Nathan Kallus

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Comment: Entropy Learning for Dynamic Treatment Regimes pdf

Nathan Kallus, Nathan Kallus, 2020, Statistica Sinica.

From data to decisions through new interfaces between optimization and statistics

Nathan Kallus, Nathan Kallus, 2015 .

Instrument-Armed Bandits pdf

Nathan Kallus, Nathan Kallus, 2017, ALT.

Data-Pooling in Stochastic Optimization

Vishal Gupta, Nathan Kallus, Nathan Kallus, 2019, SSRN Electronic Journal.

Optimal Off-Policy Evaluation from Multiple Logging Policies pdf

Masatoshi Uehara, Yuta Saito, Nathan Kallus, 2020, ICML.

Fairness Under Unawareness: Assessing Disparity When Protected Class Is Unobserved

Madeleine Udell, Jiahao Chen, Xiaojie Mao, 2018, FAT.

Doubly Robust Off-Policy Value and Gradient Estimation for Deterministic Policies pdf

Masatoshi Uehara, Nathan Kallus, Masatoshi Uehara, 2020, NeurIPS.

Localized Debiased Machine Learning: Efficient Estimation of Quantile Treatment Effects, Conditional Value at Risk, and Beyond pdf

Masatoshi Uehara, Xiaojie Mao, Nathan Kallus, 2019, ArXiv.

Statistically Efficient Off-Policy Policy Gradients pdf

Masatoshi Uehara, Nathan Kallus, Masatoshi Uehara, 2020, ICML.

Inventory Management in the Era of Big Data

Dimitris Bertsimas, Nathan Kallus, Amjad Hussain, 2016 .

Learning Preferences from Assortment Choices in a Heterogeneous Population pdf

Madeleine Udell, Nathan Kallus, Madeleine Udell, 2015, ArXiv.

Double Reinforcement Learning for Efficient Off-Policy Evaluation in Markov Decision Processes

Masatoshi Uehara, Nathan Kallus, Masatoshi Uehara, 2019, J. Mach. Learn. Res..

From Predictive to Prescriptive Analytics

Dimitris Bertsimas, Nathan Kallus, D. Bertsimas, 2014, Manag. Sci..

A Framework for Optimal Matching for Causal Inference

Nathan Kallus, Nathan Kallus, 2016, AISTATS.

Assessing Disparate Impacts of Personalized Interventions: Identifiability and Bounds

Nathan Kallus, Angela Zhou, Nathan Kallus, 2019, ArXiv.

Efficiently Breaking the Curse of Horizon: Double Reinforcement Learning in Infinite-Horizon Processes pdf

Masatoshi Uehara, Nathan Kallus, Masatoshi Uehara, 2019, ArXiv.

The Power of Optimization Over Randomization in Designing Experiments Involving Small Samples

Dimitris Bertsimas, Nathan Kallus, Mac Johnson, 2015, Oper. Res..

Causal Inference with Noisy and Missing Covariates via Matrix Factorization

Madeleine Udell, Xiaojie Mao, Nathan Kallus, 2018, NeurIPS.

Efficient Policy Learning from Surrogate-Loss Classification Reductions

Nathan Kallus, Andrew Bennett, Nathan Kallus, 2020, ICML.

More Efficient Policy Learning via Optimal Retargeting pdf

Nathan Kallus, Nathan Kallus, 2019, Journal of the American Statistical Association.

DeepMatch: Balancing Deep Covariate Representations for Causal Inference Using Adversarial Training

Nathan Kallus, Nathan Kallus, 2018, ICML.

Dynamic Assortment Personalization in High Dimensions

Madeleine Udell, Nathan Kallus, Madeleine Udell, 2016, Oper. Res..

Smooth Contextual Bandits: Bridging the Parametric and Non-differentiable Regret Regimes pdf

Xiaojie Mao, Nathan Kallus, Yichun Hu, 2019, COLT 2020.

Off-policy Evaluation in Infinite-Horizon Reinforcement Learning with Latent Confounders pdf

Ali Mousavi, Nathan Kallus, Lihong Li, 2020, AISTATS.

Stochastic Optimization Forests pdf

Xiaojie Mao, Nathan Kallus, 2020, ArXiv.

Causal Inference by Minimizing the Dual Norm of Bias: Kernel Matching & Weighting Estimators for Causal Effects

Nathan Kallus, Nathan Kallus, 2016, CFA@UAI.

Assessing algorithmic fairness with unobserved protected class using data combination

Xiaojie Mao, Nathan Kallus, Angela Zhou, 2019, FAT*.

Recursive Partitioning for Personalization using Observational Data

Nathan Kallus, Nathan Kallus, 2016, ICML.

The Fairness of Risk Scores Beyond Classification: Bipartite Ranking and the xAUC Metric

Nathan Kallus, Angela Zhou, Nathan Kallus, 2019, NeurIPS.

Regression-Robust Designs of Controlled Experiments

Nathan Kallus, 2013 .

Intrinsically Efficient, Stable, and Bounded Off-Policy Evaluation for Reinforcement Learning

Masatoshi Uehara, Nathan Kallus, Masatoshi Uehara, 2019, NeurIPS.

Balanced Policy Evaluation and Learning

Nathan Kallus, Nathan Kallus, 2017, NeurIPS.

Localized Debiased Machine Learning: Efficient Inference on Quantile Treatment Effects and Beyond

Masatoshi Uehara, Xiaojie Mao, Nathan Kallus, 2019, 1912.12945.

Policy Evaluation and Optimization with Continuous Treatments

Nathan Kallus, Angela Zhou, Nathan Kallus, 2018, AISTATS.

Fast Rates for Contextual Linear Optimization pdf

Xiaojie Mao, Nathan Kallus, Yichun Hu, 2020, ArXiv.

Generalization Bounds and Representation Learning for Estimation of Potential Outcomes and Causal Effects pdf

Uri Shalit, David Sontag, Nathan Kallus, 2020, ArXiv.

Removing Hidden Confounding by Experimental Grounding

Uri Shalit, Aahlad Manas Puli, Nathan Kallus, 2018, NeurIPS.

DTR Bandit: Learning to Make Response-Adaptive Decisions With Low Regret pdf

Nathan Kallus, Yichun Hu, Nathan Kallus, 2020, ArXiv.

Efficiently Breaking the Curse of Horizon in Off-Policy Evaluation with Double Reinforcement Learning

Masatoshi Uehara, Nathan Kallus, 2019 .

Rejoinder: New Objectives for Policy Learning pdf

Nathan Kallus, Nathan Kallus, 2020, Journal of the American Statistical Association.

Robust sample average approximation

Vishal Gupta, Dimitris Bertsimas, Nathan Kallus, 2014, Math. Program..

The Variational Method of Moments pdf

Nathan Kallus, Andrew Bennett, 2020, ArXiv.

Confounding-Robust Policy Evaluation in Infinite-Horizon Reinforcement Learning pdf

Nathan Kallus, Angela Zhou, Nathan Kallus, 2020, NeurIPS.

Data-driven robust optimization

Vishal Gupta, Dimitris Bertsimas, Nathan Kallus, 2013, Math. Program..

On the role of surrogates in the efficient estimation of treatment effects with limited outcome data pdf

Xiaojie Mao, Nathan Kallus, Nathan Kallus, 2020, ArXiv.

From Predictions to Data-Driven Decisions Using Machine Learning pdf

Nathan Kallus, Nathan Kallus, 2014, ArXiv.

Predicting crowd behavior with big public data

Nathan Kallus, Nathan Kallus, 2014, WWW.

Efficient Evaluation of Natural Stochastic Policies in Offline Reinforcement Learning pdf

Masatoshi Uehara, Nathan Kallus, 2020, ArXiv.

Scheduling, revenue management, and fairness in an academic-hospital radiology division.

Dimitris Bertsimas, Nathan Kallus, Richard Baum, 2014, Academic radiology.

Confounding-Robust Policy Improvement

Nathan Kallus, Angela Zhou, Nathan Kallus, 2018, NeurIPS.

Generalized Optimal Matching Methods for Causal Inference

Nathan Kallus, Nathan Kallus, 2016, J. Mach. Learn. Res..

Policy Evaluation with Latent Confounders via Optimal Balance

Nathan Kallus, Andrew Bennett, Nathan Kallus, 2019, NeurIPS.

Learning to Personalize from Observational Data

Nathan Kallus, Nathan Kallus, 2016 .

Deep Generalized Method of Moments for Instrumental Variable Analysis

Andrew Bennett, Nathan Kallus, Tobias Schnabel, 2019, NeurIPS.

Classifying Treatment Responders Under Causal Effect Monotonicity

Nathan Kallus, Nathan Kallus, 2019, ICML.

Double Reinforcement Learning for Efficient and Robust Off-Policy Evaluation

Masatoshi Uehara, Nathan Kallus, Masatoshi Uehara, 2020, ICML.

Revealed Preference at Scale: Learning Personalized Preferences from Assortment Choices

Madeleine Udell, Nathan Kallus, Madeleine Udell, 2015, EC.

On the Predictive Power of Web Intelligence and Social Media - The Best Way to Predict the Future Is to tweet It

Nathan Kallus, Nathan Kallus, 2014, MSM/MUSE/SenseML.

Residual Unfairness in Fair Machine Learning from Prejudiced Data

Nathan Kallus, Angela Zhou, Nathan Kallus, 2018, ICML.

Interval Estimation of Individual-Level Causal Effects Under Unobserved Confounding

Xiaojie Mao, Nathan Kallus, Angela Zhou, 2018, AISTATS.

Fairness, Welfare, and Equity in Personalized Pricing pdf

Nathan Kallus, Angela Zhou, Nathan Kallus, 2020, FAccT.

Doubly-Valid/Doubly-Sharp Sensitivity Analysis for Causal Inference with Unmeasured Confounding pdf

Nathan Kallus, Jacob Dorn, Kevin Guo, 2021, ArXiv.

Stateful Offline Contextual Policy Evaluation and Learning pdf

Nathan Kallus, Angela Zhou, Nathan Kallus, 2021, AISTATS.

Assessing Algorithmic Fairness with Unobserved Protected Class Using Data Combination

Xiaojie Mao, Nathan Kallus, Angela Zhou, 2021 .

Control Variates for Slate Off-Policy Evaluation pdf

Ashok Chandrashekar, Nathan Kallus, Nikos Vlassis, 2021, NeurIPS.

Residual Overfit Method of Exploration pdf

Nathan Kallus, James McInerney, Nathan Kallus, 2021, ArXiv.

Risk Minimization from Adaptively Collected Data: Guarantees for Supervised and Policy Learning pdf

Antoine Chambaz, Nathan Kallus, Mark van der Laan, 2021, NeurIPS.

Post-Contextual-Bandit Inference pdf

Antoine Chambaz, Nathan Kallus, Mark van der Laan, 2021, NeurIPS.

Causal Inference Under Unmeasured Confounding With Negative Controls: A Minimax Learning Approach pdf

Masatoshi Uehara, Xiaojie Mao, Nathan Kallus, 2021, ArXiv.

Fast Rates for the Regret of Offline Reinforcement Learning

Masatoshi Uehara, Nathan Kallus, Yichun Hu, 2021, COLT.

Treatment Effect Risk: Bounds and Inference

Nathan Kallus, 2022 .

Proximal Reinforcement Learning: Efficient Off-Policy Evaluation in Partially Observed Markov Decision Processes pdf

Andrew Bennett, Nathan Kallus, 2021, ArXiv.

More robust estimation of average treatment effects using kernel optimal matching in an observational study of spine surgical interventions

Nathan Kallus, Michele Santacatterina, Brenton Pennicooke, 2018, Statistics in medicine.

Optimal balancing of time-dependent confounders for marginal structural models

Nathan Kallus, Michele Santacatterina, Nathan Kallus, 2018, Journal of Causal Inference.

Minimax-Optimal Policy Learning Under Unobserved Confounding

Nathan Kallus, Angela Zhou, Nathan Kallus, 2020, Manag. Sci..

Controlling for Unmeasured Confounding in Panel Data Using Minimal Bridge Functions: From Two-Way Fixed Effects to Factor Models

Guido Imbens, Xiaojie Mao, Nathan Kallus, 2021, 2108.03849.

Finite Sample Analysis of Minimax Offline Reinforcement Learning: Completeness, Fast Rates and First-Order Efficiency pdf

Masatoshi Uehara, Nan Jiang, Tengyang Xie, 2021, ArXiv.

An Empirical Evaluation of the Impact of New York's Bail Reform on Crime Using Synthetic Controls pdf

Nathan Kallus, Angela Zhou, Tiffany Bergin, 2021, SSRN Electronic Journal.

The Variational Method of Moments pdf

Andrew Bennett, Nathan Kallus, 2020, ArXiv.

Efficiently Breaking the Curse of Horizon in Off-Policy Evaluation with Double Reinforcement Learning

Masatoshi Uehara, Nathan Kallus, 2019 .

Do the right thing ” : machine learning and causal inference for improved decision making

Thorsten Joachims, David Sontag, Nathan Kallus, .

Confounding-Robust Policy Evaluation in Infinite-Horizon Reinforcement Learning pdf

Nathan Kallus, Angela Zhou, 2020, NeurIPS.

Kernel Optimal Orthogonality Weighting: A Balancing Approach to Estimating Effects of Continuous Treatments

Nathan Kallus, Michele Santacatterina, Nathan Kallus, 2019, 1910.11972.

The Power and Limits of Predictive Approaches to Observational-Data-Driven Optimization

Dimitris Bertsimas, Nathan Kallus, D. Bertsimas, 2016, 1605.02347.

Pricing from Observational Data

Dimitris Bertsimas, Nathan Kallus, D. Bertsimas, 2016 .