Markov random fields are designed to represent structured dependencies among large collections of random variables, and are well-suited to capture the structure of real-world sign...
Tanya Roosta, Martin J. Wainwright, Shankar S. Sas...
We study multivariate approximation for continuous functions in the average case setting. The space of d variate continuous functions is equipped with the zero mean Gaussian measu...
This is a great draft book about stochastic calculus and finance. It covers large number of topics such as Introduction to Probability Theory, Conditional Expectation, Arbitrage Pr...
We briefly present and analyze, from a geometric viewpoint, strategies for designing algorithms to factor bivariate approximate polynomials in [x, y]. Given a composite polyno...
We introduce a technique to visualize the gradual evolutionary change of the shapes of living things as a morph between known three-dimensional shapes. Given geometric computer mo...
David F. Wiley, Nina Amenta, Dan A. Alcantara, Deb...