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06/06/2023
Finding Counterfactually Optimal Action Sequences in Continuous State Spaces
Humans performing tasks that involve taking a series of multiple depende...
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06/06/2023
Designing Decision Support Systems Using Counterfactual Prediction Sets
Decision support systems for classification tasks are predominantly desi...
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05/31/2023
Human-Aligned Calibration for AI-Assisted Decision Making
Whenever a binary classifier is used to provide decision support, it typ...
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01/31/2023
On the Within-Group Discrimination of Screening Classifiers
Screening classifiers are increasingly used to identify qualified candid...
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03/16/2022
Counterfactual Inference of Second Opinions
Automated decision support systems that are able to infer second opinion...
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02/02/2022
Improving Screening Processes via Calibrated Subset Selection
Many selection processes such as finding patients qualifying for a medic...
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01/28/2022
Provably Improving Expert Predictions with Conformal Prediction
Automated decision support systems promise to help human experts solve t...
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11/15/2021
Counterfactual Temporal Point Processes
Machine learning models based on temporal point processes are the state ...
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09/23/2021
Reinforcement Learning Under Algorithmic Triage
Methods to learn under algorithmic triage have predominantly focused on ...
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07/06/2021
Counterfactual Explanations in Sequential Decision Making Under Uncertainty
Methods to find counterfactual explanations have predominantly focused o...
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06/30/2021
Group Testing under Superspreading Dynamics
Testing is recommended for all close contacts of confirmed COVID-19 pati...
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03/16/2021
Differentiable Learning Under Triage
Multiple lines of evidence suggest that predictive models may benefit fr...
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11/16/2020
PanCast: Listening to Bluetooth Beacons for Epidemic Risk Mitigation
During the ongoing COVID-19 pandemic, there have been burgeoning efforts...
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10/09/2020
Large-scale randomized experiment reveals machine learning helps people learn and remember more effectively
Machine learning has typically focused on developing models and algorith...
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06/21/2020
Classification Under Human Assistance
Most supervised learning models are trained for full automation. However...
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04/15/2020
A Spatiotemporal Epidemic Model to Quantify the Effects of Contact Tracing, Testing, and Containment
We introduce a novel modeling framework for studying epidemics that is s...
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02/11/2020
Decisions, Counterfactual Explanations and Strategic Behavior
Data-driven predictive models are increasingly used to inform decisions ...
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02/11/2020
Learning to Switch Between Machines and Humans
Reinforcement learning algorithms have been mostly developed and evaluat...
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09/06/2019
Regression Under Human Assistance
Decisions are increasingly taken by both humans and machine learning mod...
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09/01/2019
Can A User Guess What Her Followers Want?
Whenever a social media user decides to share a story, she is typically ...
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05/22/2019
Optimal Decision Making Under Strategic Behavior
We are witnessing an increasing use of data-driven predictive models to ...
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05/13/2019
Consequential Ranking Algorithms and Long-term Welfare
Ranking models are typically designed to provide rankings that optimize ...
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02/08/2019
Improving Consequential Decision Making under Imperfect Predictions
Consequential decisions are increasingly informed by sophisticated data-...
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11/19/2018
On the Network Visibility Problem
Social media is an attention economy where users are constantly competin...
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10/30/2018
Stochastic Optimal Control of Epidemic Processes in Networks
We approach the development of models and control strategies of suscepti...
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05/25/2018
Enhancing the Accuracy and Fairness of Human Decision Making
Societies often rely on human experts to take a wide variety of decision...
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05/23/2018
Deep Reinforcement Learning of Marked Temporal Point Processes
In a wide variety of applications, humans interact with a complex enviro...
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05/21/2018
Teaching Multiple Concepts to Forgetful Learners
How can we help a forgetful learner learn multiple concepts within a lim...
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02/19/2018
On the Complexity of Opinions and Online Discussions
In an increasingly polarized world, demagogues who reduce complexity dow...
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02/19/2018
Steering Social Activity: A Stochastic Optimal Control Point Of View
User engagement in online social networking depends critically on the le...
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02/14/2018
Designing Random Graph Models Using Variational Autoencoders With Applications to Chemical Design
Deep generative models have been praised for their ability to learn smoo...
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12/05/2017
Optimizing Human Learning
Spaced repetition is a technique for efficient memorization which uses r...
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11/27/2017
Leveraging the Crowd to Detect and Reduce the Spread of Fake News and Misinformation
Online social networking sites are experimenting with the following crow...
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06/30/2017
From Parity to Preference-based Notions of Fairness in Classification
The adoption of automated, data-driven decision making in an ever expand...
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03/06/2017
Cheshire: An Online Algorithm for Activity Maximization in Social Networks
User engagement in social networks depends critically on the number of o...
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10/26/2016
Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment
Automated data-driven decision making systems are increasingly being use...
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10/24/2016
Distilling Information Reliability and Source Trustworthiness from Digital Traces
Online knowledge repositories typically rely on their users or dedicated...
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10/18/2016
Modeling the Dynamics of Online Learning Activity
People are increasingly relying on the Web and social media to find solu...
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10/18/2016
RedQueen: An Online Algorithm for Smart Broadcasting in Social Networks
Users in social networks whose posts stay at the top of their followers'...
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05/22/2016
Smart broadcasting: Do you want to be seen?
Many users in online social networks are constantly trying to gain atten...
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07/08/2015
COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Co-evolution
Information diffusion in online social networks is affected by the under...
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05/12/2014
Estimating Diffusion Network Structures: Recovery Conditions, Sample Complexity & Soft-thresholding Algorithm
Information spreads across social and technological networks, but often ...
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05/15/2013
