Artificial Intelligence (AI) has been applied successfully to many fields such as data analysis, finance, multimedia, signal and image processing, web technologies, robotics, and automations, etc. Machine learning, as a major technology behind AI, is changing the world rapidly by deploying varied algorithms. For example, artificial neural networks, especially those for deep learning, are implemented in real world such as the GPU computations owing to the maturity of high-speed and parallel architecture. The latter is also becoming a promising research field for further explorations. Many researches of machine learning are inspired by the developments of computational intelligence. How machine learning can be contributed to varied applications related to intelligence is the main focus of this special session. The methodologies of machine learning may include mathematical or statistical foundations, algorithms, architectures, and uncertainty issues. As for applications of machine learning, we look forward to including researches or implementations in varied fields which are emerged to intelligence and automation. For future trends of machine learning, we encourage authors to propose their innovative ideas and concepts. We offer an opportunity for researchers and practitioners to identify new promising research directions as well as to publish recent advances in this area.
The scope of the MLMAT 2017 includes, but is not limited to the following topics:
Algorithms of machine learning
Mathematical foundations of machine learning
Machine learning based on probability and statistics
Classifications based on machine learning
Supervised learning and non-supervised learning
Machine learning based on rough sets or fuzzy set theory
Methodologies of computational intelligence
GPU-based parallel computation and deep learning implementations
Big data and machine learning
IoT and machine learning
Decision making by machine learnings
FinTech and machine learning
Intelligent systems with machine learning
Machine learning in medicines, medical diagnosis and health care
Uncertainty based on machine learning
Impact of machine learning to AI
07月03日
2017
07月05日
2017
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