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06/13/2023
Questioning the Survey Responses of Large Language Models
As large language models increase in capability, researchers have starte...
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05/29/2023
Collaborative Learning via Prediction Consensus
We consider a collaborative learning setting where each agent's goal is ...
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02/10/2023
Causal Inference out of Control: Estimating the Steerability of Consumption
Regulators and academics are increasingly interested in the causal effec...
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02/08/2023
Algorithmic Collective Action in Machine Learning
We initiate a principled study of algorithmic collective action on digit...
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03/31/2022
Performative Power
We introduce the notion of performative power, which measures the abilit...
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02/01/2022
Regret Minimization with Performative Feedback
In performative prediction, the deployment of a predictive model trigger...
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06/24/2021
Alternative Microfoundations for Strategic Classification
When reasoning about strategic behavior in a machine learning context it...
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06/22/2021
Test-time Collective Prediction
An increasingly common setting in machine learning involves multiple par...
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09/23/2020
Revisiting Design Choices in Proximal Policy Optimization
Proximal Policy Optimization (PPO) is a popular deep policy gradient alg...
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06/24/2020
Randomized Block-Diagonal Preconditioning for Parallel Learning
We study preconditioned gradient-based optimization methods where the pr...
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06/12/2020
Differentially Private Stochastic Coordinate Descent
In this paper we tackle the challenge of making the stochastic coordinat...
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06/12/2020
Stochastic Optimization for Performative Prediction
In performative prediction, the choice of a model influences the distrib...
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02/16/2020
Performative Prediction
When predictions support decisions they may influence the outcome they a...
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11/18/2019
SySCD: A System-Aware Parallel Coordinate Descent Algorithm
In this paper we propose a novel parallel stochastic coordinate descent ...
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10/15/2019
Breadth-first, Depth-next Training of Random Forests
In this paper we analyze, evaluate, and improve the performance of train...
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09/11/2019
Addressing Algorithmic Bottlenecks in Elastic Machine Learning with Chicle
Distributed machine learning training is one of the most common and impo...
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03/22/2019