforcement Learning with Rich Contextual Representations. AAAI (2020)
Lin Ma, Bailu Ding, Sudipto Das, Adith Swaminathan
Active Learning for ML Enhanced Database Systems. SIGMOD Conference (2020)
J. Edward Hu, Adith Swaminathan, Hadi Salman, Greg Yang
Improved Image Wasserstein Attacks and Defenses. CoRR (2020)
Thorsten Joachims, Maria Dimakopoulou, Adith Swaminathan, Yves Raimond, Olivier Koch, Flavian Vasile
REVEAL 2019: closing the loop with the real world: reinforcement and robust estimators for recommendation. RecSys (2019)
Ricky Loynd, Roland Fernandez, Asli Celikyilmaz, Adith Swaminathan, Matthew J. Hausknecht
Working Memory Graphs. CoRR (2019)
Eric Zhan, Albert Tseng, Yisong Yue, Adith Swaminathan, Matthew J. Hausknecht
Learning Calibratable Policies using Programmatic Style-Consistency. CoRR (2019)
Maggie Makar, Adith Swaminathan, Emre Kiciman
A Distillation Approach to Data Efficient Individual Treatment Effect Estimation. AAAI (2019)
Yao Liu, Adith Swaminathan, Alekh Agarwal, Emma Brunskill
Off-Policy Policy Gradient with Stationary Distribution Correction. UAI (2019)
Aditya Modi, Debadeepta Dey, Alekh Agarwal, Adith Swaminathan, Besmira Nushi, Sean Andrist, Eric Horvitz
Metareasoning in Modular Software Systems: On-the-Fly Configuration using Reinforcement Learning with Rich Contextual Representations. CoRR (2019)
Yao Liu, Adith Swaminathan, Alekh Agarwal, Emma Brunskill
Off-Policy Policy Gradient with State Distribution Correction. CoRR (2019)
Matthew J. Hausknecht, Ricky Loynd, Greg Yang, Adith Swaminathan, Jason D. Williams
NAIL: A General Interactive Fiction Agent. CoRR (2019)
Ishan Durugkar, Matthew J. Hausknecht, Adith Swaminathan, Patrick MacAlpine
Multi-Preference Actor Critic. CoRR (2019)
Thorsten Joachims, Adith Swaminathan, Tobias Schnabel
Unbiased Learning-to-Rank with Biased Feedback. IJCAI (2018)
Thorsten Joachims, Adith Swaminathan, Yves Raimond, Olivier Koch, Flavian Vasile
REVEAL 2018: offline evaluation for recommender systems. RecSys (2018)
Thorsten Joachims, Adith Swaminathan, Maarten de Rijke
Deep Learning with Logged Bandit Feedback. ICLR (Poster) (2018)
Thorsten Joachims, Adith Swaminathan, Tobias Schnabel
Unbiased Learning-to-Rank with Biased Feedback. WSDM (2017)
Adith Swaminathan, Akshay Krishnamurthy, Alekh Agarwal, Miroslav Dudík, John Langford, Damien Jose, Imed Zitouni
Off-policy evaluation for slate recommendation. NIPS (2017)
Damien Lefortier, Adith Swaminathan, Xiaotao Gu, Thorsten Joachims, Maarten de Rijke
Large-scale Validation of Counterfactual Learning Methods: A Test-Bed. CoRR (2016)
Tobias Schnabel, Adith Swaminathan, Peter I. Frazier, Thorsten Joachims
Unbiased Comparative Evaluation of Ranking Functions. ICTIR (2016)
Thorsten Joachims, Adith Swaminathan, Tobias Schnabel
Unbiased Learning-to-Rank with Biased Feedback. CoRR (2016)
Adith Swaminathan, Akshay Krishnamurthy, Alekh Agarwal, Miroslav Dudík, John Langford, Damien Jose, Imed Zitouni
Off-policy evaluation for slate recommendation. CoRR (2016)
Tobias Schnabel, Adith Swaminathan, Peter I. Frazier, Thorsten Joachims
Unbiased Comparative Evaluation of Ranking Functions. CoRR (2016)
Thorsten Joachims, Adith Swaminathan
Counterfactual Evaluation and Learning for Search, Recommendation and Ad Placement. SIGIR (2016)
Tobias Schnabel, Adith Swaminathan, Ashudeep Singh, Navin Chandak, Thorsten Joachims
Recommendations as Treatments: Debiasing Learning and Evaluation. CoRR (2016)
Tobias Schnabel, Adith Swaminathan, Ashudeep Singh, Navin Chandak, Thorsten Joachims
Recommendations as Treatments: Debiasing Learning and Evaluation. ICML (2016)
Adith Swaminathan, Thorsten Joachims
Batch learning from logged bandit feedback through counterfactual risk minimization. J. Mach. Learn. Res. 16 (2015)
Adith Swaminathan, Thorsten Joachims
Counterfactual Risk Minimization. WWW (Companion Volume) (2015)
Tobias Schnabel, Adith Swaminathan, Thorsten Joachims
Unbiased Ranking Evaluation on a Budget. WWW (Companion Volume) (2015)
Adith Swaminathan, Thorsten Joachims
The Self-Normalized Estimator for Counterfactual Learning. NIPS (2015)
Adith Swaminathan, Thorsten Joachims
Counterfactual Risk Minimization: Learning from Logged Bandit Feedback. CoRR (2015)
Adith Swaminathan, Thorsten Joachims
Counterfactual Risk Minimization: Learning from Logged Bandit Feedback. ICML (2015)
Rakesh Agrawal, Maria Christoforaki, Sreenivas Gollapudi, Anitha Kannan, Krishnaram Kenthapadi, Adith Swaminathan
Mining Videos from the Web for Electronic Textbooks. ICFCA (2014)
Karthik Raman, Adith Swaminathan, Johannes Gehrke, Thorsten Joachims
Beyond myopic inference in big data pipelines. KDD (2013)
Ruben Sipos, Adith Swaminathan, Pannaga Shivaswamy, Thorsten Joachims
Temporal corpus summarization using submodular word coverage. CIKM (2012)