Publications associées à Parameterized SVM for Personalized Drug Concentration Prediction

Publications associées (29)

Efficient Temporally-Aware DeepFake Detection using H.264 Motion Vectors

Peter Arpad Grönquist, Sabine Süsstrunk, Yufan Ren

Video DeepFakes are fake media created with Deep Learning (DL) that manipulate a person’s expression or identity. Most current DeepFake detection methods analyze each frame independently, ignoring inconsistencies and unnatural movements between frames. Som ...

2024

The JPEG AI Standard: Providing Efficient Human and Machine Visual Data Consumption

Touradj Ebrahimi

The Joint Photographic Experts Group (JPEG) AI learning-based image coding system is an ongoing joint standardization effort between International Organization for Standardization (ISO), International Electrotechnical Commission (IEC), and International Te ...

IEEE COMPUTER SOC2023

Communication-efficient distributed training of machine learning models

Thijs Vogels

In this thesis, we explore techniques for addressing the communication bottleneck in data-parallel distributed training of deep learning models. We investigate algorithms that either reduce the size of the messages that are exchanged between workers, or th ...

EPFL2023

Automated Human Motion Analysis and Synthesis

Sena Kiciroglu

Human motion analysis and synthesis is integral to many computer vision applications, from autonomous driving to sports analysis. In this thesis, we address several problems in this domain. First we consider active viewpoint selection for pose estimation w ...

EPFL2023

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

On Block Prediction For Learning-Based Point Cloud Compression

Touradj Ebrahimi, Evangelos Alexiou, Davi Nachtigall Lazzarotto

Point clouds are among popular visual representations for immersive media. However, the vast amount of information generated during their acquisition requires effective compression for practical applications. Although relevant activities from standardizati ...

IEEE2021

Learning-based Image Coding: Early Solutions Reviewing and Subjective Quality Evaluation

Touradj Ebrahimi, Pinar Akyazi

Nowadays, image and video are the data types that consume most of the resources of modern communication channels, both in fixed and wireless networks. Thus, it is vital to compress visual data as much as possible, while maintaining some target quality leve ...

SPIE-INT SOC OPTICAL ENGINEERING2021

NUQSGD: Provably Communication-efficient Data-parallel SGD via Nonuniform Quantization

Dan Alistarh

As the size and complexity of models and datasets grow, so does the need for communication-efficient variants of stochastic gradient descent that can be deployed to perform parallel model training. One popular communication-compression method for data-para ...

Microtome Publishing2021

Structures of ABCG2 under turnover conditions reveal a key step in the drug transport mechanism

Henning Paul-Julius Stahlberg, Dongchun Ni

ABCG2 is a multidrug transporter that affects drug pharmacokinetics and contributes to multidrug resistance of cancer cells. In previously reported structures, the reaction cycle was halted by the absence of substrates or ATP, mutation of catalytic residue ...

Nature Research2021

Comprehensive assessment of image compression algorithms

Touradj Ebrahimi, Michela Testolina, Evgeniy Upenik

JPEG image coding standard has been a dominant format in a wide range of applications in soon three decades since it has been released as an international standard. The landscape of applications and services based on pictures has evolved since the original ...

SPIE2020

Subjective and Viewport-based Objective Quality Assessment of 360-degree Videos

Pascal Frossard, Roberto Gerson De Albuquerque Azevedo

Visual distortions in processed 360-degree visual content and consumed through head-mounted displays (HMDs) are perceived very differently when compared to traditional 2D content. To better understand how compression-related artifacts affect the overall pe ...

2020

Disentangling feature and lazy training in deep neural networks

Matthieu Wyart, Mario Geiger, Stefano Spigler, Arthur Ulysse Jacot-Guillarmod

Two distinct limits for deep learning have been derived as the network width h -> infinity, depending on how the weights of the last layer scale with h. In the neural tangent Kernel (NTK) limit, the dynamics becomes linear in the weights and is described b ...

IOP PUBLISHING LTD2020

Statistically-Motivated Second-order Pooling

Mathieu Salzmann, Kaicheng Yu

Second-order pooling, a.k.a. bilinear pooling, has proven effective for deep learning based visual recognition. However, the resulting second-order networks yield a final representation that is orders of magnitude larger than that of standard, first-order ...

2018

Learning Robust Features and Latent Representations for Single View 3D Pose Estimation of Humans and Objects

Bugra Tekin

Estimating the 3D poses of rigid and articulated bodies is one of the fundamental problems of Computer Vision. It has a broad range of applications including augmented reality, surveillance, animation and human-computer interaction. Despite the ever-growin ...

EPFL2018

Towards an algebraic network information theory: Simultaneous joint typicality decoding

Michael Christoph Gastpar, Adriano Pastore, Sung Hoon Lim, Chen Feng

Recent work has employed joint typicality encoding and decoding of nested linear code ensembles to generalize the compute-forward strategy to discrete memoryless multiple-access channels (MACs). An appealing feature of these nested linear code ensembles is ...

2017

Light field compression using translation-assisted view estimation

Touradj Ebrahimi, Irene Viola

Light field technology has recently been gaining traction in the research community. Several acquisition technologies have been demonstrated to properly capture light field information, and portable devices have been commercialized to the general public. H ...

IEEE2019

Privacy-Friendly Photo Sharing and Relevant Applications Beyond

Lin Yuan

Popularization of online photo sharing brings people great convenience, but has also raised concerns for privacy. Researchers proposed various approaches to enable image privacy, most of which focus on encrypting or distorting image visual content. In this ...

EPFL2017

Design and Applications of Approximate Circuits by Gate-Level Pruning

Christian Enz, Vincent Frédéric Camus, Jérémy Lucien Maurice Schlachter

Energy-efficiency is a critical concern for many systems, ranging from Internet of things objects and mobile devices to high-performance computers. Moreover, after 40 years of prosperity, Moore's law is starting to show its economic and technical limits. N ...

Ieee-Inst Electrical Electronics Engineers Inc2017

Adaptive Learning-Based Compressive Sampling for Low-power Wireless Implants

Yusuf Leblebici, Volkan Cevher, Catherine Dehollain, Mahsa Shoaran, Luca Baldassarre, Franco Maloberti, Cosimo Aprile, Kerim Türe, Gürkan Yilmaz

Implantable systems are nowadays being used to interface the human brain with external devices, in order to understand and potentially treat neurological disorders. The most predominant design constraints are the system’s area and power. In this paper, we ...

2018

TUCUXI: TUCUXI: An Intelligent System for Personalized Medicine from Individualization of Treatments to Research Databases and Back

Karl Aberer, Michael Ignaz Schumacher, Yann Thoma, Alevtina Dubovitskaya

Therapeutic Drug Monitoring (TDM) is a key concept in precision medicine. The goal of TDM is to avoid therapeutic failure or toxic effects of a drug due to insufficient or excessive circulating concentration exposure related to between-patient variability ...

2017