We compute a common feature selection or kernel selection configuration for multiple support vector machines (SVMs) trained on different yet inter-related datasets. The method is ...
In this paper, we present a novel semidefinite programming approach for multiple-instance learning. We first formulate the multipleinstance learning as a combinatorial maximum marg...
This paper presents a new approach to extracting and representing structural features of images. The approach is based on both a region-based analysis and a contour-based analysis...
L1 regularized logistic regression is now a workhorse of machine learning: it is widely used for many classification problems, particularly ones with many features. L1 regularized...
Su-In Lee, Honglak Lee, Pieter Abbeel, Andrew Y. N...
Abstract. Matrix factorization is a fundamental building block in many computer vision and machine learning algorithms. In this work we focus on the problem of ”structure from mo...