Abstract. The classical perceptron algorithm is an elementary algorithm for solving a homogeneous linear inequality system Ax > 0, with many important applications in learning t...
Alexandre Belloni, Robert M. Freund, Santosh Vempa...
Abstract. This paper presents a system that connects students with complementary profiles, so they can interchange knowledge and help each other. The profile of the students is bui...
Pseudo-likelihood and contrastive divergence are two well-known examples of contrastive methods. These algorithms trade off the probability of the correct label with the probabili...
In the past decade, smart home environment research has found application in many areas, such as activity recognition, visualization, and automation. However, less attention has be...
Boosting is a general method for improving the accuracy of learning algorithms. We use boosting to construct improved privacy-preserving synopses of an input database. These are da...