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Large-scale Kernel Machines
Solutions for learning from large scale datasets, including kernel learning algorithms that scale linearly with the volume of the data and experiments carried out on realistically large datasets. Pervasive and networked computers have dramatically reduced the cost of collecting and distributing large datasets. In this context, machine learning algorithms that scale poorly could simply become irrelevant. We need learning algorithms that scale linearly with the volume of the data while maintaining enough statistical efficiency to outperform algorithms that simply process a random subset of the data. This volume offers researchers and engineers practical solutions for learning from large scale ...
Computational Science and Its Applications - ICCSA 2003
The three-volume set, LNCS 2667, LNCS 2668, and LNCS 2669, constitutes the refereed proceedings of the International Conference on Computational Science and Its Applications, ICCSA 2003, held in Montreal, Canada, in May 2003.The three volumes present more than 300 papers and span the whole range of computational science from foundational issues in computer science and mathematics to advanced applications in virtually all sciences making use of computational techniques. The proceedings give a unique account of recent results in computational science.
Bioinformatics
This title includes a number of Open Access chapters.The book introduces bioinformatic and statistical methodology and shows approaches to bias correction and error estimation. It also presents quantitative methods for genome and proteome analysis.
Regulatory Genomics
Research in the field of gene regulation is evolving rapidly in the ever-changing scientific environment. Advances in microarray techniques and comparative genomics have enabled more comprehensive studies of regulatory genomics. The study of genomic binding locations of transcription factors has enabled a more comprehensive modeling of regulatory networks. In addition, complete genomic sequences and comparison of numerous related species have demonstrated the conservation of non-coding DNA sequences, which often provide evidence for cis-regulatory binding sites. Systematic methods to decipher the regulatory mechanism are also crucial for corroborating these regulatory networks; key to these ...
Research in Computational Molecular Biology
This book constitutes the refereed proceedings of the 17th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2013, held in Beijing, China, in April 2013. The 32 revised full papers were carefully reviewed and selected from 167 submissions. The papers cover a wide range of topics including molecular sequence analysis; genes and regulatory elements; molecular evolution; gene expression; biological networks; sequencing and genotyping technologies; genomics; epigenomics; metagenomics; population, statistical genetics; systems biology; computational proteomics; computational structural biology; imaging; large-scale data management.
Metric Learning
Similarity between objects plays an important role in both human cognitive processes and artificial systems for recognition and categorization. How to appropriately measure such similarities for a given task is crucial to the performance of many machine learning, pattern recognition and data mining methods. This book is devoted to metric learning, a set of techniques to automatically learn similarity and distance functions from data that has attracted a lot of interest in machine learning and related fields in the past ten years. In this book, we provide a thorough review of the metric learning literature that covers algorithms, theory and applications for both numerical and structured data....
Fault Detection, Supervision and Safety of Technical Processes 2003 (SAFEPROCESS 2003)
A three-volume work bringing together papers presented at 'SAFEPROCESS 2003', including four plenary papers on statistical, physical-model-based and logical-model-based approaches to fault detection and diagnosis, as well as 178 regular papers.
SCADA Security
Examines the design and use of Intrusion Detection Systems (IDS) to secure Supervisory Control and Data Acquisition (SCADA) systems Cyber-attacks on SCADA systems—the control system architecture that uses computers, networked data communications, and graphical user interfaces for high-level process supervisory management—can lead to costly financial consequences or even result in loss of life. Minimizing potential risks and responding to malicious actions requires innovative approaches for monitoring SCADA systems and protecting them from targeted attacks. SCADA Security: Machine Learning Concepts for Intrusion Detection and Prevention is designed to help security and networking professi...
Research in Computational Molecular Biology
This book constitutes the refereed proceedings of the 11th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2007, held in Oakland, CA, USA in April 2007. The 37 revised full papers address all current issues in algorithmic, theoretical, and experimental bioinformatics.
Biocomputing 2002 - Proceedings Of The Pacific Symposium
The Pacific Symposium on Biocomputing brings together key researchers from the international biocomputing community. It is designed to be maximally responsive to the need for critical mass in subdisciplines within biocomputing. This book contains peer-reviewed articles in computational biology.
