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We present a novel and flexible approach to the problem of feature selection, called grafting. Rather than considering feature selection as separate from learning, grafting treats the selection of suitable features as an integral part of learning a predictor in a regularized learning framework. To make this regularized learning process sufficiently fast for(More)
1996 \Judging from their laughter, the children at school found my remarks humorous. So without understanding humor, I have somehow mastered it." { L a l , i n S t a r T rek, \The Ospring" Abstract This thesis describes a formal model of a subtype of humour, and the implementation of that model in a program that generates jokes of that subtype. Although(More)
Batch implementations of support vector regression (SVR) are inefficient when used in an on-line setting because they must be retrained from scratch every time the training set is modified. Following an incremental support vector classification algorithm introduced by Cauwenberghs and Poggio (2001), we have developed an accurate on-line support vector(More)
Figure 1: Selective Refinement. The headrest is an object of African cultural heritage. In each frame the selected region is refined progressively. Abstract We present a framework for real-time view-dependent refinement, and adapt it to the task of browsing large model repositories on the Internet. We introduce a novel hierarchical representation of atomic(More)
—We have developed an automated feature detec-tion/classification system, called GENetic Imagery Exploitation (GENIE), which has been designed to generate image processing pipelines for a variety of feature detection/classification tasks. GENIE is a hybrid evolutionary algorithm that addresses the general problem of finding features of interest in(More)
Evolutionary algorithms are useful optimization tools but are very time consuming to run. We present a self-contained FPGA-based implementation of a spatially-structured evolutionary algorithm that provides significant speedup over conventional serial processing in three ways: (a) efficient hardware-pipelined fitness evaluation of individuals , (b)(More)
UNLABELLED We present a suite of on-line tools to design candidate vaccine proteins, and to assess antigen potential, using coverage of k-mers (as proxies for potential T-cell epitopes) as a metric. The vaccine design tool uses the recently published 'mosaic' method to generate protein sequences optimized for coverage of high-frequency k-mers; the(More)