This paper reviews the recent surge of interest in convex optimization in a context of pattern recognition and machine learning. The main thesis of this paper is that the design of...
Kristiaan Pelckmans, Johan A. K. Suykens, Bart De ...
We present a new algorithm for learning a convex set in n-dimensional space given labeled examples drawn from any Gaussian distribution. The complexity of the algorithm is bounded ...
The versatility of exponential families, along with their attendant convexity properties, make them a popular and effective statistical model. A central issue is learning these mo...
Images of an object undergoing ego- or camera- motion
often appear to be scaled, rotated, and deformed versions
of each other. To detect and match such distorted patterns
to a s...
Abstract. Verification by network invariants is a heuristic to solve uniform verification of parameterized systems. Given a system P, a network invariant for P is that abstracts th...