Publications associées à Binary data

Robust discrete choice models with t-distributed kernel errors

Michel Bierlaire, Thomas Gasos, Prateek Bansal

Outliers in discrete choice response data may result from misclassification and misreporting of the response variable and from choice behaviour that is inconsistent with modelling assumptions (e.g. random utility maximisation). In the presence of outliers, ...

2023

Governing Heritage and Creativity: Frictions, Avenues and Questions

Creative approaches to both planned and unplanned new practices remain an essential, yet somewhat invisible, part of sustaining living heritage. This collection of essays by interdisciplinary scholars and practitioners draws attention to how decisions are ...

Lettera Ventidue2023

Advances in Magnetics Roadmap on Spin-Wave Computing

Qian Wang, Dirk Grundler, Xiuwei Zhang, Yiming Li

Magnonics addresses the physical properties of spin waves and utilizes them for data processing. Scalability down to atomic dimensions, operation in the GHz-to-THz frequency range, utilization of nonlinear and nonreciprocal phenomena, and compatibility wit ...

Institute of Electrical and Electronics Engineers2022

Gradient-Based Learning of Discrete Structured Measurement Operators for Signal Recovery

Jonathan Paul Sauder

Countless signal processing applications include the reconstruction of signals from few indirect linear measurements. The design of effective measurement operators is typically constrained by the underlying hardware and physics, posing a challenging and of ...

2022

Counting using deep learning regression gives value to ecological surveys

Devis Tuia, Benjamin Alexander Kellenberger

Many ecological studies rely on count data and involve manual counting of objects of interest, which is time-consuming and especially disadvantageous when time in the field or lab is limited. However, an increasing number of works uses digital imagery, whi ...

Nature Research2021

Topology design of general tensegrity with rigid bodies

Yafeng Wang

This study presents a general approach to the topology design of tensegrities with rigid bodies. To the best of the authors' knowledge, all existing topology design methods of tensegrities focus on tensegrities that only consist of members carrying axial f ...

2020

HALucinator: Firmware Re-hosting Through Abstraction Layer Emulation

Mathias Josef Payer

Given the increasing ubiquity of online embedded devices, analyzing their firmware is important to security, privacy, and safety. The tight coupling between hardware and firmware and the diversity found in embedded systems makes it hard to perform dynamic ...

USENIX ASSOC2020

Minimum energy adaptive structures – All-In-One problem formulation

Gennaro Senatore, Yafeng Wang

This paper presents a new All-In-One (AIO) implementation of an existing formulation to design adaptive structures through Total Energy Optimization (TEO). The method implemented in previous work is a nested optimization process, here named TEO-Nested. Num ...

2020

Method and system for the creation of an h-spline based data structure, data storage, and data representation

Michaël Unser, Zsuzsanna Püspöki, Daniel Andreas Schmitter

A method for generating a data structure to digitally represent a geometrical object based on H-splines, the method being performed on a computer device having a data processor and memory, the method including the steps of creating a first data structure a ...

2019

Correlating Twitter Language with Community-Level Health Outcomes

Martin Jaggi, Arno Schneuwly

We study how language on social media is linked to diseases such as atherosclerotic heart disease (AHD), diabetes and various types of cancer. Our proposed model leverages state-of-the-art sentence embeddings, followed by a regression model and clustering, ...

ASSOC COMPUTATIONAL LINGUISTICS-ACL2019

Applications of Approximate Learning and Inference for Probabilistic Models

Young Jun Ko

We develop approximate inference and learning methods for facilitating the use of probabilistic modeling techniques motivated by applications in two different areas. First, we consider the ill-posed inverse problem of recovering an image from an underdeter ...

EPFL2017

A Disk Asymmetry in Motion Around the B[e] Star MWC158

Ferréol Arnaud Marie Soulez

Context. MWC158 is a star with the B[e] phenomenon that shows strong spectrophotometric variability (in lines and in UV and visible continuum) attributed to phases of shell ejection. The evolutionary stage of this star was never clearly determined. Previou ...

EDP Sciences2016

A Time-Based, Digitally Intensive Circuit and System Architecture for Wireless Neural Recording with High Dynamic Range

Alexandre Schmid, Wen-Yang Hsu, Chen Cao

A new type of wireless neural recording front-end with PWM modulation and VCO-based ADC is proposed. The target signal is first encoded into binary levels with varying pulse width by PWM modulation, which intrinsically has much higher dynamic range compare ...

2016

Consistency of $\ell_1$-Regularized Maximum-Likelihood for Compressive Poisson Regression

Volkan Cevher, Yen-Huan Li

We consider Poisson regression with the canonical link function. This regression model is widely used in regression analysis involving count data; one important application in electrical engineering is transmission tomography. In this paper, we establish t ...

2015

Variational Gaussian Inference for Bilinear Models of Count Data

Mohammad Emtiyaz Khan, Young Jun Ko

Bilinear models of count data with Poisson distribution are popular in applications such as matrix factorization for recommendation systems, modeling of receptive fields of sensory neurons, and modeling of neural-spike trains. Bayesian inference in such mo ...

2014

Predicting the Usefulness of Monitoring for Identifying the Behavior of Structures

Ian Smith, James-Alexandre Goulet

Structures can be better understood when measurement data are used to improve the modeling of structural behavior. Our capacity to interpret data depends on aspects such as the choice of model class, model parameters (and their range of possible values), a ...

American Society of Civil Engineers2013

Randomized recovery for boolean compressed sensing

Martin Vetterli, Mitra Fatemi

We consider the problem of boolean compressed sensing, which is alternatively known as group testing. The goal is to recover a small number of defective items in a large set from a few collective binary tests. This problem can be formulated as a binary lin ...

2013

Bits from Photons: Oversampled Image Acquisition Using Binary Poisson Statistics

Martin Vetterli, Luciano Sbaiz, Feng Yang, Yue Lu

We study a new image sensor that is reminiscent of traditional photographic film. Each pixel in the sensor has a binary response, giving only a one-bit quantized measurement of the local light intensity. To analyze its performance, we formulate the oversam ...

Institute of Electrical and Electronics Engineers2012

Bits from Photons : Oversampled Binary Image Acquisition

Feng Yang

The trends in the design of image sensors are to build sensors with low noise, high sensitivity, high dynamic range, and small pixel size. How can we benefit from pixels with small size and high sensitivity? In this dissertation, we study a new image senso ...

EPFL2012

Robust binary regression

Stephan Morgenthaler, Sahar Hosseinian Ehrensberger

Robust procedures increase the reliability of the results of a data analysis. We studied such a robust procedure for binary regression models based on the criterion of least absolute deviation. The resulting estimating equation consists in a simple modific ...

Elsevier2011