Concept

Variable (mathematics)

Related publications (50)

Reducibility bounds of objective functions over the integers

We study the settings where we are given a separable objective function of n variables defined in a given box of integers. We show that in many cases we can replace the given objective function by a new function with a much smaller domain. Our results appl ...

Amsterdam2023

Keep Sensors in Check: Disentangling Country-Level Generalization Issues in Mobile Sensor-Based Models with Diversity Scores

Daniel Gatica-Perez, Lakmal Buddika Meegahapola

Machine learning models trained with passive sensor data from mobile devices can be used to perform various inferences pertaining to activity recognition, context awareness, and health and well-being. Prior work has improved inference performance through t ...

New York2023

Declarative Variables in Online Dating: A Mixed-Method Analysis of a Mimetic-Distinctive Mechanism

Daniel Gatica-Perez, Jessica Carolina Pidoux

Declarative variables of self-description have a long-standing tradition in matchmaking media. With the advent of online dating platforms and their brand positioning, the volume and semantics of variables vary greatly across apps. However, a variable lands ...

2021

On long time behavior of solutions to nonlinear dispersive equations

Stefano Francesco Burzio

In part I, we address the issue of existence of solutions for Cauchy problems involving nonlinear hyperbolic equations for initial data in Sobolev spaces with scaling subcritical regularity. In particular, we analyse nonlinear estimates for null-forms in t ...

EPFL2020

Cost for a controlled linear KdV equation

Joachim Krieger, Shengquan Xiang

The controllability of the linearized KdV equation with right Neumann control is studied in the pioneering work of Rosier [25]. However, the proof is by contradiction arguments and the value of the observability constant remains unknown, though rich mathem ...

2019

Unsupervised Scalable Representation Learning for Multivariate Time Series

Martin Jaggi, Aymeric Daphnis Kévin Dieuleveut

Time series constitute a challenging data type for machine learning algorithms, due to their highly variable lengths and sparse labeling in practice. In this paper, we tackle this challenge by proposing an unsupervised method to learn universal embeddings ...

NEURAL INFORMATION PROCESSING SYSTEMS (NIPS)2019

On decoupling rate processes in chemical reaction systems - Methods and applications

Dominique Bonvin, Julien Léo Billeter, Michael Amrhein, Diogo Filipe Mateus Rodrigues

Models of chemical reaction systems can be complex as they need to include information regarding the reactions and the mass and heat transfers. The commonly used state variables, namely, concentrations and temperatures, express the interplay between many p ...

2018

The Mutual Information in Random Linear Estimation Beyond i.i.d. Matrices

Nicolas Macris, Florent Gérard Krzakala, Jean François Emmanuel Barbier

There has been definite progress recently in proving the variational single-letter formula given by the heuristic replica method for various estimation problems. In particular, the replica formula for the mutual information in the case of noisy linear esti ...

IEEE2018

On Decoupling Rate Processes in Chemical Reaction Systems - Methods and Applications

Dominique Bonvin, Julien Léo Billeter, Michael Amrhein, Sriniketh Srinivasan, Diogo Filipe Mateus Rodrigues

Elsevier2017

Null Controllability and Finite Time Stabilization for the Heat Equations with Variable Coefficients in Space in One Dimension via Backstepping Approach

Hoài-Minh Nguyên

Using the backstepping approach we recover the null controllability for the heat equations with variable coefficients in space in one dimension and prove that these equations can be stabilized in finite time by means of periodic time-varying feedback laws. ...

Springer Verlag2017

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