A new spectral representation called the composite model is proposed. Its key point is to decompose all spectra into a smooth background and a collection of spikes. The smooth par...
This paper provides an algorithmic framework for learning statistical models involving directed spanning trees, or equivalently non-projective dependency structures. We show how p...
Terry Koo, Amir Globerson, Xavier Carreras, Michae...
Abstract. We present Local Church-Rosser, Parallelism, and Concurrency Theorems for rules with nested application conditions in the framework of weak adhesive HLR categories includ...
— We evaluate the average waiting time between observing the price of financial markets and the next price change, especially in an on-line foreign exchange trading service for ...
Probabilistic techniques are widely used in the analysis of algorithms to estimate the computational complexity of algorithms or a computational problem. Traditionally, such analys...