We present a biology-inspired probabilistic graphical model, called the hypernetwork model, and its application to medical diagnosis of disease. The hypernetwork models are a way ...
JungWoo Ha, Jae-Hong Eom, Sung-Chun Kim, Byoung-Ta...
Abstract-- Hypernetworks consist of a large number of hyperedges that represent higher-order features sampled from training patterns. Evolutionary algorithms have been used as a me...
As a new pattern classification method, nearest feature line (NFL) provides an effective way to tackle the sort of pattern recognition problems where only limited data are availab...
Background: Predicting a protein's structural or functional class from its amino acid sequence or structure is a fundamental problem in computational biology. Recently, there...
Iain Melvin, Jason Weston, Christina S. Leslie, Wi...
Abstract--This paper proposes a training-based channel estimation scheme for achieving quality-of-service discrimination between legitimate and unauthorized receivers in wireless m...
Tsung-Hui Chang, Wei-Cheng Chiang, Yao-Win Peter H...