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ICANN
2009
Springer
15 years 8 months ago
Selective Attention Improves Learning
Abstract. We demonstrate that selective attention can improve learning. Considerably fewer samples are needed to learn a source separation problem when the inputs are pre-segmented...
Antti Yli-Krekola, Jaakko Särelä, Harri ...
ECOI
2006
59views more  ECOI 2006»
15 years 1 months ago
Model-building with interpolated temporal data
Ecological data can be difficult to collect, and as a result, some important temporal ecological datasets contain irregularly sampled data. Since many temporal modelling technique...
Robert I. McKay, Tuan Hao Hoang, Naoki Mori, Nguye...
IPL
2010
92views more  IPL 2010»
14 years 12 months ago
Learning parities in the mistake-bound model
We study the problem of learning parity functions that depend on at most k variables (kparities) attribute-efficiently in the mistake-bound model. We design a simple, deterministi...
Harry Buhrman, David García-Soriano, Arie M...
CIMAGING
2010
195views Hardware» more  CIMAGING 2010»
15 years 3 months ago
SPIRAL out of convexity: sparsity-regularized algorithms for photon-limited imaging
The observations in many applications consist of counts of discrete events, such as photons hitting a detector, which cannot be effectively modeled using an additive bounded or Ga...
Zachary T. Harmany, Roummel F. Marcia, Rebecca Wil...
BIRD
2008
Springer
141views Bioinformatics» more  BIRD 2008»
15 years 3 months ago
Nested q-Partial Graphs for Genetic Network Inference from "Small n, Large p" Microarray Data
Abstract. Gaussian graphical models are widely used to tackle the important and challenging problem of inferring genetic regulatory networks from expression data. These models have...
Kevin Kontos, Gianluca Bontempi