
Computing Equilibria of Prediction Markets via Persuasion
We study the computation of equilibria in prediction markets in perhaps ...
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A Smoothed Analysis of Online Lasso for the Sparse Linear Contextual Bandit Problem
We investigate the sparse linear contextual bandit problem where the par...
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Prophet Inequalities with Linear Correlations and Augmentations
In a classical online decision problem, a decisionmaker who is trying t...
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An Embedding Framework for Consistent Polyhedral Surrogates
We formalize and study the natural approach of designing convex surrogat...
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Decentralized & Collaborative AI on Blockchain
Machine learning has recently enabled large advances in artificial intel...
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Toward a Characterization of Loss Functions for Distribution Learning
In this work we study loss functions for learning and evaluating probabi...
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Equal Opportunity in Online Classification with Partial Feedback
We study an online classification problem with partial feedback in which...
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MultiObservation Regression
Recent work introduced loss functions which measure the error of a predi...
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Local Differential Privacy for Evolving Data
There are now several large scale deployments of differential privacy us...
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A Smoothed Analysis of the Greedy Algorithm for the Linear Contextual Bandit Problem
Bandit learning is characterized by the tension between longterm explor...
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Strategic Classification from Revealed Preferences
We study an online linear classification problem, in which the data is g...
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An Axiomatic Study of Scoring Rule Markets
Prediction markets are wellstudied in the case where predictions are pr...
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LowCost Learning via Active Data Procurement
We design mechanisms for online procurement of data held by strategic ag...
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Bo Waggoner
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