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Spotlight Talk 4: Fairness, Welfare, and Equity in Personalized Pricing
Nathan Kallus · Angela Zhou
Author Information
Nathan Kallus (Cornell University)
Angela Zhou (Cornell University)
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2021 : It's COMPASlicated: The Messy Relationship between RAI Datasets and Algorithmic Fairness Benchmarks »
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2021 : Stateful Offline Contextual Policy Evaluation and Learning »
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2022 Panel: Panel 3C-5: Biologically-Plausible Determinant Maximization… & What's the Harm? ... »
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2022 Poster: Provably Efficient Reinforcement Learning in Partially Observable Dynamical Systems »
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2022 Poster: The Implicit Delta Method »
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2022 Poster: What's the Harm? Sharp Bounds on the Fraction Negatively Affected by Treatment »
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2021 Workshop: Causal Inference Challenges in Sequential Decision Making: Bridging Theory and Practice »
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2021 : Stateful Offline Contextual Policy Evaluation and Learning »
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2021 Workshop: Machine Learning Meets Econometrics (MLECON) »
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2021 Poster: Risk Minimization from Adaptively Collected Data: Guarantees for Supervised and Policy Learning »
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2021 Poster: Control Variates for Slate Off-Policy Evaluation »
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2021 Poster: Post-Contextual-Bandit Inference »
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2021 : It's COMPASlicated: The Messy Relationship between RAI Datasets and Algorithmic Fairness Benchmarks »
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2020 Workshop: Consequential Decisions in Dynamic Environments »
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2020 Poster: Confounding-Robust Policy Evaluation in Infinite-Horizon Reinforcement Learning »
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2020 Poster: Doubly Robust Off-Policy Value and Gradient Estimation for Deterministic Policies »
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2019 : Coffee Break and Poster Session »
Rameswar Panda · Prasanna Sattigeri · Kush Varshney · Karthikeyan Natesan Ramamurthy · Harvineet Singh · Vishwali Mhasawade · Shalmali Joshi · Laleh Seyyed-Kalantari · Matthew McDermott · Gal Yona · James Atwood · Hansa Srinivasan · Yonatan Halpern · D. Sculley · Behrouz Babaki · Margarida Carvalho · Josie Williams · Narges Razavian · Haoran Zhang · Amy Lu · Irene Y Chen · Xiaojie Mao · Angela Zhou · Nathan Kallus -
2019 : Opening Remarks »
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2019 Workshop: “Do the right thing”: machine learning and causal inference for improved decision making »
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2019 : Nathan Kallus: Efficiently Breaking the Curse of Horizon with Double Reinforcement Learning »
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2019 Poster: The Fairness of Risk Scores Beyond Classification: Bipartite Ranking and the XAUC Metric »
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2019 Poster: Assessing Disparate Impact of Personalized Interventions: Identifiability and Bounds »
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2019 Poster: Intrinsically Efficient, Stable, and Bounded Off-Policy Evaluation for Reinforcement Learning »
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2019 Poster: Policy Evaluation with Latent Confounders via Optimal Balance »
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2019 Poster: Deep Generalized Method of Moments for Instrumental Variable Analysis »
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2018 Workshop: Challenges and Opportunities for AI in Financial Services: the Impact of Fairness, Explainability, Accuracy, and Privacy »
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2018 Poster: Causal Inference with Noisy and Missing Covariates via Matrix Factorization »
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2018 Poster: Removing Hidden Confounding by Experimental Grounding »
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2018 Spotlight: Removing Hidden Confounding by Experimental Grounding »
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2018 Poster: Confounding-Robust Policy Improvement »
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2018 Poster: Balanced Policy Evaluation and Learning »
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2017 Workshop: From 'What If?' To 'What Next?' : Causal Inference and Machine Learning for Intelligent Decision Making »
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