In this paper, we consider the problem of unsupervised morphological analysis from a new angle. Past work has endeavored to design unsupervised learning methods which explicitly o...
Tolerances are a very important property of a design. This paper presents a method for simulating tolerances in signal processing and control systems on the system level using aï¬...
Wilhelm Heupke, Christoph Grimm, Klaus Waldschmidt
Low-dimensional topic models have been proven very useful for modeling a large corpus of documents that share a relatively small number of topics. Dimensionality reduction tools s...
We develop a new component analysis framework, the Noisy-Or Component Analyzer (NOCA), that targets high-dimensional binary data. NOCA is a probabilistic latent variable model tha...
Background: Protein remote homology detection and fold recognition are central problems in bioinformatics. Currently, discriminative methods based on support vector machine (SVM) ...
Bin Liu, Xiaolong Wang, Lei Lin, Qiwen Dong, Xuan ...