Constructing a high-resolution (HR) image from lowresolution (LR) image(s) has been a very active research topic recently with focus shifting from multi-frames to learning based s...
This contribution develops a theoretical framework that takes into account the effect of approximate optimization on learning algorithms. The analysis shows distinct tradeoffs for...
In this paper, we introduce a system named Argo which provides intelligent advertising made possible from users’ photo collections. Based on the intuition that user-generated ph...
Xin-Jing Wang, Mo Yu, Lei Zhang, Rui Cai, Wei-Ying...
In this work we take a novel view of nonlinear manifold learning. Usually, manifold learning is formulated in terms of finding an embedding or `unrolling' of a manifold into ...
Most machine learning algorithms are lazy: they extract from the training set the minimum information needed to predict its labels. Unfortunately, this often leads to models that ...
Joseph O'Sullivan, John Langford, Rich Caruana, Av...