Embedded signal processing systems are usually associated with real-time constraints and/or high data rates so that fully software implementation are often not satisfactory. In th...
Neural networks and other sophisticated machine learning algorithms frequently miss simple solutions that can be discovered by a more constrained learning methods. Transition from ...
Reliable DNA computing requires a large pool of oligonucleotides that do not produce cross-hybridize. In this paper, we present a transformed algorithm to calculate the maximum wei...
Qinru Qiu, Prakash Mukre, Morgan Bishop, Daniel J....
In this paper we propose a classification-based method towards the segmentation of diffusion tensor images. We use Support Vector Machines to classify diffusion tensors and we ex...
In the paper we present new Alternating Least Squares (ALS) algorithms for Nonnegative Matrix Factorization (NMF) and their extensions to 3D Nonnegative Tensor Factorization (NTF) ...