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The IEEE Transactions on Learning Technologies (TLT) is a peer-reviewed scientific journal covering advances in the development of technologies for supporting human learning. It was established in 2008 and is published by the IEEE Education Society. [1] The current editor-in-chief (since 2022) is Minjuan Wang of San Diego State University.
The publications of the Institute of Electrical and Electronics Engineers (IEEE) constitute around 30% of the world literature in the electrical and electronics engineering and computer science fields, [citation needed] publishing well over 100 peer-reviewed journals. [1]
The reparameterization trick (aka "reparameterization gradient estimator") is a technique used in statistical machine learning, particularly in variational inference, variational autoencoders, and stochastic optimization.
IEEE Transactions on Neural Networks and Learning Systems is a monthly peer-reviewed scientific journal published by the IEEE Computational Intelligence Society. It covers the theory, design, and applications of neural networks and related learning systems. According to the Journal Citation Reports, the journal had a 2021 impact factor of 14. ...
In 1996, Nikolopoulos completed his bachelor's in computer engineering and informatics at the University of Patras. [1] [2] In 1997 he completed his master's and in 2000 he completed his Ph.D. in computer engineering at the same University. [7]
Reinforcement learning (RL) is an interdisciplinary area of machine learning and optimal control concerned with how an intelligent agent should take actions in a dynamic environment in order to maximize a reward signal.
Model-free RL algorithms can start from a blank policy candidate and achieve superhuman performance in many complex tasks, including Atari games, StarCraft and Go.Deep neural networks are responsible for recent artificial intelligence breakthroughs, and they can be combined with RL to create superhuman agents such as Google DeepMind's AlphaGo.
In pattern recognition, the iDistance is an indexing and query processing technique for k-nearest neighbor queries on point data in multi-dimensional metric spaces.The kNN query is one of the hardest problems on multi-dimensional data, especially when the dimensionality of the data is high.