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...
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...
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...
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...
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...