We study on-line generalized linear regression with multidimensional outputs, i.e., neural networks with multiple output nodes but no hidden nodes. We allow at the final layer tra...
Abstract. With Next Generation Sequencers, sequence based transcriptomic or epigenomic assays yield millions of short sequence reads that need to be mapped back on a reference geno...
Eric Rivals, Leena Salmela, Petteri Kiiskinen, Pet...
This paper considers two similar graph algorithms that work by repeatedly increasing "flow" along "augmenting paths": the Ford-Fulkerson algorithm for the maxi...
Brian C. Dean, Michel X. Goemans, Nicole Immorlica
The aim of this work is to learn a shape prior model
for an object class and to improve shape matching with the
learned shape prior. Given images of example instances,
we can le...
call it, provides abstraction through the rewriting arrow and explicit rule application. It also embeds the notion of sets of results to deal with non-deterministic computations. F...