output
20042015
most citedNo More Pesky Learning Rates

289 citations

Showing 2012Show all

18 papers · 1 filter

cs.NI20124 cited

Deriving Pareto-optimal performance bounds for 1 and 2-relay wireless networks

Qi Wang, Katia Jaffrès-Runser, Claire Goursaud +1

This work addresses the problem of deriving fundamental trade-off bounds for a 1-relay and a 2-relay wireless network when multiple performance criteria are of interest. It propose…

cs.OH201213 cited

A Robust Lot Sizing Problem with Ill-known Demands

Romain Guillaume, Przemyslaw Kobylanski, Pawel Zielinski

The paper deals with a lot sizing problem with ill-known demands modeled by fuzzy intervals whose membership functions are possibility distributions for the values of the uncertain…

math.AP2012

Stability estimate in an inverse problem for non-autonomous Schrödinger equations

Michel Cristofol, Eric Soccorsi

We consider the inverse problem of determining the time dependent magnetic field of the Schrödinger equation in a bounded open subset of , with , from a finite numbe…

cond-mat.soft20126 cited

Doxorubicin Loaded Magnetic Polymersomes: Theranostic Nanocarriers for MR Imaging and Magneto-Chemotherapy

Charles Sanson, Odile Diou, Julie Thevenot +10

Hydrophobically modified magnetic nanoparticles (MNPs) were encapsulated within the membrane of poly(trimethylene carbonate)-b-poly(L-glutamic acid) (PTMC-b-PGA) block copolymer ve…

cs.AI201213 cited

A Unified framework for order-of-magnitude confidence relations

Didier Dubois, Helene Fargier

The aim of this work is to provide a unified framework for ordinal representations of uncertainty lying at the crosswords between possibility and probability theories. Such confide…

math.CO20127 cited

Parallelogram polyominoes, the sandpile model on a complete bipartite graph, and a q,t-Narayana polynomial

Mark Dukes, Yvan Le Borgne

We classify recurrent configurations of the sandpile model on the complete bipartite graph K_{m,n} in which one designated vertex is a sink. We present a bijection from these recur…