research
∙
07/20/2022
DataPerf: Benchmarks for Data-Centric AI Development
Machine learning (ML) research has generally focused on models, while th...
share
research
∙
02/15/2021
A Data Quality-Driven View of MLOps
Developing machine learning models can be seen as a process similar to t...
research
∙
10/19/2020
Online Active Model Selection for Pre-trained Classifiers
Given k pre-trained classifiers and a stream of unlabeled data examples,...
research
∙
05/11/2020
Nearest Neighbor Classifiers over Incomplete Information: From Certain Answers to Certain Predictions
Machine learning (ML) applications have been thriving recently, largely ...
research
∙
03/19/2020
RAB: Provable Robustness Against Backdoor Attacks
Recent studies have shown that deep neural networks (DNNs) are vulnerabl...
research
∙
02/28/2020
End-to-end Robustness for Sensing-Reasoning Machine Learning Pipelines
As machine learning (ML) being applied to many mission-critical scenario...
research
∙
12/19/2019
Data Science through the looking glass and what we found there
The recent success of machine learning (ML) has led to an explosive grow...
research
∙
03/01/2019
Continuous Integration of Machine Learning Models with ease.ml/ci: Towards a Rigorous Yet Practical Treatment
Continuous integration is an indispensable step of modern software engin...
research
∙
03/17/2018