Counterfactual Reasoning and Learning Systems

11 September 2012

Papers citing "Counterfactual Reasoning and Learning Systems"

50 / 363 papers shown

Title
MARS-Gym: A Gym framework to model, train, and evaluate Recommender Systems for Marketplaces Marlesson R. O. Santana Luckeciano C. Melo Fernando H. F. Camargo Bruno Brandão Anderson Soares Renan M. Oliveira Sandor Caetano OffRL 8 15 0 30 Sep 2020
Targeted VAE: Variational and Targeted Learning for Causal Inference M. Vowels Necati Cihan Camgöz Richard Bowden BDL OOD CML 19 8 0 28 Sep 2020
Probabilistic Machine Learning for Healthcare Irene Y. Chen Shalmali Joshi Marzyeh Ghassemi Rajesh Ranganath OOD 11 52 0 23 Sep 2020
Conditionally Adaptive Multi-Task Learning: Improving Transfer Learning in NLP Using Fewer Parameters & Less Data Jonathan Pilault Amine Elhattami C. Pal CLL MoE 30 89 0 19 Sep 2020
Competing AI: How does competition feedback affect machine learning? Antonio A. Ginart Eva Zhang Yongchan Kwon James Zou AAML 20 0 0 15 Sep 2020
BLOB : A Probabilistic Model for Recommendation that Combines Organic and Bandit Signals Otmane Sakhi Stephen Bonner D. Rohde Flavian Vasile 30 34 0 28 Aug 2020
Hi-CI: Deep Causal Inference in High Dimensions Ankit Sharma Garima Gupta Ranjitha Prasad Arnab Chatterjee L. Vig Gautam M. Shroff BDL CML 14 4 0 22 Aug 2020
Open Bandit Dataset and Pipeline: Towards Realistic and Reproducible Off-Policy Evaluation Yuta Saito Shunsuke Aihara Megumi Matsutani Yusuke Narita OffRL 24 73 0 17 Aug 2020
Accountable Off-Policy Evaluation With Kernel Bellman Statistics Yihao Feng Tongzheng Ren Ziyang Tang Qiang Liu OffRL 10 42 0 15 Aug 2020
Unbiased Learning for the Causal Effect of Recommendation Masahiro Sato S. Takemori Janmajay Singh Tomoko Ohkuma CML OffRL 17 69 0 11 Aug 2020
Predicting Individual Treatment Effects of Large-scale Team Competitions in a Ride-sharing Economy T. Ye W. Ai Lingyu Zhang Ning Luo Lulu Zhang Jieping Ye Qiaozhu Mei 9 10 0 07 Aug 2020
Deep Bayesian Bandits: Exploring in Online Personalized Recommendations Dalin Guo S. Ktena Ferenc Huszár Pranay K. Myana Wenzhe Shi Alykhan Tejani OffRL 38 40 0 03 Aug 2020
An Interpretable Probabilistic Approach for Demystifying Black-box Predictive Models Catarina Moreira Yu-Liang Chou M. Velmurugan Chun Ouyang Renuka Sindhgatta P. Bruza 36 57 0 21 Jul 2020
Near-Optimal Provable Uniform Convergence in Offline Policy Evaluation for Reinforcement Learning Ming Yin Yu Bai Yu Wang OffRL 44 31 0 07 Jul 2020
Offline Contextual Bandits with Overparameterized Models David Brandfonbrener William F. Whitney Rajesh Ranganath Joan Bruna OffRL 12 10 0 27 Jun 2020
Confident Off-Policy Evaluation and Selection through Self-Normalized Importance Weighting Ilja Kuzborskij Claire Vernade András Gyorgy Csaba Szepesvári OffRL 8 46 0 18 Jun 2020
Off-policy Bandits with Deficient Support Noveen Sachdeva Yi-Hsun Su Thorsten Joachims OffRL 38 75 0 16 Jun 2020
Latent Bandits Revisited Joey Hong Branislav Kveton Manzil Zaheer Yinlam Chow Amr Ahmed Craig Boutilier OffRL 10 47 0 15 Jun 2020
Non-Stationary Off-Policy Optimization Joey Hong Branislav Kveton Manzil Zaheer Yinlam Chow Amr Ahmed OffRL 27 0 0 15 Jun 2020
Learning Decomposed Representation for Counterfactual Inference Anpeng Wu Kun Kuang Junkun Yuan Bo Li Jianrong Tao Qiang Zhu Yueting Zhuang Fei Wu CML 29 21 0 12 Jun 2020
Counterfactual VQA: A Cause-Effect Look at Language Bias Yulei Niu Kaihua Tang Hanwang Zhang Zhiwu Lu Xiansheng Hua Ji-Rong Wen CML 61 395 0 08 Jun 2020
CausaLM: Causal Model Explanation Through Counterfactual Language Models Amir Feder Nadav Oved Uri Shalit Roi Reichart CML LRM 51 157 0 27 May 2020
Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems Sergey Levine Aviral Kumar George Tucker Justin Fu OffRL GP 346 1,968 0 04 May 2020
MultiMBNN: Matched and Balanced Causal Inference with Neural Networks Ankit Sharma Garima Gupta Ranjitha Prasad Arnab Chatterjee L. Vig Gautam M. Shroff CML 29 7 0 28 Apr 2020
Counterfactual Learning of Stochastic Policies with Continuous Actions: from Models to Offline Evaluation Houssam Zenati A. Bietti Matthieu Martin Eustache Diemert Pierre Gaillard Julien Mairal OffRL CML 17 4 0 22 Apr 2020
Causality-aware counterfactual confounding adjustment for feature representations learned by deep models E. C. Neto AI4CE OOD BDL CML 30 2 0 20 Apr 2020
Black-box Off-policy Estimation for Infinite-Horizon Reinforcement Learning Ali Mousavi Lihong Li Qiang Liu Denny Zhou OffRL 27 32 0 24 Mar 2020
GenDICE: Generalized Offline Estimation of Stationary Values Ruiyi Zhang Bo Dai Lihong Li Dale Schuurmans OffRL 14 172 0 21 Feb 2020
Performative Prediction Juan C. Perdomo Tijana Zrnic Celestine Mendler-Dünner Moritz Hardt 39 306 0 16 Feb 2020
Improved Algorithms for Conservative Exploration in Bandits Evrard Garcelon Mohammad Ghavamzadeh A. Lazaric Matteo Pirotta 11 24 0 08 Feb 2020
Conservative Exploration in Reinforcement Learning Evrard Garcelon Mohammad Ghavamzadeh A. Lazaric Matteo Pirotta 35 28 0 08 Feb 2020
Causally Correct Partial Models for Reinforcement Learning Danilo Jimenez Rezende Ivo Danihelka George Papamakarios Nan Rosemary Ke Ray Jiang ... Jane X. Wang Jovana Mitrović F. Besse Ioannis Antonoglou Lars Buesing AI4TS 29 32 0 07 Feb 2020
Teaching Machines to Converse Jiwei Li 29 4 0 31 Jan 2020
Combining Offline Causal Inference and Online Bandit Learning for Data Driven Decision Li Ye Yishi Lin Hong Xie John C. S. Lui CML 6 11 0 16 Jan 2020
Counterfactual Evaluation of Treatment Assignment Functions with Networked Observational Data Ruocheng Guo Jundong Li Huan Liu CML OffRL 33 21 0 22 Dec 2019
MetaCI: Meta-Learning for Causal Inference in a Heterogeneous Population Ankit Sharma Garima Gupta Ranjitha Prasad Arnab Chatterjee L. Vig Gautam M. Shroff OOD 30 12 0 09 Dec 2019
Efficient adjustment sets for population average treatment effect estimation in non-parametric causal graphical models A. Rotnitzky Ezequiel Smucler CML 21 30 0 01 Dec 2019
Analysis of Explainers of Black Box Deep Neural Networks for Computer Vision: A Survey Vanessa Buhrmester David Münch Michael Arens MLAU FaML XAI AAML 21 355 0 27 Nov 2019
Causality for Machine Learning Bernhard Schölkopf CML AI4CE LRM 38 451 0 24 Nov 2019
Empirical Study of Off-Policy Policy Evaluation for Reinforcement Learning Cameron Voloshin Hoang Minh Le Nan Jiang Yisong Yue OffRL 30 152 0 15 Nov 2019
Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning Dipendra Kumar Misra Mikael Henaff A. Krishnamurthy John Langford 29 151 0 13 Nov 2019
Triply Robust Off-Policy Evaluation Anqi Liu Hao Liu Anima Anandkumar Yisong Yue OffRL 35 10 0 13 Nov 2019
Integrating Markov processes with structural causal modeling enables counterfactual inference in complex systems Robert Osazuwa Ness Kaushal Paneri O. Vitek 25 7 0 06 Nov 2019
Thompson Sampling for Contextual Bandit Problems with Auxiliary Safety Constraints Sam Daulton Shaun Singh Vashist Avadhanula Drew Dimmery E. Bakshy 21 13 0 02 Nov 2019
MultiVerse: Causal Reasoning using Importance Sampling in Probabilistic Programming Yura N. Perov L. Graham Kostis Gourgoulias Jonathan G. Richens Ciarán M. Gilligan-Lee Adam Baker Saurabh Johri LRM 20 17 0 17 Oct 2019
Doubly Robust Bias Reduction in Infinite Horizon Off-Policy Estimation Ziyang Tang Yihao Feng Lihong Li Dengyong Zhou Qiang Liu OffRL 30 67 0 16 Oct 2019
Ranking metrics on non-shuffled traffic Alexandre Gilotte 12 0 0 17 Sep 2019
Towards Sharing Task Environments to Support Reproducible Evaluations of Interactive Recommender Systems Andrea Barraza-Urbina Mathieu d’Aquin LRM 6 2 0 13 Sep 2019
Counterfactual Story Reasoning and Generation Lianhui Qin Antoine Bosselut Ari Holtzman Chandra Bhagavatula Elizabeth Clark Yejin Choi LRM 32 141 0 09 Sep 2019
Efron-Stein PAC-Bayesian Inequalities Ilja Kuzborskij Csaba Szepesvári 24 22 0 04 Sep 2019