research
∙
06/19/2022
Adversarial Scrutiny of Evidentiary Statistical Software
The U.S. criminal legal system increasingly relies on software output to...
share
research
∙
08/10/2021
Retiring Adult: New Datasets for Fair Machine Learning
Although the fairness community has recognized the importance of data, r...
research
∙
07/20/2021
Improving COVID-19 Forecasting using eXogenous Variables
In this work, we study the pandemic course in the United States by consi...
research
∙
07/09/2021
Accuracy on the Line: On the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization
For machine learning systems to be reliable, we must understand their pe...
research
∙
06/28/2021
Malaria Risk Mapping Using Routine Health System Incidence Data in Zambia
Improvements to Zambia's malaria surveillance system allow better monito...
research
∙
02/17/2021
Outside the Echo Chamber: Optimizing the Performative Risk
In performative prediction, predictions guide decision-making and hence ...
research
∙
01/04/2021
Gaussian Function On Response Surface Estimation
We propose a new framework for 2-D interpreting (features and samples) b...
research
∙
04/29/2020
The Effect of Natural Distribution Shift on Question Answering Models
We build four new test sets for the Stanford Question Answering Dataset ...
research
∙
10/23/2019
Strategic Adaptation to Classifiers: A Causal Perspective
Consequential decision-making incentivizes individuals to adapt their be...
research
∙
09/29/2019
Test-Time Training for Out-of-Distribution Generalization
We introduce a general approach, called test-time training, for improvin...
research
∙
05/29/2019
Model Similarity Mitigates Test Set Overuse
Excessive reuse of test data has become commonplace in today's machine l...
research
∙
08/25/2018
The Social Cost of Strategic Classification
Consequential decision-making typically incentivizes individuals to beha...
research
∙
05/25/2018
When Recurrent Models Don't Need To Be Recurrent
We prove stable recurrent neural networks are well approximated by feed-...
research
∙
10/20/2017
Deep Voice 3: Scaling Text-to-Speech with Convolutional Sequence Learning
We present Deep Voice 3, a fully-convolutional attention-based neural te...
research
∙
10/20/2017
Deep Voice 3: 2000-Speaker Neural Text-to-Speech
We present Deep Voice 3, a fully-convolutional attention-based neural te...
research
∙
09/08/2017
Globally Normalized Reader
Rapid progress has been made towards question answering (QA) systems tha...
research
∙
05/24/2017
Deep Voice 2: Multi-Speaker Neural Text-to-Speech
We introduce a technique for augmenting neural text-to-speech (TTS) with...
research
∙
02/25/2017
Deep Voice: Real-time Neural Text-to-Speech
We present Deep Voice, a production-quality text-to-speech system constr...
research
∙
06/03/2015
