A Stochastic Subgradient Method for Distributionally Robust Non-convex and Non-smooth Learning

Journal of Optimization Theory and Applications - We consider a distributionally robust formulation of stochastic optimization problems arising in statistical learning, where robustness is with...     

Dichlorocarbene and analogs: discovery,properties and reactions

Russian Chemical Bulletin - The discovery and studies of chemistry of dichlorocarbene and other electron deficient carbenes are discussed.     

Surface of Ru/Fe2O3 catalysts used in water-gas shift reaction studied by auger electron spectrometry

Summary Carbon deposits on the surface ofRu/Fe₂O₃ catalysts used in the water-gas shift reaction have been investigated by Auger Electron Spectrometry. A correlation has been found between the thickness of the carbon deposit and the catalytic activity in WGSR. The carbon deposit covers the metallic active centers and blocks their contact with reagents. The dotting of the iron oxide support with sodium has been found to reduce the amount of carbon deposit. .      

Space-Time Directional Lyapunov Exponents for Cellular Automata

Space-time directional Lyapunov exponents are introduced. They describe the maximal velocity of propagation to the right or to the left of fronts of perturbations in a frame moving with a given velocity. The continuity of these exponents as function of the velocity and an inequality relating them to the directional entropy is proved.     

Regularization of Discrete Ill-Posed Problems

The paper concerns conditioning aspects of finite-dimensional problems arising when the Tikhonov regularization is applied to discrete ill-posed problems. A relation between the regularization parameter and the sensitivity of the regularized solution is investigated. The main conclusion is that the condition number can be decreased only to the square root of that for the nonregularized problem. The convergence of solutions of regularized discrete problems to the exact generalized solution is analyzed just in the case when the regularization corresponds to the minimal condition number. The convergence theorem is proved under the assumption of the suitable relation between the discretization level and the data error. As an example the method of truncated singular value decomposition with regularization is considered. This revised version was published online in July 2006 with corrections to the Cover Date.