research
∙
05/23/2023
Disincentivizing Polarization in Social Networks
On social networks, algorithmic personalization drives users into filter...
share
research
∙
10/04/2019
The Disparate Equilibria of Algorithmic Decision Making when Individuals Invest Rationally
The long-term impact of algorithmic decision making is shaped by the dyn...
research
∙
09/20/2019
Efficient sampling and counting algorithms for the Potts model on Z^d at all temperatures
For d > 2 and all q≥ q_0(d) we give an efficient algorithm to approximat...
research
∙
06/10/2019
Tackling Climate Change with Machine Learning
Climate change is one of the greatest challenges facing humanity, and we...
research
∙
05/02/2019
Visualizing the Consequences of Climate Change Using Cycle-Consistent Adversarial Networks
We present a project that aims to generate images that depict accurate, ...
research
∙
04/10/2019
What's in a Name? Reducing Bias in Bios without Access to Protected Attributes
There is a growing body of work that proposes methods for mitigating bia...
research
∙
01/27/2019
Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting
We present a large-scale study of gender bias in occupation classificati...
research
∙
10/30/2018
Private Algorithms Can Always Be Extended
We consider the following fundamental question on ϵ-differential privacy...
research
∙
10/30/2018
Private Algorithms Can be Always Extended
We consider the following fundamental question on ϵ-differential privacy...
research
∙
10/04/2018
Revealing Network Structure, Confidentially: Improved Rates for Node-Private Graphon Estimation
Motivated by growing concerns over ensuring privacy on social networks, ...
research
∙
12/03/2017
Iterative Collaborative Filtering for Sparse Matrix Estimation
The sparse matrix estimation problem consists of estimating the distribu...
research
∙
11/06/2016
Entropy-SGD: Biasing Gradient Descent Into Wide Valleys
This paper proposes a new optimization algorithm called Entropy-SGD for ...
research
∙
05/20/2016
Unreasonable Effectiveness of Learning Neural Networks: From Accessible States and Robust Ensembles to Basic Algorithmic Schemes
In artificial neural networks, learning from data is a computationally d...
research
∙
02/04/2016
