Publications related to Memoryless Worker-Task Assignment with Polylogarithmic Switching Cost

Stable parameterization of continuous and piecewise-linear functions

Michaël Unser, Alexis Marie Frederic Goujon, Joaquim Gonçalves Garcia Barreto Campos

Rectified-linear-unit (ReLU) neural networks, which play a prominent role in deep learning, generate continuous and piecewise-linear (CPWL) functions. While they provide a powerful parametric representation, the mapping between the parameter and function s ...

2023

Time vs. Truth: Age-Distortion Tradeoffs and Strategies for Distributed Inference

Yunus Inan

In 1948, Claude Shannon laid the foundations of information theory, which grew out of a study to find the ultimate limits of source compression, and of reliable communication. Since then, information theory has proved itself not only as a quest to find the ...

EPFL2023

Nothing New Under the Sun: Novelty Constructs and Measures in Social Studies

Davide Bavato

The concept of novelty is central to questions of creativity, innovation, and discovery. Despite the prominence in scientific inquiry and everyday discourse, there is a chronic ambiguity over its meaning and a surprising variety of empirical measures, whic ...

Emerald Publishing Limited2022

A New Channel-Base Lightning Current Formula With Analytically Adjustable Parameters

Farhad Rachidi-Haeri

The article provides a new channel-based current function, which aims at faithfully reproducing the salient parameters of lightning currents. All the model parameters can be set in a fully analytical way, guaranteeing the possibility of changing them (acco ...

2021

Pairs of majority-decomposing functions

Giovanni De Micheli, Mathias Soeken, Eleonora Testa

We are interested in decompositions xnf1f2 of the majority function over n odd arguments x1, ...,xnsuch that f1and f2do not depend on xn. In this paper, we derive the conditions for f1and f2that satisfy the decomposition. Such decompositions play a centr ...

2018

Discrete least-squares approximations over optimized downward closed polynomial spaces in arbitrary dimension

Fabio Nobile, Giovanni Migliorati

We analyze the accuracy of the discrete least-squares approximation of a function

u

in multivariate polynomial spaces

P_\Lambda:=span\{y\mapsto y^\nu \,: \, \nu\in \Lambda\}

with

\Lambda\subset N_0^d

over the domain

\Gamma:=[-1,1]^d

, based on the s ...

2017

BDD Minimization for Approximate Computing

Mathias Soeken, Arun Chandrasekharan

We present Approximate BDD Minimization (ABM) as a problem that has application in approximate computing. Given a BDD representation of a multi-output Boolean function, ABM asks whether there exists another function that has a smaller BDD representa ...

IEEE2016

MATHICSE Technical Report : Discrete least-squares approximations over optimized downward closed polynomial spaces in arbitrary dimension

Fabio Nobile, Giovanni Migliorati

We analyze the accuracy of the discrete least-squares approximation of a function u in multivariate polynomial spaces

P_\Lambda := span\{y \mapsto y^\nu | \nu \in \Lambda\}

with

\Lambda\subset N_0^d

over the domain

\Gamma := [-1,1]^d

, based on the sa ...

MATHICSE2015

The centre cannot hold: untangling two different trajectories of the 'approaches to learning'framework

Roland John Tormey

The ‘deep/surface approach to learning’ framework is widely used in higher education. Its perceived strength is that it is regarded as having two functions: both being (1) a useful metaphor for development of teaching and learning in higher education and ( ...

2014

Function computation via subspace coding

Christina Fragouli, Lorenzo Keller, Nikhil Karamchandani

This paper considers function computation in a network where intermediate nodes perform randomized network coding, through appropriate choice of the subspace codebooks at the source nodes. Unlike traditional network coding for comput- ing functions, that r ...

2013

Memoryless Worker-Task Assignment with Polylogarithmic Switching Cost

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Stable parameterization of continuous and piecewise-linear functions

Time vs. Truth: Age-Distortion Tradeoffs and Strategies for Distributed Inference

Nothing New Under the Sun: Novelty Constructs and Measures in Social Studies

A New Channel-Base Lightning Current Formula With Analytically Adjustable Parameters

Pairs of majority-decomposing functions

Discrete least-squares approximations over optimized downward closed polynomial spaces in arbitrary dimension

BDD Minimization for Approximate Computing

MATHICSE Technical Report : Discrete least-squares approximations over optimized downward closed polynomial spaces in arbitrary dimension

The centre cannot hold: untangling two different trajectories of the 'approaches to learning'framework

Function computation via subspace coding

Stable parameterization of continuous and piecewise-linear functions

Time vs. Truth: Age-Distortion Tradeoffs and Strategies for Distributed Inference

MATHICSE Technical Report : Discrete least-squares approximations over optimized downward closed polynomial spaces in arbitrary dimension

Discrete least-squares approximations over optimized downward closed polynomial spaces in arbitrary dimension

A New Channel-Base Lightning Current Formula With Analytically Adjustable Parameters

The centre cannot hold: untangling two different trajectories of the 'approaches to learning'framework

Pairs of majority-decomposing functions

BDD Minimization for Approximate Computing

Nothing New Under the Sun: Novelty Constructs and Measures in Social Studies

Function computation via subspace coding