special machine learning


Reinforcement learning is the learning of a mapping from situations to actions so as to maximize a scalar reward or reinforcement signal. The learner is not told which action to take, as in most forms of machine learning , but instead must discover which actions yield the It can be argued that every interactive software system utilizes a user model, albeit, in many cases, an implicit model of the users objectives, and capabilities. Rather than such implicit models, research on user modeling has concentrated on explicit models that provide some

Hybrid and ensemble methods in machine learning J. UCS special issue
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Hybrid and ensemble methods in machine learning have attracted a great attention of the scientific community over the last years [Zhou, 12]. Multiple, ensemble learning models have been theoretically and empirically shown to provide significantly better performance than

Special issue of machine learning on information retrieval introduction
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As the field of machine learning (ML) has matured, it has reached out to several related fields, both for challenging applications and problems (eg, robotics), and for new techniques and methods (eg, statistics and databases). One especially interesting source of both The research presented here aims at developing special -purpose VLSI modules to be used as components of fully autonomous massively-parallel systems for real-time adaptive applications based on Machine Learning techniques. In particular, one can realize Neural

Guest Editors Introduction to the Special Issue: Machine Learning for Bioinformatics-Part 1
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IN recent years, rapid developments in genomics and proteomics have generated a large amount of data. Often, drawing conclusions from these data requires sophisticated computational analyses. Bioinformatics, or computational biology, is the interdisciplinary

Improving special purpose machine user-interfaces by machine – learning algorithms
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This paper proposes to make complex production machines more user-friendly. Improved machines help the operator in case of an error message or a process event by displaying recommendations, such as in the last 10 occurences of this event the operators performed

Scoring of Machine – Learning Algorithms for Providing User Guidance in Special Purpose Machines
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We propose a system to make complex production machines more user-friendly by giving the operator recommendations, such as in the last 10 occurrences of this event the operators performed the following keystrokes . We describe algorithms to generate the

Benchmarking of classical and machine – learning algorithms (with special emphasis on bagging and boosting approaches) for time series forecasting
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The goal of this Master thesis is to evaluate the time series forecast capability of several Machine Learning approaches, in detail Neural Nets, Random Forests, Kernel Machines (Support Vector Machines and Gaussian Processes), tree-based and component-wise linear

Special issue on machine learning methods in signal processing
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MUCH of modern statistical and adaptive signal pro-cessing relies on learning algorithms of one form or another. While some of the rich literature on machine learning has penetrated the signal processing community in great depth, a variety of new techniques, which offer Hybrid and ensemble methods in machine learning have gained great attention of the scientific community over the last few years. Multiple learning models have been theoretically and empirically shown to provide significantly better performance than their

Guest Editors Introduction to the Special Issue: Machine Learning for Bioinformatics-Part 2
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THIS issue of the IEEE/ACM Transactions on Computational Biology and Bioinformatics comprises the second half of our special issue on Machine Learning for Bioinformatics. In total, more than 50 papers were submitted to the special issue, of which 13 were accepted

introduction to the special issue: machine learning approaches to multimedia information retrieval
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With todays ubiquitous presence of multimedia informa- tion in almost all IT-based applications, it is imperative to address the indexing and retrieval issues for managing the explosive growth of the multimedia data for such applications. Research in the area of Multimedia

Special issue on fuzzy methods in machine learning and data mining
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Machine learning , data mining, and related research fields have received a great deal of attention in recent years and, beyond doubt, have established themselves as core elements of intelligent and knowledge-based systems design. In these fields, a multitude of efficient

SPECIAL INTEREST GROUP IN MACHINE LEARNING [MLRD PRESENTATIONS]
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Page 1. SPECIAL INTEREST GROUP IN MACHINE LEARNING 22 August 15, RM 101 Prof Vinay Namboodiri ​, ​Current Trend in Computer Vision Prof Harish Karnick ​, ​ Machine Learning 2.0 Avi Singh ​, ​ Learning Temporal Models for Anticipating

Machine Learning Approach to Classification of Childhood Disabilities for Special Education
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This paper presents an investigation of a machine learning approach to classification of childhood disabilities for special education, an inherently complicated multi-class problem. We applied the supervised learning to train various classification algorithms utilizing an The aim of the COLT special issues is to provide a forum for COLT conference papers which though theoretical have been judged to have significant practical ramifications and hence to be of potential interest to a broader spectrum of Machine Learning readers. The papers This special issue, with invited papers solicited from authors who contributed to the 2001 IEEE Workshop on Neural Networks for Signal Processing, gathers papers from three areas where machine learning methods have found fruitful applications. These are:(1) data

Introduction to the Special Issue on Machine Learning for Microarray Bioinformatics
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One of the main challenges in computational biology is the revelation and interpretation of the rich genomic information underlying cancer biology and to facilitating molecular classification and prediction of cancers and responses to therapies. Genomic sequencing

Introduction to the Special Issue on Deep Learning Approaches for Machine Translation
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Deep learning is revolutionizing speech and natural language technologies since it is offering an effective way to train systems and obtaining significant improvements. The main advantage of deep learning is that, by developing the right architecture, the system



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