Mathematics for Big Data
News
June 2018: The MSCA-ITN-EID project BIGMATH has been funded!
Presentations
Optimization, learning, and statistics for Big Data
Joao Xavier, Distributed learning algorithms for Big Data
Alessandra Micheletti, A clustering algorithm for multivariate big data with correlated components
Stefania Bellavia, A Levenberg-Marquardt method for large-scale noisy nonlinear least squares problems
Milan Merkle, Calculation of high-dimensional Tukey median
Dragana Bajovic, Hypothesis testing for stochastic graph processes
Dusan Jakovetic, Distributed optimization methods with randomized agents’ activities
Hanno Gottschalk, Student projects on statistical learning with companies of all sizes
Matti Heilio. Big Models and CUDA
Big Data for communication engineering
Branka Vucetic, Next-generation Telecommunication Networks: Carriers and Users of Big Data
Dejan Vukobratovic, David Murray, H2020 SENSIBLE project: Big Data Analytics for Intelligent Buildings
Biosense Institute: Data analytics in biosystems and agri-food
Sanja Brdar, Exploring Microbial World with Clustering Algorithms - Challenges and Perspectives
Predrag Lugonja, Satellite Image Processing for Sustainable Agriculture
Oskar Marko, Yield Prediction and Seed Selection using Data Analytics
Marko Panic, Hyperspectral Imaging for Fruits and Vegetables Quality Assessment
Data analytics for text and image processing
Stefano Iacus, Sentiment Analysis over Big Data
Aleksandra Pizurica, Sparse Coding and Multimodal Dictionary Learning in Computer Vision
Big Data applications in industry
Industrial case studies
Lara Quijano Sanchez, The BIG CHASE: A decision support system for client acquisition applied to financial networks
Content Insights, Ognjen Zelenbabic: Editorial analytics and big data