We introduce a boosting framework to solve a classification problem with added manifold and ambient regularization costs. It allows for a natural extension of boosting into both s...
Nicolas Loeff, David A. Forsyth, Deepak Ramachandr...
A key ingredient in the design of visual object classification
systems is the identification of relevant class specific
aspects while being robust to intra-class variations. Whil...
We address the problem of multiclass object detection. Our aims are to enable models for new categories to benefit from the detectors built previously for other categories, and fo...
We study the problem of learning kernel machines transductively for structured output variables. Transductive learning can be reduced to combinatorial optimization problems over a...
There are well-established methods for reducing the number of support vectors in a trained binary support vector machine, often with minimal impact on accuracy. We show how reduce...