Multi-task learning aims at combining information across tasks to boost prediction performance, especially when the number of training samples is small and the number of predictor...
Online incremental evolution for a complex high-speed pattern recognition architecture has been implemented on a Xilinx Virtex-II Pro FPGA. The fitness evaluation module is entir...
Abstract We describe a method of representing human activities that allows a collection of motions to be queried without examples, using a simple and effective query language. Our ...
This paper presents a general, trainable system for object detection in unconstrained, cluttered scenes. The system derives much of its power from a representation that describes a...
This paper introduces a strategy for training ensemble classifiers by analysing boosting within margin theory. We present a bound on the generalisation error of ensembled classifi...
Huma Lodhi, Grigoris J. Karakoulas, John Shawe-Tay...