Semantic Scholar uses AI to extract papers important to this topic.
This paper considers regularized block multiconvex optimization, where the feasible set and objective function are generally… Expand Nonnegative Matrix Factorization (NMF) is an effective dimension reduction method for non-negative dyadic data, and has proven to… Expand Abstract A mega-analytic study was designed to exploit the power of a large data set combining raw data from multiple studies ( n… Expand The sequential minimal optimization algorithm (SMO) has been shown to be an effective method for training support vector machines… Expand We consider the problem of learning with instances defined over a space of sets of vectors. We derive a new positive definite… Expand Abstract This manuscript reviews information on past use of the CBCL to describe the clinical status of children in state custody… Expand The self-report technique is one of three major ways of measuring involvement in delinquent and criminal behavior. The basic… Expand The Support Vector Machine (SVM) is a new and very promising classification technique developed by Vapnik and his group at AT\&T… Expand Object and pattern detection is a classical computer vision problem with many potential applications, ranging from automatic… Expand Noncompliance strategies for asserting autonomy were examined. Ss were depressed and well mothers and their children, who were 1… Expand