WorldCat Identities

Bottou, Léon

Overview
Works: 17 works in 46 publications in 2 languages and 1,517 library holdings
Genres: Conference papers and proceedings  Academic theses 
Roles: Author, Other, Editor, 958, wpr
Publication Timeline
.
Most widely held works by Léon Bottou
Large-scale kernel machines by Léon Bottou( )

13 editions published between 2007 and 2016 in English and held by 1,326 WorldCat member libraries worldwide

"This volume offers researchers and engineers practical solutions for learning from large-scale datasets, with detailed descriptions of algorithms and experiments carried out on realistically large datasets. At the same time it offers researchers information that can address the relative lack of theoretical grounding for many useful algorithms."--Jacket
Perceptrons : an introduction to computational geometry by Marvin Minsky( )

3 editions published in 2017 in English and held by 92 WorldCat member libraries worldwide

Computing Methodologies -- Artificial Intelligence
Advances in neural information processing systems 17 : proceedings of the 2004 conference by Lawrence K Saul( Book )

8 editions published in 2005 in English and held by 42 WorldCat member libraries worldwide

On layer-wise representations in deep neural networks by Grégoire Montavon( )

1 edition published in 2013 in English and held by 15 WorldCat member libraries worldwide

Proceedings, Twenty-sixth International Conference on Machine Learning by International Conference on Machine Learning( Book )

3 editions published in 2009 in English and held by 9 WorldCat member libraries worldwide

TDNN-extracted features by Xavier Driancourt( Book )

2 editions published in 1990 in English and held by 4 WorldCat member libraries worldwide

A framework for the coopération of learning algorithms by Léon Bottou( Book )

3 editions published in 1991 in English and held by 4 WorldCat member libraries worldwide

Speaker independent isolated digit recognition : multilayer perceptrons vs dynamic time warping by Léon Bottou( Book )

2 editions published in 1990 in English and held by 4 WorldCat member libraries worldwide

Factor graphs for relational regression by Sumit Prakash Chopra( )

1 edition published in 2008 in English and held by 4 WorldCat member libraries worldwide

The models are applied to predicting the prices of real estate properties. A by-product of it is a house price index. The relational aspect of the model accounts for the hidden spatio-temporal influences on the price of every house. The experiments show that one can achieve considerably superior performance by identifying and using the underlying spatio-temporal structure associated with the problem. To the best of our knowledge this is the first work in the direction of relational regression, especially in the frame-based class of statistical relational learning models. Furthermore, this is also the first work in constructing house price indices by simultaneously accounting for the spatio-temporal effects on house prices using large-scale industry standard data set
Comparison and cooperation of several classifiers by Xavier Driancourt( Book )

3 editions published in 1991 in English and held by 4 WorldCat member libraries worldwide

Proceedings of the 26th Annual International Conference on Machine Learning : 2009, Montreal, Quebec, Canada, June 14-18, 2009 by International Conference on Machine Learning( )

1 edition published in 2007 in English and held by 4 WorldCat member libraries worldwide

Towards real-time image understanding with convolutional networks by Clément Farabet( )

1 edition published in 2013 in English and held by 2 WorldCat member libraries worldwide

One of the open questions of artificial computer vision is how to produce good internal representations of the visual world. What sort of internal representation would allow an artificial vision system to detect and classify objects into categories, independently of pose, scale, illumination, conformation, and clutter ? More interestingly, how could an artificial vision system {em learn} appropriate internal representations automatically, the way animals and humans seem to learn by simply looking at the world ? Another related question is that of computational tractability, and more precisely that of computational efficiency. Given a good visual representation, how efficiently can it be trained, and used to encode new sensorial data. Efficiency has several dimensions: power requirements, processing speed, and memory usage. In this thesis I present three new contributions to the field of computer vision:(1) a multiscale deep convolutional network architecture to easily capture long-distance relationships between input variables in image data, (2) a tree-based algorithm to efficiently explore multiple segmentation candidates, to produce maximally confident semantic segmentations of images,(3) a custom dataflow computer architecture optimized for the computation of convolutional networks, and similarly dense image processing models. All three contributions were produced with the common goal of getting us closer to real-time image understanding. Scene parsing consists in labeling each pixel in an image with the category of the object it belongs to. In the first part of this thesis, I propose a method that uses a multiscale convolutional network trained from raw pixels to extract dense feature vectors that encode regions of multiple sizes centered on each pixel. The method alleviates the need for engineered features. In parallel to feature extraction, a tree of segments is computed from a graph of pixel dissimilarities. The feature vectors associated with the segments covered by each node in the tree are aggregated and fed to a classifier which produces an estimate of the distribution of object categories contained in the segment. A subset of tree nodes that cover the image are then selected so as to maximize the average "purity" of the class distributions, hence maximizing the overall likelihood that each segment contains a single object (...)
Statistical learning and data science( Book )

1 edition published in 2012 in English and held by 2 WorldCat member libraries worldwide

"Data analysis is changing fast. Driven by a vast range of application domains and affordable tools, machine learning has become mainstream. Unsupervised data analysis, including cluster analysis, factor analysis, and low dimensionality mapping methods continually being updated, have reached new heights of achievement in the incredibly rich data world that we inhabit. Statistical Learning and Data Science is a work of reference in the rapidly evolving context of converging methodologies. It gathers contributions from some of the foundational thinkers in the different fields of data analysis to the major theoretical results in the domain. On the methodological front, the volume includes conformal prediction and frameworks for assessing confidence in outputs, together with attendant risk. It illustrates a wide range of applications, including semantics, credit risk, energy production, genomics, and ecology. The book also addresses issues of origin and evolutions in the unsupervised data analysis arena, and presents some approaches for time series, symbolic data, and functional data. Over the history of multidimensional data analysis, more and more complex data have become available for processing. Supervised machine learning, semi-supervised analysis approaches, and unsupervised data analysis, provide great capability for addressing the digital data deluge. Exploring the foundations and recent breakthroughs in the field, Statistical Learning and Data Science demonstrates how data analysis can improve personal and collective health and the well-being of our social, business, and physical environments."--
UNE APPROCHE THEORIQUE DE L'APPRENTISSAGE CONNEXIONNISTE ET APPLICATIONS A LA RECONNAISSANCE DE LA PAROLE by Léon Bottou( Book )

1 edition published in 1991 in French and held by 2 WorldCat member libraries worldwide

LA THESE EXPOSE PLUSIEURS POINTS THEORIQUES CONCERNANT L'APPRENTISSAGE CONNEXIONNISTE, PROVENANT DES MATHEMATIQUES DES ALGORITHMES ADAPTATIFS ET DES STATISTIQUES. CES POINTS SONT DISCUTES A LA LUMIERE DE PROBLEMES PRATIQUES POSES PAR LA RECONNAISSANCE AUTOMATIQUE DE LA PAROLE
Proceedings : [Montréal, Canada, June 14-18, 2009 ; proceedings]( Book )

1 edition published in 2009 in English and held by 1 WorldCat member library worldwide

Proceedings of the 2004 conference( Book )

1 edition published in 2005 in English and held by 1 WorldCat member library worldwide

Une approche theorique de l'apprentissage connexioniste : application a la reconnaissance de la parole by Léon Bottou( Book )

1 edition published in 1991 in French and held by 1 WorldCat member library worldwide

 
moreShow More Titles
fewerShow Fewer Titles
Audience Level
0
Audience Level
1
  Kids General Special  
Audience level: 0.12 (from 0.04 for Large-scal ... to 0.99 for Towards re ...)

Large-scale kernel machines
Covers
Advances in neural information processing systems 17 : proceedings of the 2004 conferenceStatistical learning and data scienceProceedings of the 2004 conference
Alternative Names
Léon Bottou Frans wiskundige

Léon Bottou fransk matematikar, informatikar og ingeniør

Léon Bottou fransk matematiker, datavetare och ingenjör

Léon Bottou fransk matematiker, informatiker og ingeniør

Léon Bottou French mathematician and computer scientist

Languages
English (44)

French (2)