Publications related to Local consistency

A semi-supervised algorithm for improving the consistency of crowdsourced datasets: The COVID-19 case study on respiratory disorder classification

David Atienza Alonso, Tomas Teijeiro Campo, Lara Orlandic

Background and Objective: Cough audio signal classification is a potentially useful tool in screening for respiratory disorders, such as COVID-19. Since it is dangerous to collect data from patients with contagious diseases, many research teams have turned ...

2023

Unsupervised Visual Entity Abstraction towards 2D and 3D Compositional Models

Beril Besbinar

Object-centric learning has gained significant attention over the last years as it can serve as a powerful tool to analyze complex scenes as a composition of simpler entities. Well-established tasks in computer vision, such as object detection or instance ...

EPFL2022

A positive combinatorial formula for symplectic Kostka-Foulkes polynomials I: Rows

Thomas Gerber

We prove a conjecture of Lecouvey, which proposes a closed, positive combinatorial formula for symplectic Kostka-Foulkes polynomials, in the case of rows of arbitrary weight. To show this, we construct a new algorithm for computing cocyclage in terms of wh ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2020

Bayesian Monte Carlo assimilation for the PETALE experimental programme using inter-dosimeter correlation

Andreas Pautz, Vincent Pierre Lamirand, Dimitri Rochman, Axel Guy Marie Laureau

This article presents the methodology developed to generate and use dosimeter covariances and to estimate nuisance parameters for the PETALE experimental programme. In anticipation of the final experimental results, this work investigates the consideration ...

2020

Strong constraints on the b -> s gamma photon polarisation from B-0 -> K(*0)e(+)e(-) decays

Olivier Schneider, Aurelio Bay, Yiming Li, Guido Haefeli, Frédéric Blanc, Christoph Frei, Tatsuya Nakada, Michel De Cian, Luca Pescatore, Matthieu Philippe Luther Marinangeli, Minh Tâm Tran, François Fleuret, Pietro Marino, Federico Leo Redi, Elena Graverini, Chitsanu Khurewathanakul, Maxime Schubiger, Guido Andreassi, Renato Quagliani, Violaine Bellée, Federico Betti, Preema Rennee Pais, Pavol Stefko, Aravindhan Venkateswaran, Tara Nanut, Luis Miguel Garcia Martin, Maria Elena Stramaglia, Vitalii Lisovskyi, Vladimir Macko, Veronica Sølund Kirsebom, Guillaume Max Pietrzyk, Jian Wang, Mingkui Wang, Sebastian Schulte, Zhirui Xu, Ana Bárbara Rodrigues Cavalcante, Brice Emile Maurin, Yi Zhang, Vincenzo Battista, Lei Zhang, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,

Joint Learning of Semantic Alignment and Object Landmark Detection

Seungryong Kim

Convolutional neural networks (CNNs) based approaches for semantic alignment and object landmark detection have improved their performance significantly. Current efforts for the two tasks focus on addressing the lack of massive training data through weakly ...

IEEE2019

What Face and Body Shapes Can Tell Us About Height

Pascal Fua, Helge Jochen Rhodin, Semih Günel

Recovering a person's height from a single image is important for virtual garment fitting, autonomous driving and surveillance. However, it is also very challenging without absolute scale information. Here, we examine the rarely addressed case, where camer ...

IEEE COMPUTER SOC2019

Distributed Coupled Learning Over Adaptive Networks

Ali H. Sayed, Sulaiman A S A E Alghunaim

This work develops an effective distributed algorithm for the solution of stochastic optimization problems that involve partial coupling among both local constraints and local cost functions. While the collection of networked agents is interested in discov ...

IEEE2018

Learning Monocular 3D Human Pose Estimation from Multi-view Images

Pascal Fua, Mathieu Salzmann, Frédéric Meyer, Isinsu Katircioglu, Helge Jochen Rhodin, Victor Constantin

Accurate 3D human pose estimation from single images is possible with sophisticated deep-net architectures that have been trained on very large datasets. However, this still leaves open the problem of capturing motions for which no such database exists. Ma ...

IEEE2018

Non-Discriminatory Machine Learning through Convex Fairness Criteria

Boi Faltings, Naman Goel, Mohammad Yaghini

Biased decision making by machine learning systems is increasingly recognized as an important issue. Recently, techniques have been proposed to learn non-discriminatory classifiers by enforcing constraints in the training phase. Such constraints are either ...

ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE2018

A Framework for the Secretary Problem on the Intersection of Matroids

Ola Nils Anders Svensson, Moran Feldman, Rico Zenklusen

The secretary problem became one of the most prominent online selection problems due to its numerous applications in online mechanism design. The task is to select a maximum weight subset of elements subject to given constraints, where elements arrive one- ...

ASSOC COMPUTING MACHINERY2018

On Coordinated Primal-Dual Interior-Point Methods for Multi-Agent Optimization

Colin Neil Jones, Altug Bitlislioglu

This paper presents a coordinated primal-dual interior point (PDIP) method for solving structured convex linear and quadratic programs (LP-QP) in a distributed man- ner. The considered class of problems represents a multi-agent setting, where the aggregate ...

2017

Constraint-Flow Nets: A Model for Building Constraints from Resource Dependencies

Simon Bliudze, Alena Simalatsar, Alina Zolotukhina

The major research in the resource management literature focuses primarily on two complementary sub-problems: (1) specification languages for formulating resource requests and (2) constraint problems modelling allocation and scheduling. Both directions ass ...

Springer International Publishing2017

Fréchet means in Wasserstein space : theory and algorithms

Yoav Zemel

This work studies the problem of statistical inference for Fréchet means in the Wasserstein space of measures on Euclidean spaces,

\mathcal W_2 ( \mathbb R^d )

. This question arises naturally from the problem of separating amplitude and phase variation i ...

EPFL2017

Splines Are Universal Solutions of Linear Inverse Problems with Generalized TV Regularization

Michaël Unser, Julien René Pierre Fageot, John Paul Ward

Splines come in a variety of flavors that can be characterized in terms of some differential operator L. The simplest piecewise-constant model corresponds to the derivative operator. Likewise, one can extend the traditional notion of total variation by con ...

2017

Reconstructing Evolving Tree Structures in Time Lapse Sequences by Enforcing Time-Consistency

Pascal Fua, Engin Türetken, Raphael Sznitman, Jan Kybic, Agata Justyna Mosinska, Przemyslaw Rafal Glowacki, Miguel Amável Dos Santos Pinheiro, Daniel Lebrecht

We propose a novel approach to reconstructing curvilinear tree structures evolving over time, such as road networks in 2D aerial images or neural structures in 3D microscopy stacks acquired in vivo. To enforce temporal consistency, we simultaneously proces ...

2017

GDSP: A graphical perspective on the distributed storage systems

Michael Christoph Gastpar, Saeid Sahraei

The classical distributed storage problem can be modeled by a k-uniform complete hyper-graph where vertices represent servers and hyper-edges represent users. Hence each hyper-edge should be able to recover the full file using only the memories of the vert ...

2017

Exploiting Satisfiability Solvers for Efficient Logic Synthesis

Ana Petkovska

Logic synthesis is an important part of electronic design automation (EDA) flows, which enable the implementation of digital systems. As the design size and complexity increase, the data structures and algorithms for logic synthesis must adapt and improve ...

EPFL2017

redGEM: Systematic reduction and analysis of genome-scale metabolic reconstructions for development of consistent core metabolic models

Vassily Hatzimanikatis, Meriç Ataman, Georgios Fengos, Daniel Federico Hernandez Gardiol

Genome-scale metabolic reconstructions have proven to be valuable resources in enhancing our understanding of metabolic networks as they encapsulate all known metabolic capabilities of the organisms from genes to proteins to their functions. However the co ...

2017

A Dichotomy for Real Weighted Holant Problems

Sangxia Huang

Holant is a framework of counting characterized by local constraints. It is closely related to other well-studied frameworks such as the counting constraint satisfaction problem (#CSP) and graph homomorphism. An effective dichotomy for such frameworks can ...

Springer Basel Ag2016