£73.29

Springer Dual Learning

Name: Dual Learning
Brand: Springer
Price: 73.29 GBP
Availability: InStock

AI & Machine Learning

It has never been this cheap. We have no record of a lower price.

£73 today · cheaper than every other day in the last 3 months

NEW HERE?

Amazon shows you one price. We show you all of them.

Tosheroon watches Amazon prices so you don't have to. Every product on Amazon has a price history — we make it visible. Set the price you'd actually pay, and we'll email you the second it gets there. No app, no account, one email.

WHAT'S ON THIS PAGE

↓ Price chart
when this has been cheap or pricey

↓ Forecast
where the price is heading next

↓ Statistics
all-time high & low, recent range

↑ Price alert
name your number, we'll email you

Price History & Forecast

Grey patches = out of stock. Cheaper = lower on the chart. Hover for exact prices.

Last 48 days • 48 data points (No recent data available)

Historical

Generating forecast...

Price Distribution

Price distribution over 48 days • 1 price levels

Days at Price

Price Analysis

Most common price: £73 (48 days, 100.0%)

Price range: £73 - £73

Price levels: 1 different prices over 48 days

Description

Many AI (and machine learning) tasks present in dual forms, e.g., English-to-Chinese translation vs. Chinese-to-English translation, speech recognition vs. speech synthesis,question answering vs. question generation, and image classification vs. image generation. Dual learning is a new learning framework that leverages the primal-dual structure of AI tasks to obtain effective feedback or regularization signals in order to enhance the learning/inference process. Since it was first introduced four years ago, the concept has attracted considerable attention in multiple fields, and been proven effective in numerous applications, such as machine translation, image-to-image translation, speech synthesis and recognition, (visual) question answering and generation, image captioning and generation, and code summarization and generation. Offering a systematic and comprehensive overview of dual learning, this book enables interested researchers (both established and newcomers) and practitioners to gain a better understanding of the state of the art in the field. It also provides suggestions for further reading and tools to help readers advance the area. The book is divided into five parts. The first part gives a brief introduction to machine learning and deep learning. The second part introduces the algorithms based on the dual reconstruction principle using machine translation, image translation, speech processing and other NLP/CV tasks as the demo applications. It covers algorithms, such as dual semi-supervised learning, dual unsupervised learning and multi-agent dual learning. In the context of image translation, it introduces algorithms including CycleGAN, DualGAN, DiscoGAN cdGAN and more recent techniques/applications. The third part presents various work based on the probability principle, including dual supervised learning and dual inference based on the joint-probability principle and dual semi-supervised learning based on the marginal-probability principle. The fourth part reviews various theoretical studies on dual learning and discusses its connections to other learning paradigms. The fifth part provides a summary and suggests future research directions.

Product Specifications

Brand: Springer
Format: hardcover
ASIN: 981158883X
Category: Books > Subjects > Computing & Internet > Computer Science > AI & Machine Learning
Domain: Amazon UK
Release Date: 14 November 2020
Listed Since: 18 August 2020

Barcode

No barcode data available

Springer Dual Learning

It has never been this cheap. We have no record of a lower price.

Price History & Forecast

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

Generative Adversarial Learning: Architectures and Applications: 217 (Intelligent Systems Reference Library, 217)

Machine Learning: From the Classics to Deep Networks, Transformers, and Diffusion Models

Deep Learners and Deep Learner Descriptors for Medical Applications: 186 (Intelligent Systems Reference Library, 186)

Deep Learning: A Visual Approach

Advanced Topics in Intelligent Information and Database Systems: 710 (Studies in Computational Intelligence, 710)

Penguin Random House Deep Learning (Adaptive Computation and Machine Learning series)

Springer Deep Neural Evolution - Deep Learning and EC Book

Recent Advances in Information and Communication Technology 2018: Proceedings of the 14th International Conference on Computing and Information ... in Intelligent Systems and Computing, 769)

Advances in Computer Science for Engineering and Education III: 1247 (Advances in Intelligent Systems and Computing, 1247)

Geometry of Deep Learning: A Signal Processing Perspective: 37 (Mathematics in Industry, 37)

Proceedings of the 22nd Engineering Applications of Neural Networks Conference: EANN 2021: 3 (Proceedings of the International Neural Networks Society, 3)

Springer Deep Learning in Healthcare: Paradigms and Applications

Data Science and Predictive Analytics: Biomedical and Health Applications using R (The Springer Series in Applied Machine Learning)

Data Science and Predictive Analytics: Biomedical and Health Applications using R (The Springer Series in Applied Machine Learning)

Progress in Image Processing, Pattern Recognition and Communication Systems: Proceedings of the Conference (CORES, IP&C, ACS) - June 28-30 2021: 255 (Lecture Notes in Networks and Systems, 255)

Modern Approaches in Machine Learning and Cognitive Science: A Walkthrough: Latest Trends in AI, Volume 2: 956 (Studies in Computational Intelligence, 956)

Multimedia Analysis, Processing and Communications: 346 (Studies in Computational Intelligence, 346)

Math and Architectures of Deep Learning

Python Deep Learning: Exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow

Proceedings of the 21st EANN (Engineering Applications of Neural Networks) 2020 Conference: Proceedings of the EANN 2020: 2 (Proceedings of the International Neural Networks Society, 2)

Learning Deep Architectures for AI (Foundations and Trends® in Machine Learning)

Synthetic Data for Deep Learning: 174 (Springer Optimization and Its Applications, 174)

Handbook of Research on AI and ML for Intelligent Machines and Systems

Deep Learning For 3d Vision: Algorithms And Applications