Concept

Stanley symmetric function

Publications associées (6)

A Determinantal Identity for the Permanent of a Rank 2 Matrix

We prove an identity relating the permanent of a rank 2 matrix and the determinants of its Hadamard powers. When viewed in the right way, the resulting formula looks strikingly similar to an identity of Carlitz and Levine, suggesting the possibility that t ...

TAYLOR & FRANCIS INC2022

Function Computation over Networks : Efficient Information Processing for Cache and Sensor Applications

Chien-Yi Wang

This thesis looks at efficient information processing for two network applications: content delivery with caching and collecting summary statistics in wireless sensor networks. Both applications are studied under the same paradigm: function computation ove ...

EPFL2015

Maximizing Symmetric Submodular Functions

Moran Feldman

Symmetric submodular functions are an important family of submodular functions capturing many interesting cases including cut functions of graphs and hypergraphs. In this work, we identify submodular maximization problems for which one can get a better app ...

Springer Int Publishing Ag2015

Computing in social networks

Rachid Guerraoui, Anne-Marie Kermarrec, Kévin Clément Huguenin, Andrei Giurgiu

This paper defines the problem of Scalable Secure computing in a Social network: we call it the S-3 problem. In short, nodes, directly reflecting on associated users, need to compute a symmetric function f : V-n -> U of their inputs in a set of constant si ...

Elsevier2014

Silence-Based Communication

Christina Fragouli

Communication complexity---the minimum amount of communication required---of computing a function of data held by several parties is studied. A communication model where silence is used to convey information is introduced. For this model the worst-case and ...

2010

A Determinantal Identity for the Permanent of a Rank 2 Matrix

Adam Wade Marcus

TAYLOR & FRANCIS INC2022

Principal Component Analysis By Optimization Of Symmetric Functions Has No Spurious Local Optima

Armin Eftekhari

Principal component analysis (PCA) finds the best linear representation of data and is an indispensable tool in many learning and inference tasks. Classically, principal components of a dataset are interpreted as the directions that preserve most of its "e ...

SIAM PUBLICATIONS2020