Download PLEASE UPDATE with TRACK CHANGES

PLEASE UPDATE with TRACK CHANGES
VERSION 1 – Wouter Haerick
UPDATE 1 – Tom Dhaene
UPDATE 2 – Dirk Deschrijver
UPDATE 3 - Ivo Couckuyt
UPDATE 4 – Joni Dambre
Input for IDLab website:
Machine Learning & data mining
1. Topic Title
Machine Learning & Data Mining
2. Short text
Target Length: max. 2 lines
State-of-the-art machine learning techniques for image, video and sensor data
processing (neural networks, Gaussian process regression and latent variable models,
…)
3. Long text
Target Length: max. 20 lines
Intro-text: 2 lines - why this domain is important nowadays
The volume of data that companies are gathering is increasing rapidly. Traditional data
analytic tools hit their limits. They suffer in processing real-time data streams, and do
not easily scale towards big data sets. Novel algorithms, tools and platforms, such as
SPARC, HADOOP, KAFKA, HIVE… however open new opportunities.
IDLab Subtopics: 10 lines – text with subfields we address and why we are well positioned
At IDLab, we offer the full spectrum of machine learning and artificial intelligence
expertise. This covers supervised learning (classification, regression, …), unsupervised
learning (clustering, data pattern recognition, …) and reinforcement learning. Deep
neural networks for image, video, audio and sensor signal analysis/classification,
probabilistic generative models, and deep Q-learning for robotics and game applications
are only some of the techniques we are mastering.
Our experts tackle the most complex data challenges, and differentiate with automated
machine learning solutions. These solutions apply machine learning techniques to
optimize the hyperparameters and to select the best machine learning model.
Datasets are often not so well suited to apply machine learning straight away. At IDLab,
we have built the expertise to facilitate dimensionality reduction, outlier detection,
mitigation of missing data, denoising of data, feature extraction, model selection and
hyper parameterization, and sensitivity analysis
Examples: 8 lines one or two examples
The data scientists at IDLab are internationally recognized for their machine learning
insights and capabilities.
* In 2016, a team of IDLab scientists finished among the winners of US 2nd National Data
Science Bowl (on Kaggle.com), with a machine learning algorithm to automatically
determine cardiac volumes from MRI scans. In 2015, this team also won the “Deep Sea”
challenge , out of 1049 teams, in the 1st National Data Science Bowl.
* The surrogate modeling (SUMO) toolbox for data-efficient machine learning,
developed at IDLab, is recognized worldwide as state-of-the-art, and has been
downloaded more than 3000 times across the globe. Licenses have been requested by
players in automotive, bay-area based semi-conductor companies, etc. The toolbox can
be used as an add-on to popular simulation and design automation platforms (ANSYS,
…).
At IDLab, the data scientists from different labs, previously known as MultimediaLab,
Reservoir Lab, Data Science Lab, and Surrogate Modeling Lab, are joining forces.
4. Picture:
Add image that illustrates the field / demonstrates technologie.
Adapt the short texts: