Posts

Showing posts from 2014

The law of excessive gardening in education

Image
Once upon a time. the term proletarian (or a Latin equivalent) used refer to  a Roman citizen who was so poor that he only had his children considered as his property. The term proles stands here for descendants (or litter ). The term evolved through Marxism, to workers without capital or production means, who should sell their own work-force. The term can be somehow extended to the loss of knowledge of the production tools. An example lies in the comparison between the craftsman or artisan , who masters his tools, and may even be able to repair them, and manages a series of processes, as opposed to the factory worker, whose work has been taylorized and who lacks of knowledge in the whole meaning of the chain, or the functioning of the robots he "controls". The concept of proletarianization has been used more recently by Bernard Stiegler ( Ars Indutrialis ), to describe a pauperization, not in terms of wealth, but in terms of ability to do, to make and to live

Learning meets compression: small-data-science internship (IFPEN)

Image
We ( Camille Couprie / Laurent Duval ) are looking for a higly motivated master/engineering school student for an internship on the " Compatibility between sparse machine learning and lossy compression " at IFPEN. Internship subject: [ french / english ] Many experimental designs acquire continuous or salve signals or images. Those are characteristic of a specific phenomenon. One may find examples at IFPEN in seismic data/images, NDT/NDE acoustic emissions (corrosion, battery diagnosis) engine benches (cylinder pressure data, fast camera), high-thoughput screening in chemistry. Very often, such data is analyzed with standardized, a priori indices. Comparisons between different experiments (difference- or classification-based) are often based on the same indices, without resorting to initial measurements. The increasing data volume, the variability in sensor and sampling, the possibility of different pre-processing yield two problems: the management and access to

Haiku (libre) : sémantique et général

Image
La trahison des images, René Magritte Les gens qui confondent La carte et le territoire Me fatiguent un peu [En ce moment, une belle exposition Magritte thématique est à voir au centre national d'art et de culture Beaubourg-Georges Pompidou] 

Big data and Data science: LIX colloquium 2014

Image
Sketch of the Hype Cycle for Emerging Technologies Data science and Big data are two concepts at the tip of the tongue and the top of the Gartner Hype Cycle for Emerging Technologies . Close to the peak of inflated expectations. The Data science LIX colloquium 2014 at Ecole Polytechnique, organized by Michalis Vazirgiannis from DaSciM was held yesterday on the Plateau de Saclay, which may have prevented some to attend the event. Fortunately, it was webcast. The talks covered a wide range of topics pertaining to Datacy (data + literacy). The community detection in graphs (with survey) keynote promoted local optimization ( OSLOM , with order statistics). It was said than " We should define validation procedures even before starting developing algorithms ", including negative tests; on random graphs, a clustering method should find non prominent cluster (except the whole graph), in other words no signal in noise. But there was no mention to phase transition in

Cédric Villani : les mathématiques sont un art comme les autres (podcast)

Les mathématiques sont un art comme les autres, une série de cinq entretiens avec Cédric Villani (professeur de l'Université de Lyon et directeur de l'Institut Henri Poincaré), dans l'émission " Un autre jour est possible ", sur France Culture. Sur la poésie, la musique, le design, les arts de la rue et le cinéma. Cette tête chercheuse fait beaucoup et bien pour la vulgarisation des mathématiques et leur transfert innovation vers des disciplines afférentes. Louable effort. "Nul ne peut être mathématicien s'il n'a une âme de poète", disait Sophie Kowalevskaia. Les 15 et 16 décembre 2014, le forum Horizon Maths a lieu à IFP Energies nouvelles à Rueil-Malmaison (thème : "Les mathématiques se dévoilent aux industriels"), le programme en pdf est ici .En plus détaillé, après la pause podcast sur Cédric Villani. Session « Méthodes pour la chimie ab initio » Pascal Raybaud (IFPEN) : « Enjeux de la performance numérique po

BEADS: Baseline Estimation And Denoising w/ Sparsity

Image
Essentials: BEADS paper : Baseline Estimation And Denoising w/ Sparsity BEADS Matlab toolbox BEADS Baseline toolbox at MatlabCentral BEADS page: references, toolboxes and uses Most signals and images can be split into broad classes of morphological features . There are five traditional classes, with potentially different names, although the dams are not fully waterproof: smooth parts: trends, backgrounds, wanders, continuums, biases, drifts or baselines, ruptures, discontinuities: contours, edges or jumps, harmonic parts: oscillations, resonances , geometric textures, hills: bumps, blobs or peaks, noises: un-modeled, more or less random, unstructured or stochastic. In analytical chemistry,  many types of signals (chromatography, mass spectroscopy, Raman, NMR) resemble Fourier spectra: a quantity of positive bump-like peaks, representing the proportion of chemical compounds or atoms, over an instrumental baseline, with noise. Individual  isolated peaks Supe

Geophysics: Taking signal and noise to new dimensions

Image
Edit (2015/12/25): the special issue is  out (Geophysics, Nov.-Dec. 2015), the editorial is here . Call for papers: Taking signal and noise to new dimensions The journal (from SEG: Society of Exploration Geophysicists) Geophysics ( SCImago journal ranking ) has issued a call for papers for a special issue devoted to signal processing (" Taking signal and noise to new dimensions "), deadline end January 2015. Original seismic stack Large Gaussian noise corruption Denoised with dual-tree wavelets Taking signal and noise to new dimensions Editors: Laurent Duval ( IFP Energies nouvelles ), Sergey Fomel ( University of Texas, Austin ), Mostafa Naghizadeh ( Shell Canada ), Mauricio Sacchi ( University of Alberta ) Scope:   The inherent complexity of seismic data has sparked, since about half a century, the development of innovative techniques to separate signal and noise. Localized time-scale representations (e. g. wavelets), parsim

Cours : Radial basis functions

Image
Un message d' Albert Cohen annonce un mini-cours : "Interpolation et Quasi-Interpolation utilisant les fonctions radiales comme méthode d'approximation de plusieurs variables" Le professeur Martin Buhmann (Université de Justus-Liebig, Giessen), de l’Université de Giessen, fera le lundi 22 septembre au laboratoire J.L. Lions un mini-cours de 2h sur les bases de fonction radiales . Ces outils sont fréquement utilisés en approximation multivariée, en particulier en grande dimension, en statistiques (méthodes à noyaux), et parfois dans le traitement de l’image et l’approximation des EDP. Martin Buhmann est un expert reconnu dans ce domaine. Le cours aura lieu de 16:00 à 18:30 en salle 309 (salle de séminaire du LJLL ) couloir 15-16, 3ème étage, Jussieu.  Radial version of the Laplacian of a Gaussian wavelet Le résumé (en français !) Les méthodes utilisant les fonctions radiales sont des façons d'approcher une fonction par une combinaison l

Euclid in a Taxicab makes some SOOT : A smoothed l_1/l_2 norm ratio for sparsity enforcement and blind restoration

Image
[This post deals with a smoothed l1/l2 norm ratio as a proxy for sparsity (called continuous numerical sparsity in Discrete uncertainty principles and sparse signal processing by Afonso Bandeira, Megan Lewis, Dustin Mixon, 2015), applied to blind signal deconvolution with an example on seismic data] Matlab toolbox: SOOT Sparse Blind deconvolution toolbox or http://lc.cx/soot Smoothed $\ell_1/\ell_2$ norm ratio for $\ell_0$ approximation (paper fortune teller/cootie catcher) There are Taxicab services in the city of Euclid , OH, near Cleveland. There is a first Euclid Avenue , in Cleveland, was a beautiful and wealthy city a century ago, with a string of mansions known as Millionaire's Row. According to wikipedia, " Euclid Avenue is a street name used in multiple U.S. municipalities. Surveyors frequently named a street after Euclid (or Euclides) the father of geometry as it is the basis of their profession".  I wonder why i have seen so far so fe

Seismic Signal Processing (ICASSP 2014)

Image
There was a special session on " Seismic Signal Processing " at International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014, Florence. Our talk was on simplified optimization techniques to solve multiple reflections via adaptive filtering techniques in wavelet frame domains. A constrained-based optimization approach for seismic data recovery problems  Mai Quyen Pham , Caroline Chaux , Laurent Duval , Jean-Christophe Pesquet Special session on " SS5 - Seismic Signal Processing ", International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014 , Florence, Italy [ journal paper + blog +arxiv+ paper + slides ]  Random and structured noise both affect seismic data, hiding the reflections of interest (primaries) that carry meaningful geophysical interpretation. When the structured noise is composed of multiple reflections, its adaptive cancellation is obtained through time-varying filtering, compensating inaccuracie

Sparse template-based adaptive filtering

Image
Significance index related to Student's t-test The phenomenon arises in several real-life signal processing contexts: acoustic echo-cancellation (AEC) in sound and speech,  non-destructive testing where transmitted waves may rebound at material interfaces (e.g. ultrasounds), or pattern matching in images . Here in seismic reflection or seismology . Weak signals (of interest) are buried under both strong random and structured noise. Provided appropriate templates are obtained, we propose a structured-pattern filtering algorithm (called Ricochet) through constrained adaptive filtering in a  transformed domain. Its generic methodology impose sparsity: in different wavelet frames (Haar, Daubechies, Symmlets) coefficients, using the L-1 or Manhattan norm , as well as on adaptive filter coefficients using concentration measures (for sparser filters in the time domain): L-1, the Frobenius norm squared, and the mixed L-1,2 norms). Regularity properties are constrained as well