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JMLR
2010
143views more  JMLR 2010»
13 years 3 months ago
A Quasi-Newton Approach to Nonsmooth Convex Optimization Problems in Machine Learning
We extend the well-known BFGS quasi-Newton method and its memory-limited variant LBFGS to the optimization of nonsmooth convex objectives. This is done in a rigorous fashion by ge...
Jin Yu, S. V. N. Vishwanathan, Simon Günter, ...
NIPS
2003
13 years 6 months ago
Convex Methods for Transduction
The 2-class transduction problem, as formulated by Vapnik [1], involves finding a separating hyperplane for a labelled data set that is also maximally distant from a given set of...
Tijl De Bie, Nello Cristianini
CVPR
2012
IEEE
11 years 7 months ago
What is optimized in tight convex relaxations for multi-label problems?
In this work we present a unified view on Markov random fields and recently proposed continuous tight convex relaxations for multi-label assignment in the image plane. These rel...
Christopher Zach, Christian Hane, Marc Pollefeys
PKDD
2009
Springer
162views Data Mining» more  PKDD 2009»
13 years 11 months ago
A Convex Method for Locating Regions of Interest with Multi-instance Learning
Abstract. In content-based image retrieval (CBIR) and image screening, it is often desirable to locate the regions of interest (ROI) in the images automatically. This can be accomp...
Yu-Feng Li, James T. Kwok, Ivor W. Tsang, Zhi-Hua ...