Conferences

29 August–1 September 2017, Reggio Calabria, Italy
International Cross Domain (CD) Conference for Machine Learning & Knowledge Extraction (MAKE) CD-MAKE 2017

Machine learning deals with understanding intelligence for the design and development of algorithms that can learn from data and improve over time. The original definition was “the artificial generation of knowledge from experience”. The challenge is to discover relevant structural patterns and/or temporal patterns (“knowledge”) in such data, which are often hidden and not accessible to a human. Today, machine learning is the fastest growing technical field, having many application domains, e.g. health, Industry 4.0, recommender systems, speech recognition, autonomous driving, etc. The challenge is in decision making under uncertainty, and probabilistic inference enormously influenced artificial intelligence and statistical learning. The inverse probability allows to infer unknowns, learn from data and make predictions to support decision making. Whether in social networks, recommender systems, health or Industry 4.0 applications, the increasingly complex data sets require efficient, useful and useable solutions for knowledge discovery and knowledge extraction.

A synergistic combination of methodologies and approaches of two domains offer ideal conditions towards unraveling these challenges and to foster new, efficient and user-friendly machine learning algorithms and knowledge extraction tools: Human-Computer Interaction (HCI) and Knowledge Discovery/Data Mining (KDD), aiming at augmenting human intelligence with computational intelligence and vice versa.

Consequently, successful Machine Learning & Knowledge extraction needs a concerted international effort without boundaries, supporting collaborative and integrative cross-disciplinary research between experts from 7 (the magical number seven +/- 0) fields (image below):

❶ Data science (i.e. data fusion, data preprocessing, data mapping, knowledge representation),
❷ Machine learning algorithms,
❸ Graphical models/network science,
❹ Topological data analytics,
❺ Time/entropy,
❻ Data visualization, and last but not least – and with increasing imporance in and for our ML-society:
❼ Privacy, data protection, safety and security.

The goal of the CD-MAKE conference is to bring together researchers from these seven areas in an cross-disciplinary manner, to stimulate fresh ideas and to encourage multi-disciplinary problem solving.

https://cd-make.net/

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