The field of machine learning (ML) is concerned with the question of how to construct algorithms that automatically improve with experience. In recent years many successful ML app...
We present a novel framework for learning to interpret and generate language using only perceptual context as supervision. We demonstrate its capabilities by developing a system t...
Abstract. Learning-based approaches have become increasingly practical in medical imaging. For a supervised learning strategy, the quality of the trained algorithm (usually a class...
Juan Eugenio Iglesias, Cheng-Yi Liu, Paul M. Thomp...
Multi-task learning leverages shared information among data sets to improve the learning performance of individual tasks. The paper applies this framework for data where each task ...
Multi-instance learning, as other machine learning tasks, also suffers from the curse of dimensionality. Although dimensionality reduction methods have been investigated for many ...
Wei Ping, Ye Xu, Kexin Ren, Chi-Hung Chi, Shen Fur...