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{ "item_title" : "Recent Advances in Big Data and Deep Learning", "item_author" : [" Luca Oneto", "Nicolò Navarin", "Alessandro Sperduti "], "item_description" : "On the trade-off between number of examples and precision of supervision in regression.- Distributed SmSVM Ensemble Learning.- Size/Accuracy Trade-off in Convolutional Neural Networks: An Evolutionary Approach.- Fast transfer learning for image polarity detection.- Dropout for Recurrent Neural Networks.- Psychiatric disorders classification with 3D Convolutional Neural Networks.- Perturbed Proximal Descent to Escape Saddle Points for Non-convex and Non-smooth Objective Functions.- Deep-learning domain adaptation techniques for credit cards fraud detection.- Selective Information Extraction Strategies for Cancer Pathology Reports with Convolutional Neural Networks.- An information theoretic approach to the autoencoder.- Deep Regression Counting: Customized Datasets and Inter-Architecture Transfer Learning.- Improving Railway Maintenance Actions with Big Data and Distributed Ledger Technologies.", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/3/03/016/840/3030168409_b.jpg", "price_data" : { "retail_price" : "169.99", "online_price" : "169.99", "our_price" : "169.99", "club_price" : "169.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Recent Advances in Big Data and Deep Learning|Luca Oneto

Recent Advances in Big Data and Deep Learning : Proceedings of the Inns Big Data and Deep Learning Conference Innsbddl2019, Held at Sestri Levante, Gen

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Overview

On the trade-off between number of examples and precision of supervision in regression.- Distributed SmSVM Ensemble Learning.- Size/Accuracy Trade-off in Convolutional Neural Networks: An Evolutionary Approach.- Fast transfer learning for image polarity detection.- Dropout for Recurrent Neural Networks.- Psychiatric disorders classification with 3D Convolutional Neural Networks.- Perturbed Proximal Descent to Escape Saddle Points for Non-convex and Non-smooth Objective Functions.- Deep-learning domain adaptation techniques for credit cards fraud detection.- Selective Information Extraction Strategies for Cancer Pathology Reports with Convolutional Neural Networks.- An information theoretic approach to the autoencoder.- Deep Regression Counting: Customized Datasets and Inter-Architecture Transfer Learning.- Improving Railway Maintenance Actions with Big Data and Distributed Ledger Technologies.


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Details

  • ISBN-13: 9783030168407
  • ISBN-10: 3030168409
  • Publisher: Springer
  • Publish Date: April 2019
  • Dimensions: 9.21 x 6.14 x 0.83 inches
  • Shipping Weight: 1.24 pounds
  • Page Count: 392

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