Deep Learning (DL) is growing in popularity because it exploits rather well the unreasonable effectiveness of data to solve complex problems in machine learning. In fact, multi scale machine perception tasks such as object and speech recognitions using DL have recently outperformed systems that have been under development for many years. The principles of DL, and its ability to capture multi scale representations, are very general and the technology can be applied to many other problem domains, which makes it quite attractive. The IEEE DL'16 Symposium will be held simultaneously with other symposia and workshops in one location at the 2016 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2016) in Greece. Sponsored by the IEEE Computational Intelligence Society, this event will attract top scientists, researchers, professionals, practitioners and students from around the world. The registration to SSCI 2016 will allow participants to attend all the symposia, including the complete set of the proceedings of all the meetings, coffee breaks, lunches, and the banquet.
Topics of IEEE DL’16 include but are not limited to:
Unsupervised, semi-supervised, and supervised learning
Deep reinforcement learning (deep value function estimation, policy learning and stochastic control)
Memory Networks and differentiable programming
Multi-task learning
Learning from multiple modalities
Weakly supervised learning
Metric learning and kernel learning
Dimensionality expansion and sparse modeling
Learning representations from large-scale data
Hierarchical models
Implementation issues, both software and hardware platforms
Applications in vision, audio, speech, natural language processing, robotics, navigation, control, games AI, cognitive architectures, etc.
12月06日
2016
12月09日
2016
注册截止日期
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