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Composite Relationship Fields with Transformers for Scene Graph Generation

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Adaptive hot water production based on Supervised Learning

Alexandre Massoud Alahi, Dolaana Khovalyg, Amirreza Heidari

A major challenge in the common approach of hot water generation in residential houses lies in the highly stochastic nature of domestic hot water (DHW) demand. Learning hot water use behavior enables water heating systems to continuously adapt to the stoch ...

2021

ResOT: Resource-Efficient Oblique Trees for Neural Signal Classification

Mahsa Shoaran, Bingzhao Zhu

Classifiers that can be implemented on chip with minimal computational and memory resources are essential for edge computing in emerging applications such as medical and IoT devices. This paper introduces a machine learning model based on oblique decision ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Monitoring of Cardiovascular and Neurological Diseases Using Wearable Devices

Dionisije Sopic

In this thesis, I focus on monitoring of patients suffering from cardiovascular and neurological diseases through the use of wearable devices. The main diseases considered in this thesis are atrial fibrillation (AF), myocardial infarction (MI), and epileps ...

EPFL2020

MonoLoco: Monocular 3D Pedestrian Localization and Uncertainty Estimation

Alexandre Massoud Alahi, Sven Kreiss, Lorenzo Bertoni

We tackle the fundamentally ill-posed problem of 3D human localization from monocular RGB images. Driven by the limitation of neural networks outputting point estimates, we address the ambiguity in the task by predicting confidence intervals through a loss ...

2019

Multiscale Centerline Extraction Based on Regression and Projection onto the Set of Elongated Structures

Amos Sironi

Automatically extracting linear structures from images is a fundamental low-level vision problem with numerous applications in different domains. Centerline detection and radial estimation are the first crucial steps in most Computer Vision pipelines aimin ...

EPFL2016

Robust image classification : analysis and applications

Alhussein Fawzi

In the past decade, image classification systems have witnessed major advances that led to record performances on challenging datasets. However, little is known about the behavior of these classifiers when the data is subject to perturbations, such as rand ...

EPFL2016

Weak teachers: assisted specification of discrete choice models using ensemble learning algorithms

Timothy Michael Hillel

Discrete Choice Models (DCMs) have a distinct advantage over Machine Learning (ML) classification algorithms, in that they employ a highly interpretable linear structure. However, a key drawback of DCMs compared to ML is the need to specify the utility fun ...

2019

Real-Time Event-Driven Classification Technique for Early Detection and Prevention of Myocardial Infarction on Wearable Systems

David Atienza Alonso, Amir Aminifar, Dionisije Sopic

A considerable portion of government health-care spending is allocated to the continuous monitoring of patients suffering from cardiovascular diseases, particularly myocardial infarction (MI). Wearable devices present a cost-effective means of monitoring p ...

2018

Graph-based Isometry Invariant Representation Learning

Pascal Frossard, Renata Khasanova

Learning transformation invariant representations of visual data is an important problem in computer vision. Deep convolutional networks have demonstrated remarkable results for image and video classification tasks. However, they have achieved only limited ...

2017

Integration of scientific and social networks

In this paper, we address the problem of scientific-social network integration to find a matching relationship between members of these networks (i.e. The DBLP publication network and the Twitter social network). This task is a crucial step toward building ...

Springer2014

Real-time classification technique for early detection and prevention of myocardial infarction on wearable devices

David Atienza Alonso, Amir Aminifar, Dionisije Sopic

Continuous monitoring of patients suffering from cardiovascular diseases and, in particular, myocardial infarction (MI) places a considerable burden on health-care systems and government budgets. The rise of wearable devices alleviates this burden, allowin ...

IEEE2017

Optimal Classification In Sparse Gaussian Graphic Model

Zhigang Yao

Consider a two-class classification problem where the number of features is much larger than the sample size. The features are masked by Gaussian noise with mean zero and covariance matrix Sigma, where the precision matrix Omega = Sigma(-1) is unknown but ...

Institute of Mathematical Statistics2013

Understanding and Decoding Imagined Speech using Electrocorticographic Recordings in Humans

Stéphanie Martin

Certain brain disorders, resulting from brainstem infarcts, traumatic brain injury, stroke and amyotrophic lateral sclerosis, limit verbal communication despite the patient being fully aware. People that cannot communicate due to neurological disorders wou ...

EPFL2017

Fast Object Detection with Entropy-Driven Evaluation

Pascal Fua, François Fleuret, Raphael Sznitman, Carlos Joaquin Becker

Cascade-style approaches to implementing ensemble classifiers can deliver significant speed-ups at test time. While highly effective, they remain challenging to tune and their overall performance depends on the availability of large validation sets to esti ...

2013

Multi-task additive models with shared transfer functions based on dictionary learning

Pascal Frossard, Alhussein Fawzi

Additive models form a widely popular class of regression models which represent the relation between covariates and response variables as the sum of low-dimensional transfer functions. Besides flexibility and accuracy, a key benefit of these models is the ...

Institute of Electrical and Electronics Engineers2017