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Specifically, we proposed a novel ℓ2,1 norm balanced multiple kernel feature selection (ℓ2,1 MKFS), and designed a proximal based optimization algorithm for efficiently learning the model.
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Ebbinhaus' quarry was the recipe for a perfect memory -- or at least for the formula for most efficiently learning new information.
Ebbinhaus' quarry was the recipe for a perfect memory -- or at least for the formula for most efficiently learning new information.
Pieter Abbeel and Adam Coates developed apprenticeship learning algorithms that leverage expert demonstrations to efficiently learn good controllers for the tasks being demonstrated by an expert.
Policy Reuse is a reinforcement learning technique that efficiently learns a new policy by using past similar learned policies.
Reinforcement learning is a plausible theoretical basis for developing self-learning, autonomous agents or robots that can effectively represent the world dynamics and efficiently learn the problem features to perform different tasks in different environments.
Momentum tuning is critical for efficiently training deep learning models.
Amari, S.-i Natural gradient works efficiently in learning.
In the present study, we propose a method for using learning machines efficiently in an evolving context.
Moreover, for efficiently handling out-of-sample extension and learning with the local consistency, we decompose the manifold learning as a two-step approach.
In this paper, we propose a fast fixed-point learning algorithm for efficiently implementing maximization of the harmony function on Gaussian mixture with automated model selection.
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CEO of Professional Science Editing for Scientists @ prosciediting.com