Results 141 to 150 of about 141,184 (170)
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2017
This chapter gives a broad overview and a historical context around the subject of deep learning. It also gives the reader a roadmap for navigating the book, the prerequisites, and further reading to dive deeper into the subject matter.
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This chapter gives a broad overview and a historical context around the subject of deep learning. It also gives the reader a roadmap for navigating the book, the prerequisites, and further reading to dive deeper into the subject matter.
openaire +1 more source
Error Analysis of Stochastic Gradient Descent Ranking
IEEE Transactions on Cybernetics, 2013Ranking is always an important task in machine learning and information retrieval, e.g., collaborative filtering, recommender systems, drug discovery, etc. A kernel-based stochastic gradient descent algorithm with the least squares loss is proposed for ranking in this paper.
Chen, Hong +5 more
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Ant Colony Optimization and Stochastic Gradient Descent
Artificial Life, 2002In this article, we study the relationship between the two techniques known as ant colony optimization (ACO) and stochastic gradient descent. More precisely, we show that some empirical ACO algorithms approximate stochastic gradient descent in the space of pheromones, and we propose an implementation of stochastic gradient descent that belongs to the ...
Meuleau, Nicolas, Dorigo, Marco
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Stochastic Gradient Descent with GPGPU
2012We show how to optimize a Support Vector Machine and a predictor for Collaborative Filtering with Stochastic Gradient Descent on the GPU, achieving 1.66 to 6-times accelerations compared to a CPU-based implementation. The reference implementations are the Support Vector Machine by Bottou and the BRISMF predictor from the Netflix Prices winning team ...
David Zastrau, Stefan Edelkamp
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Resampling Stochastic Gradient Descent Cheaply
2023 Winter Simulation Conference (WSC), 2023Henry Lam, Zitong Wang
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Stochastic Geometry Analysis of Spatial-Temporal Performance in Wireless Networks: A Tutorial
IEEE Communications Surveys and Tutorials, 2021Xiao Lu, Mohammad Salehi, Martin Haenggi
exaly
Detection methods for stochastic gravitational-wave backgrounds: a unified treatment
Living Reviews in Relativity, 2017Joseph D Romano, Neil Cornish
exaly