We present an algorithm, called the offset tree, for learning in situations where a loss associated with different decisions is not known, but was randomly probed. The algorithm i...
Abstract. We consider the iterates of bilinear functions over the semiring (max, +). Equivalently, our object of study can be viewed as recognizable tree series over the semiring (...
Sabrina Mantaci, Vincent D. Blondel, Jean Mairesse
The evolution of dependencies in information hierarchies can be modeled by sequences of compound digraphs with edge weights. In this paper we present a novel approach to visualize...
Abstract. Most of the work in Machine Learning assume that examples are generated at random according to some stationary probability distribution. In this work we study the problem...
Testing for uniformity of multivariate data is the initial step in exploratory pattern analysis. We propose a new uniformity testing method, which first computes the maximum (sta...