Machine Theory

Embeddings provide concrete numerical representations of otherwise abstract items, for use in downstream tasks. For example, a biologist might look for subfamilies of related cells by clustering embedding vectors associated with individual cells, while a...

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Over the last decade, Approximate Message Passing (AMP) algorithms have become extremely popular in various structured high-dimensional statistical problems. Many of the original ideas of AMP were developed in the physics and engineering literature and...

Thompson sampling is an algorithm for online decision problems where actions are taken sequentially in a manner that must balance between exploiting what is known to maximize immediate performance and investing to accumulate new information that may...

A multi-armed bandit problem - or, simply, a bandit problem - is a sequential allocation problem defined by a set of actions. At each time step, a unit resource is allocated to an action and some observable payoff is obtained. The goal is to maximize the...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9781601985460Author Shai Shalev-ShwartzFormat PaperbackPage Count 102Imprint now publishers IncPublisher now publishers IncWeight(grams) 156gDimensions(mm)...

Deep reinforcement learning is the combination of reinforcement learning (RL) and deep learning. This field of research has recently been able to solve a wide range of complex decision-making tasks that were previously out of reach for a machine. Deep RL...

Datasets are growing not just in size but in complexity, creating a demand for rich models and quantification of uncertainty. Bayesian methods are an excellent fit for this demand, but scaling Bayesian inference is a challenge. In response to this...

An Introduction to Conditional Random Fields provides a comprehensive tutorial aimed at application-oriented practitioners seeking to apply CRFs. The monograph does not assume previous knowledge of graphical modeling, and so is intended to be useful to...

As data is a predominant resource in applications, Riemannian geometry is a natural framework to model and unify complex nonlinear sources of data. However, the development of computational tools from the basic theory of Riemannian geometry is laborious...

Random matrix theory plays a central role in statistical physics, computational mathematics and engineering sciences, including data assimilation, signal processing, combinatorial optimization, compressed sensing, econometrics and mathematical finance,...

Among the data structures commonly used in machine learning, graphs are arguably one of the most general. Graphs allow the modelling of complex objects, each of which can be annotated by metadata. Nonetheless, seemingly simple questions, such as...

A popular method for selecting the number of clusters is based on stability arguments: one chooses the number of clusters such that the corresponding clustering results are most stable. In recent years, a series of papers has analyzed the behavior of...

Reinforcement learning (RL) is one of the foundational pillars of artificial intelligence and machine learning. An important consideration in any optimization or control problem is the notion of risk, but its incorporation into RL has been a fairly...

Sparse estimation methods are aimed at using or obtaining parsimonious representations of data or models. They were first dedicated to linear variable selection but numerous extensions have now emerged such as structured sparsity or kernel selection. It...

Randomized algorithms for very large matrix problems have received a great deal of attention in recent years. Much of this work was motivated by problems in large-scale data analysis, largely since matrices are popular structures with which to model data...

This book presents some new concentration inequalities for Feynman-Kac particle processes. It analyzes different types of stochastic particle models, including particle profile occupation measures, genealogical tree based evolution models, particle free...

Provides a simple and clear description of explicit-duration modeling by categorizing the different approaches into three main groups, which differ in encoding in the explicit-duration variables different information about regime switching/reset...

A key strategy in machine learning is to break down a problem into smaller and more manageable parts, then process data or unknown variables recursively. Sequential Monte Carlo (SMC) is a technique for solving statistical inference problems recursively...

Learning Representation and Control in Markov Decision Processes describes methods for automatically compressing Markov decision processes (MDPs) by learning a low-dimensional linear approximation defined by an orthogonal set of basis functions. A unique...

This book constitutes the thoroughly refereed post-conference proceedings of the 12th International Conference on Membrane Computing, CMC 2011, held in Fontainebleau, France, in August 2011. The 19 revised selected papers presented were carefully...

The two-volume set LNCS 6852/6853 constitutes the refereed proceedings of the 17th International Euro-Par Conference held in Bordeaux, France, in August/September 2011. The 81 revised full papers presented were carefully reviewed and selected from 271...

This book and its sister volume collect refereed papers presented at the 7th Inter- tional Symposium on Neural Networks (ISNN 2010), held in Shanghai, China, June 6-9, 2010. Building on the success of the previous six successive ISNN symposiums, ISNN has...

This book constitutes the refereed proceedings of the sixth International Conference on Artificial Neural Networks - ICANN 96, held in Bochum, Germany in July 1996. The 145 papers included were carefully selected from numerous submissions on the basis of...

This book constitutes the refereed proceedings of the 7th International Conference on Artificial Immune Systems, ICARIS 2008, held in Phuket, Thailand, in August 2008. The 40 revised full papers presented were carefully reviewed and selected from 67...

This book constitutes the refereed proceedings of the 8th International Conference on Cellular Automata for Research and Industry, ACRI 2008, held in Yokohama, Japan, in September 2008. The 43 revised full papers and 22 revised poster papers presented...

This book constitutes the refereed proceedings of the 6th International Conference on Simulated Evolution and Learning, SEAL 2006, held in Hefei, China in October 2006. The 117 revised full papers presented were carefully reviewed and selected from 420...

"What joy to discern the minute in in?nity, the vast to perceive in the small, what divinity!" Jacob Bernoulli (1654-1705) in Ars Conjectandi (1713) We are proud to present to you the proceedings of the Sixth International C- ference on...

The three volume set LNCS 3496/3497/3498 constitutes the refereed proceedings of the Second International Symposium on Neural Networks, ISNN 2005, held in Chongqing, China in May/June 2005. The 483 revised papers presented were carefully reviewed and...

Stergios Papadimitriou and Lefteris Moussiades begin Chapter One by comparing and contrasting some aspects of ScalaLab and GroovyLab, the MATLAB-like environments for the Java Virtual Machine. Additionally, this chapter highlights the strengths and...

Email has become an indispensable communication tool in daily life. However, high volumes of spam waste resources, interfere with productivity, and present severe threats to computer system security and personal privacy. This book introduces research on...

This volume contains a selection of papers presented at the 10th Workshop on Membrane Computing, WMC 2009, which took place in Curtea de Arge, s, Romania, during August 24-27, 2009. The?rstthreeWorkshopsonMembraneComputingwereorganizedinCurtea de Arge,...

The two-volume set IFIP AICT 363 and 364 constitutes the refereed proceedings of the 12th International Conference on Engineering Applications of Neural Networks, EANN 2011, and the 7th IFIP WG 12.5 International Conference, AIAI 2011, held jointly in...

The two-volume set LNCS 6852/6853 constitutes the refereed proceedings of the 17th International Euro-Par Conference held in Bordeaux, France, in August/September 2011. The 81 revised full papers presented were carefully reviewed and selected from 271...

This book constitutes the refereed proceedings of the 13th International Workshop of Descriptional Complexity of Formal Systems 2011, held in Limburg, Germany, in July 2011. The 21 revised full papers presented together with 4 invited papers were...

This book constitutes the refereed proceedings of the 7th Conference on Computability in Europe, CiE 2011, held in Sofia, Bulgaria, in June/July 2011. The 22 revised papers presented together with 11 invited lectures were carefully reviewed and selected...

This book constitutes the refereed proceedings of the 10th International Conference on Unconventional Computation, UC 2011, held in Turku, Finland, in June 2011. The 17 revised full papers presented together with 6 extended abstracts of invited talks,...

This book constitutes the refereed proceedings of the 5th International Conference on Language and Automata Theory and Applications, LATA 2011, held in Tarragona, Spain in May 2011. The 36 revised full papers presented together with four invited articles...

This book constitutes the thoroughly refereed post-conference proceedings of the 16th International Conference on DNA Computing and Molecular Programming, DNA16, held in Hong Kong, China, in June 2010. The 16 revised full papers presented were carefully...

This book and its sister volume collect refereed papers presented at the 7th Inter- tional Symposium on Neural Networks (ISNN 2010), held in Shanghai, China, June 6-9, 2010. Building on the success of the previous six successive ISNN symposiums, ISNN has...