Publications related to Vector quantization

Convex Quantization Preserves Logconcavity

A logconcave likelihood is as important to proper statistical inference as a convex cost function is important to variational optimization. Quantization is often disregarded when writing likelihood models, ignoring the limitations of the physical detectors ...

IEEE Institute of Electrical and Electronics Engineers2022

Quantization for Distributed Processing and Learning of Structured Data

Isabela Cunha Maia Nobre

In the domains of machine learning, data science and signal processing, graph or network data, is becoming increasingly popular. It represents a large portion of the data in computer, transportation systems, energy networks, social, biological, and other s ...

EPFL2022

Remote sensing visual question answering with a self-attention multi-modal encoder

Devis Tuia, Joao Magalhaes

Visual Question Answering (VQA) on remote sensing imagery can help non-expert users in extracting information from Earth observation data. Current approaches follow a neural encoder-decoder design, combining convolutional and recurrent encoders together wi ...

2022

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

Benchmarking of objective quality metrics for point cloud compression

Touradj Ebrahimi, Davi Nachtigall Lazzarotto, Evangelos Alexiou

Point cloud is a promising imaging modality for the representation of 3D media. The vast volume of data associated with it requires efficient compression solutions, with lossy algorithms leading to larger bit-rate savings at the expense of visual impairmen ...

IEEE2021

Perceptual Quality of Point Clouds with application to Compression

Evangelos Alexiou

Modern information technologies and human-centric communication systems employ advanced content representations for richer portrayals of the real world. The newly adopted imaging modalities offer additional information cues and permit the depiction of real ...

EPFL2021

Large-Scale Crowdsourcing Subjective Quality Evaluation of Learning-Based Image Coding

Touradj Ebrahimi, Evgeniy Upenik, Michela Testolina

Learning-based image codecs produce different compression artifacts, when compared to the blocking and blurring degradation introduced by conventional image codecs, such as JPEG, JPEG~2000 and HEIC. In this paper, a crowdsourcing based subjective quality e ...

IEEE2021

Distributed Learning in Non-Convex Environments-Part II: Polynomial Escape From Saddle-Points

Ali H. Sayed, Stefan Vlaski

The diffusion strategy for distributed learning from streaming data employs local stochastic gradient updates along with exchange of iterates over neighborhoods. In Part I [3] of this work we established that agents cluster around a network centroid and pr ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Distributed Learning in Non-Convex Environments-Part I: Agreement at a Linear Rate

Ali H. Sayed, Stefan Vlaski

Driven by the need to solve increasingly complex optimization problems in signal processing and machine learning, there has been increasing interest in understanding the behavior of gradient-descent algorithms in non-convex environments. Most available wor ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Wavelet-Fourier CORSING techniques for multidimensional advection-diffusion-reaction equations

Fabio Nobile, Simone Brugiapaglia

We present and analyze a novel wavelet-Fourier technique for the numerical treatment of multidimensional advection–diffusion–reaction equations based on the COmpRessed SolvING (CORSING) paradigm. Combining the Petrov–Galerkin technique with the compressed ...

2021

Toward a Dynamic Threshold for Quality-Score Distortion in Reference-Based Alignment

Marco Mattavelli, Claudio Paolo Alberti, Ana Angelica Hernandez Lopez

The intrinsic high entropy metadata, known as quality scores, are largely the cause of the substantial size of sequence data files. Yet, there is no consensus on a viable reduction of the resolution of the quality score scale, arguably because of collatera ...

2019

On the relevance of quality score metadata in genomic sequence data for omics applications

Ana Angelica Hernandez Lopez

High-throughput sequencing of DNA molecules has revolutionized biomedical research by enabling the quantitative analysis of the genome to study its function, structure and dynamics. It is driving sequencing-based experiments in life sciences as evidenced b ...

EPFL2019

Polynomial Escape-Time From Saddle Points In Distributed Non-Convex Optimization

Ali H. Sayed, Stefan Vlaski

The diffusion strategy for distributed learning from streaming data employs local stochastic gradient updates along with exchange of iterates over neighborhoods. In this work we establish that agents cluster around a network centroid in the mean-fourth sen ...

IEEE2019

Diffusion Learning In Non-Convex Environments

Ali H. Sayed, Stefan Vlaski

Driven by the need to solve increasingly complex optimization problems in signal processing and machine learning, recent years have seen rising interest in the behavior of gradient-descent based algorithms in non-convex environments. Most of the works on d ...

IEEE2019

Approximate Cloaking via Transformation Optics for Electromagnetic Waves

Xuan Loc Tran

Cloaking via transformation optics was introduced by Pendry, Schurig, and Smith for the Maxwell system and Leonhardt in the geometric optics setting. They used a singular change of variables which blows up a point into a cloaked region. The same transforma ...

EPFL2018

Optimal Lagrange Multipliers for Dependent Rate Allocation in Video Coding

Pascal Frossard, Ana Karina De Abreu Goes

In a typical video rate allocation problem, the objective is to optimally distribute a source rate budget among a set of (in)dependently coded data units to minimize the total distortion. Conventional Lagrangian approaches convert the lone rate constraint ...

Elsevier2018

Machine learning-based tools to model and to remove the off-target effect

François Fleuret

A RNA interference, also called a gene knockdown, is a biological technique which consists of inhibiting a targeted gene in a cell. By doing so, one can identify statistical dependencies between a gene and a cell phenotype. However, during such a gene inhi ...

Springer2017

Jump-Penalized Least Absolute Values Estimation of Scalar or Circle-Valued Signals

Michaël Unser, Martin Kurt Storath

We study jump-penalized estimators based on least absolute deviations which are often referred to as Potts estimators. They are estimators for a parsimonious piecewise constant representation of noisy data having a noise distribution which has heavier tail ...

Oxford University Press2017

Towards large scale multimedia indexing

Jean-Marc Odobez

The rapid growth of multimedia databases and the human interest in their peers make indices representing the location and identity of people in audio-visual documents essential for searching archives. Person discovery in the absence of prior identity knowl ...

2017

Band structure diagram paths based on crystallography

Giovanni Pizzi

Systematic and automatic calculations of the electronic band structure are a crucial component of computationally-driven high-throughput materials screening. An algorithm, for any crystal, to derive a unique description of the crystal structure together wi ...

Elsevier2017