Asynchronous Proximal Stochastic Gradient Algorithm for Composition Optimization Problems

We present the first shared-memory parallel data structure for union-find (equivalently, IGC) that is both provably work-efficient (i.e. performs no more work than the best

From the perspective of consumers, enterprises, and government, we use numerical experiments to illustrate the impacts of consumer discount perception and cost savings on the

Europe (Iceland, British Isles, Spain, France, Germany, Switzerland, Czech Re- public, Poland, Austria, Slovakia, Hungary, Cro- atia, Bulgaria, Italy, Russia), Asia (India, Japan),

Alternatively the proposed dynamic HMM approach using the complete patient longitudinal data has additional benefits over the traditional threshold based detection by both (i) using

The ideal of self-r eliance cer tainly does not exclude this other ideal of shar ing, of the g iv e-and-tak e, whether spontaneous or institutionalized, that

• Introduction: stochastic approximation algorithms – Supervised machine learning and convex optimization – Stochastic gradient and averaging.. – Strongly

Another reason why Savills initially set up this virtual office in the area is because of the consistent similarities in the profiles and requirements of buyers in Richmond, Barnes,

5 The fact is, despite the apparent self-evidence of the Synonym Substitution Principle, despite the synonymy of an interception's terms, and despite a logical