Publications associées à Learning Image Descriptors with Boosting

Enabling Uncertainty Estimation in Iterative Neural Networks

Pascal Fua, Doruk Oner, Nikita Durasov, Minh Hieu Lê

Turning pass-through network architectures into iterative ones, which use their own output as input, is a well-known approach for boosting performance. In this paper, we argue that such architectures offer an additional benefit: The convergence rate of the ...

Curran Associates2024

Self-Supervised Learning for Patient Stratification and Survival Analysis in Computational Pathology: An Application to Colorectal Cancer

Christian Robert Abbet

Over the years, clinical institutes accumulated large amounts of digital slides from resected tissue specimens. These digital images, called whole slide images (WSIs), are high-resolution tissue snapshots that depict the complex interaction of cells at the ...

EPFL2023

Optimization Over Banach Spaces: A Unified View on Supervised Learning and Inverse Problems

Shayan Aziznejad

In this thesis, we reveal that supervised learning and inverse problems share similar mathematical foundations. Consequently, we are able to present a unified variational view of these tasks that we formulate as optimization problems posed over infinite-di ...

EPFL2022

Learning the Exciton Properties of Azo-dyes

Anne-Clémence Corminboeuf, Alberto Fabrizio, Sergio Vela Llausi, Ksenia Briling

The ab initio determination of electronic excited state (ES) properties is the cornerstone of theoretical photochemistry. Yet, traditional ES methods become impractical when applied to fairly large molecules, or when used on thousands of systems. Machine l ...

AMER CHEMICAL SOC2021

Recursive Input And State Estimation: A General Framework For Learning From Time Series With Missing Data

Robert West, Alberto Garcia Duran

Time series with missing data are signals encountered in important settings for machine learning. Some of the most successful prior approaches for modeling such time series are based on recurrent neural networks that transform the input and previous state ...

IEEE2021

A Deeper Look at the Energy Consumption of Lightweight Block Ciphers

Francesco Regazzoni, Andrea Felice Caforio, Muhammed Fatih Balli, Subhadeep Banik

In the last few years, the field of lightweight cryptography has seen an influx in the number of block ciphers and hash functions being proposed. In the past there have been numerous papers that have looked at circuit level implementation of block ciphers ...

IEEE2021

Vehicle sharing systems: A review and a holistic management framework

Michel Bierlaire, Nikola Obrenovic, Selin Ataç

Although different vehicle sharing systems (VSSs) use different vehicle types, the management challenges and optimization problems to be solved are similar or even the same. This observation led us to create a generalized and holistic VSS management framew ...

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

Time in cryptography

Gwangbae Choi

Time travel has always been a fascinating topic in literature and physics. In cryptography, one may wonder how to keep data confidential for some time. In this dissertation, we will study how to make private information travel to the future. This dissertat ...

EPFL2020

A novel biomechanical approach for animal behaviour recognition using accelerometers

Kamiar Aminian, Pritish Chakravarty

Data from animal-borne inertial sensors are widely used to investigate several aspects of an animal's life, such as energy expenditure, daily activity patterns and behaviour. Accelerometer data used in conjunction with machine learning algorithms have b ...

2019

Model-based predictive control methods for distributed energy resources in smart grids

Luca Fabietti

This thesis develops optimization-based techniques for the control of distributed energy resources to provide multiple services to the power network. It is divided into three parts. The first part of this thesis focuses on the development of a framework f ...

EPFL2019

Closing the Performance Gap Between Volatile and Persistent Key-Value Stores Using Cross-Referencing Logs

Matej Pavlovic

Key-Value (K-V) stores are an integral building block in modern datacenter applications. With byteaddressable persistent memory (PM) technologies, such as Intel/Micron's 3D XPoint, on the horizon, there has been an influx of new high performance K-V stores ...

USENIX ASSOC2018

Log-Free Concurrent Data Structures

Rachid Guerraoui, Aleksandar Dragojevic, Mihail Igor Zablotchi, Tudor Alexandru David

Non-volatile RAM (NVRAM) makes it possible for data structures to tolerate transient failures, assuming however that programmers have designed these structures such that their consistency is preserved upon recovery. Previous ap- proaches are typically tran ...

USENIX Association2018

Log-Free Concurrent Data Structures

Rachid Guerraoui, Aleksandar Dragojevic, Mihail Igor Zablotchi, Tudor Alexandru David

Non-volatile RAM (NVRAM) makes it possible for data structures to tolerate transient failures, assuming however that programmers have designed these structures such that their consistency is preserved upon recovery. Previous approaches are typically transa ...

USENIX ASSOC2018

Elastic transactions

Pascal Felber, Rachid Guerraoui, Vincent Gramoli

This paper presents elastic transactions, an appealing alternative to traditional transactions, in particular to implement search structures in shared memory multicore architectures. Upon conflict detection, an elastic transaction might drop what it did so ...

Academic Press Inc Elsevier Science2017

Efficient Logging in Non-Volatile Memory by Exploiting Coherency Protocols

James Richard Larus, Nachshon Cohen

Non-volatile memory (NVM) technologies such as PCM, ReRAM and STT-RAM allow processors to directly write values to persistent storage at speeds that are significantly faster than previous durable media such as hard drives or SSDs. Many applications of NVM ...

ACM2017

Vision-based detection of aircrafts and UAVs

Artem Rozantsev

Unmanned Aerial Vehicles are becoming increasingly popular for a broad variety of tasks ranging from aerial imagery to objects delivery. With the expansion of the areas, where drones can be efficiently used, the collision risk with other flying objects inc ...

EPFL2017

Optimistic Concurrency with OPTIK

Rachid Guerraoui, Vasileios Trigonakis

We introduce OPTIK, a new practical design pattern for designing and implementing fast and scalable concurrent data structures. OPTIK relies on the commonly-used technique of version numbers for detecting conflicting concurrent operations. We show how to i ...

ACM Press2016

Towards Scalable Segmentation of 3D Image Stacks

Carlos Joaquin Becker

Imaging modalities such as Electron Microscopy (EM) and Light Microscopy (LM) can now deliver high-quality, high-resolution image stacks of neural structures. Though these imaging modalities can be used to analyze a variety of components that are critical ...

EPFL2016

Learning to Match Aerial Images with Deep Attentive Architectures

Pascal Fua, Eduard Trulls Fortuny, Hani Altwaijry

Image matching is a fundamental problem in Computer Vision. In the context of feature-based matching, SIFT and its variants have long excelled in a wide array of applications. However, for ultra-wide baselines, as in the case of aerial images captured unde ...

2016