## Neural Networks: Tricks of the Trade : by an increase in available

Neural Networks: Tricks of the Trade power. In parallel to this trend, the focus of neural network research and the practice...

Author : Grégoire Montavon, Geneviève Orr, Klaus-Robert Müllerof neural network research and the practice of training neural networks has undergone a number

Publisher : Springertraining neural networks has undergone a number of important changes, for example, use of deep

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example, use of deep learning machines. The second edition of the book augments the first## Neural Networks: Tricks of the Trade : by an increase in available data

Neural Networks: Tricks of the Trade power. In parallel to this trend, the focus of neural network research and the practice of...

Author : Grégoire Montavon, Geneviève Orr, Klaus-Robert Müllerof neural network research and the practice of training neural networks has undergone a number of

Publisher : Springertraining neural networks has undergone a number of important changes, for example, use of deep learning

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example, use of deep learning machines. The second edition of the book augments the first edition## Neural Networks: Tricks of the Trade : practitioners acquire, through experience and word-of-mouth, techniques and

Neural Networks: Tricks of the Trade heuristics that help them successfully apply neural networks to di cult real world problems....

Author : Genevieve B. Orr, Klaus-Robert Müllerto di cult real world problems. Often these \tricks" are theo- tically well motivated.

Publisher : Springer\tricks" are theo- tically well motivated. Sometimes they are the result of trial and

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of trial and error. However, their most common link is that they are usually## From Statistics to Neural Networks : to neural networks, theory and pattern recognition applications

From Statistics to Neural Networks took place in Les Arcs, Bourg Saint Maurice, France, from June 21 through July 2,...

Author : Vladimir Cherkassky, Jerome H. Friedman, Harry WechslerFrance, from June 21 through July 2, 1993. The meeting brought to gether over 100

Publisher : Springer Science & Business MediaThe meeting brought to gether over 100 participants (including 19 invited lecturers) from 20 countries.

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lecturers) from 20 countries. The invited lecturers whose contributions appear in this volume are: L.## Advances in Intelligent Signal Processing and Data Mining : efficient statistical and deterministic methods for

Advances in Intelligent Signal Processing and Data Mining and applications in order to extract targeted information and find hidden patterns. The techniques presented range from...

Author : Petia Georgieva, Lyudmila Mihaylova, Lakhmi C Jainand find hidden patterns. The techniques presented range from Bayesian approaches and their variations such as sequential

Publisher : Springerfrom Bayesian approaches and their variations such as sequential Monte Carlo methods, Markov Chain Monte Carlo filters,

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methods, Markov Chain Monte Carlo filters, Rao Blackwellization, to the biologically inspired paradigm of Neural Networks and## Introduction to Deep Learning : engaging first introduction to deep learning,

Introduction to Deep Learning wide range of connectionist models which represent the current state-of-the-art. The text explores the most popular...

Author : Sandro Skansicurrent state-of-the-art. The text explores the most popular algorithms and architectures in a simple and intuitive

Publisher : Springeralgorithms and architectures in a simple and intuitive style, explaining the mathematical derivations in a step-by-step

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mathematical derivations in a step-by-step manner. The content coverage includes convolutional networks, LSTMs, Word2vec, RBMs, DBNs,## Connectionism : modeling through practical exercises in

Connectionism architectures. explores three different types of connectionist architectures– distributed associative memory, perceptron, and multilayerperceptron provides a...

Author : Michael R. W. Dawsondistributed associative memory, perceptron, and multilayerperceptron provides a brief overview of each architecture, a detailedintroduction on

Publisher : John Wiley & Sonsbrief overview of each architecture, a detailedintroduction on how to use a program to explore this

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a program to explore this network, and aseries of practical exercises that are designed to highlight## Neural Networks in a Softcomputing Framework : most popular neural-network methods and

Neural Networks in a Softcomputing Framework Each chapter provides state-of-the-art descriptions of important major research results of...

Author : Ke-Lin Du, M.N.S. Swamyresearch results of the respective neural-network methods. A range of relevant

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evolutionary algorithms – powerful tools for neural-network learning – are introduced.## Outlier Analysis : field of outlier analysis from a

Outlier Analysis point of view. It integrates methods from data mining, machine learning, and statistics within...

Author : Charu C. Aggarwalmining, machine learning, and statistics within the computational framework and therefore appeals to multiple

Publisher : Springerframework and therefore appeals to multiple communities. The chapters of this book can be

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book can be organized into three categories: Basic algorithms: Chapters 1 through 7 discuss## Probability and Statistics for Computer Science : undergraduates late in sophomore or early

Probability and Statistics for Computer Science year, supplying a comprehensive background in qualitative and quantitative data analysis, probability, random...

Author : David Forsythquantitative data analysis, probability, random variables, and statistical methods, including machine learning. With

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the curricular needs for the course, Probability and Statistics for Computer Science features:## Proceedings of the 1993 Connectionist Models Summer School : summer school, the papers in this

Proceedings of the 1993 Connectionist Models Summer School the tremendous breadth and depth of research underway in the field of neural...

Author : Michael C. Mozer, Paul Smolensky, David S. Touretzky, Jeffrey L. Elman, Andreas S. Weigendin the field of neural networks. Although the slant of the summer school

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and artificial intelligence, the diverse scientific backgrounds and research interests of accepted students## Information Theory, Inference and Learning Algorithms : underpinning the most dynamic areas of

Information Theory, Inference and Learning Algorithms and engineering....

Author : David J. C. MacKay Publisher : Cambridge University Press 9780521642989ISBN

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## Introduction to Parallel Computing : software development have fueled rapid growth

Introduction to Parallel Computing and distributed computing. However, this development is only of practical benefit...

Author : Roman Trobec, Boštjan Slivnik, Patricio Bulić, Borut Robičof practical benefit if it is accompanied by progress in the

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concise textbook provides, in one place, three mainstream parallelization approaches, Open## Neural Networks and Deep Learning : models in deep learning. the

Neural Networks and Deep Learning on the theory and algorithms of deep learning. The theory and algorithms of neural...

Author : Charu C. AggarwalThe theory and algorithms of neural networks are particularly important for understanding important concepts,

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the important design concepts of neural architectures in different applications. Why do neural networks## Reinforcement Learning : of a widely used text on reinforcement

Reinforcement Learning one of the most active research areas in artificial intelligence. Reinforcement learning, one of the...

Author : Richard S. Sutton, Andrew G. Bartoartificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is

Publisher : A Bradford Bookactive research areas in artificial intelligence, is a computational approach to learning whereby an agent

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learning whereby an agent tries to maximize the total amount of reward it receives while## Professional Search in the Modern World : of the cost action ic1002 on

Professional Search in the Modern World Multifaceted Interactive Information Access, MUMIA. It contains outstanding research, recent developments and new...

Author : Georgios Paltoglou, Fernando Loizides, Preben Hansenresearch, recent developments and new directions in all related aspects of multifaceted and

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on professional and enterprise search. The contributions are grouped in the following three## Introduction to Deep Learning Business Applications for Developers : of deep learning from a business perspective with

Introduction to Deep Learning Business Applications for Developers technical examples. These applications include image recognition, segmentation and annotation, video processing and annotation, voice recognition, intelligent...

Author : Armando Vieira, Bernardete Ribeiroand annotation, video processing and annotation, voice recognition, intelligent personal assistants, automated translation, and autonomous vehicles. An

Publisher : Apressintelligent personal assistants, automated translation, and autonomous vehicles. An Introduction to Deep Learning Business Applications for Developers

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Deep Learning Business Applications for Developers covers some common DL algorithms such as content-based recommendation algorithms and## Neural Networks and Deep Learning : to get your self-driving car pick

Neural Networks and Deep Learning kids from school? Want to add 'Deep Learning' to your LinkedIn profile? Well,...

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deep learning, there is basic theory to march through first! Take a step-by-step