Deep Belief Networks (DBN's) are generative models that contain many layers of hidden variables. Efficient greedy algorithms for learning and approximate inference have allow...
We present an algorithm for identifying putative non-coding RNA (ncRNA) using an RCSG (RNA Common-Structural Grammar) and show the effectiveness of the algorithm. The algorithm con...
Jin-Wu Nam, Je-Gun Joung, Y. S. Ahn, Byoung-Tak Zh...
We propose a novel boosting algorithm which improves on current algorithms for weighted voting classification by striking a better balance between classification accuracy and the ...
We study a generative model in which hidden causes combine competitively to produce observations. Multiple active causes combine to determine the value of an observed variable thr...
Dependency networks are a compelling alternative to Bayesian networks for learning joint probability distributions from data and using them to compute probabilities. A dependency ...