LARCA UPC
9 SlideShares 2 Abonné
Personal Information
Entreprise/Lieu de travail
Barcelona, Catalonia Spain
Secteur d’activité
Technology / Software / Internet
Site Web
recerca.upc.edu/larca
À propos
LARCA is an international research group working on data mining, machine learning, data analysis, and mathematical linguistics. We typically approach problems from sound mathematical principles, using modelling tools and techniques from algorithmics, computational complexity, automata theory, logic, discrete mathematics, statistics, and dynamic systems. We are also starting partnerships with companies and other institutions to apply our solutions to real-world problems.
Mots-clés
machine learning data mining clustering data streams multi instance weka eibe frank spectral learning networks anton dries graphs gemma garriga aris gionis geoff holmes regression ensembles indrė Žliobaitė adaptive pre-processing joao gama distributed
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Présentations

(9)
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Adaptive pre-processing for streaming data

il y a 12 ans • 1449 Vues

Distributed clustering from data streams

il y a 12 ans • 771 Vues

Semi-random model tree ensembles: an effective and scalable regression method

il y a 12 ans • 588 Vues

Machine Learning Application Development

il y a 12 ans • 720 Vues

Overlapping correlation clustering

il y a 12 ans • 1249 Vues

A discussion on sampling graphs to approximate network classification functions

il y a 12 ans • 1497 Vues

A query language for analyzing networks

il y a 12 ans • 560 Vues

Spectral Learning Methods for Finite State Machines with Applications to Natural Language Tagging and Parsing

il y a 12 ans • 773 Vues

Experiments with Randomisation and Boosting for Multi-instance Classification

il y a 12 ans • 956 Vues
Personal Information
Entreprise/Lieu de travail
Barcelona, Catalonia Spain
Secteur d’activité
Technology / Software / Internet
Site Web
recerca.upc.edu/larca
À propos
LARCA is an international research group working on data mining, machine learning, data analysis, and mathematical linguistics. We typically approach problems from sound mathematical principles, using modelling tools and techniques from algorithmics, computational complexity, automata theory, logic, discrete mathematics, statistics, and dynamic systems. We are also starting partnerships with companies and other institutions to apply our solutions to real-world problems.
Mots-clés
machine learning data mining clustering data streams multi instance weka eibe frank spectral learning networks anton dries graphs gemma garriga aris gionis geoff holmes regression ensembles indrė Žliobaitė adaptive pre-processing joao gama distributed
Tout plus