Self-supervised learning in vision-language processing exploits semantic...
Prediction failures of machine learning models often arise from deficien...
Multi-modal data abounds in biomedicine, such as radiology images and
re...
We present CRYPTFLOW, a system that converts TensorFlow inference code i...
The increasing popularity of machine learning approaches and the rising
...
Machine learning models, especially deep neural networks have been shown...
In syntax-guided synthesis (SyGuS), a synthesizer's goal is to automatic...
In syntax-guided synthesis (SyGuS), a synthesizer's goal is to automatic...
In syntax-guided synthesis (SyGuS), a synthesizer's goal is to automatic...
Deep neural networks and decision trees operate on largely separate
para...
We present a novel cost function for semi-supervised learning of neural
...
We propose the autofocus convolutional layer for semantic segmentation w...
With the range and sensitivity of algorithmic decisions expanding at a
b...
Significant advances have been made towards building accurate automatic
...
We explore the following question: Is a decision-making program fair, fo...
Despite having high accuracy, neural nets have been shown to be suscepti...
Unlike traditional programs (such as operating systems or word processor...