Algorithm Research Papers

Machine learning: Trends, perspectives, and prospects

Machine learning addresses the question of how to build computers that improve automatically through experience. It is one of today's most rapidly growing technical fields, lying at the intersection of computer science and statistics, and a...

Machine learning: a primer

Automatic Differentiation in Machine Learning: a Survey

Derivatives, mostly in the form of gradients and Hessians, are ubiquitous in machine learning. Automatic differentiation (AD) is a technique for calculating derivatives of numeric functions expressed as computer programs efficiently and acc...

Quantum machine learning

Machine learning and data mining

Machine learning algorithms enable discovery of important "regularities" in large data sets....

Overfitting and undercomputing in machine learning

suggests a reasonable line of research: find algorithms that can search the hypothesis class better. Hence, there is been extensive research in applying second-order methods to fit neural networks and in conducting much more thorough search...

Machine Learning

An Introduction to Machine Learning

lab2clean: a novel algorithm for automated cleaning of retrospective clinical laboratory results data for secondary uses

Abstract Background The integrity of clinical research and machine learning models in healthcare heavily relies on the quality of underlying clinical laboratory data. However, the preprocessing of this data to ensure its reliability and acc...

Machine Learning : A Probabilistic Perspective

Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict fu...

Elements of Machine Learning

Elements of Machine Learning by Pat Langley Preface 1. An overview of machine learning 1.1 The science of machine learning 1.2 Nature of the environment 1.3 Nature of representation and performance 1.4 Nature of the learning component 1.5 F...

Pattern Recognition and Machine Learning

(2007). Pattern Recognition and Machine Learning. Technometrics: Vol. 49, No. 3, pp. 366-366....

Readings in Machine Learning

From the Publisher: The ability to learn is a fundamental characteristic of intelligent behavior. Consequently, machine learning has been a focus of artificial intelligence since the beginnings of AI in the 1950s. The 1980s saw tremendous ...

Causality for Machine Learning

Graphical causal inference as pioneered by Judea Pearl arose from research on artificial intelligence (AI), and for a long time had little connection to the field of machine learning. This article discusses where links have been and should ...

Machine Learning in Action

SummaryMachine Learning in Action is unique book that blends the foundational theories of machine learning with the practical realities of building tools for everyday data analysis. You'll use the flexible Python programming language to bui...

Research on recognizing required items based on opencv and machine learning

Starting from the background of the outbreak of New Coronavirus, in order to realize the function of automatically identifying the required items by machine, the support vector machine algorithm in the neural network and the traditional com...

An Introduction to Machine Learning

Introduction to Machine Learning

Foundations of Machine Learning

Machine Learning

A Proven, Hands-On Approach for Students without a Strong Statistical FoundationSince the best-selling first edition was published, there have been several prominent developments in the field of machine learning, including the increasing wo...