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Advances in Neural Information Processing Systems 16
Papers presented at the 2003 Neural Information Processing Conference by leading physicists, neuroscientists, mathematicians, statisticians, and computer scientists. The annual Neural Information Processing (NIPS) conference is the flagship meeting on neural computation. It draws a diverse group of attendees -- physicists, neuroscientists, mathematicians, statisticians, and computer scientists. The presentations are interdisciplinary, with contributions in algorithms, learning theory, cognitive science, neuroscience, brain imaging, vision, speech and signal processing, reinforcement learning and control, emerging technologies, and applications. Only thirty percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. This volume contains all the papers presented at the 2003 conference.
Immortal evil
The teenager punched on the thick wooden stake around him, and this thick wooden stake with a diameter of about half a meter was broken on the spot!
Breaking into the world with a plug-in
The animals on the forum are growling, but now Zhang Biao can't care about these. In the dark room, he is staring at the download progress bar of another LCD screen with excitement. Small eyes flashed with obscene light.
Intelligence Science and Big Data Engineering. Big Data and Machine Learning Techniques
The two-volume set LNCS 9242 + 9243 constitutes the proceedings of the 5th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2015, held in Suzhou, China, in June 2015. The total of 126 papers presented in the proceedings was carefully reviewed and selected from 416 submissions. They deal with big data, neural networks, image processing, computer vision, pattern recognition and graphics, object detection, dimensionality reduction and manifold learning, unsupervised learning and clustering, anomaly detection, semi-supervised learning.
Elements of Dimensionality Reduction and Manifold Learning
Dimensionality reduction, also known as manifold learning, is an area of machine learning used for extracting informative features from data for better representation of data or separation between classes. This book presents a cohesive review of linear and nonlinear dimensionality reduction and manifold learning. Three main aspects of dimensionality reduction are covered: spectral dimensionality reduction, probabilistic dimensionality reduction, and neural network-based dimensionality reduction, which have geometric, probabilistic, and information-theoretic points of view to dimensionality reduction, respectively. The necessary background and preliminaries on linear algebra, optimization, an...
Computational and Information Science
The 2004 International Symposium on Computational and Information Sciences (CIS 2004) aimed at bringing researchers in the area of computational and - formation sciences together to exchange new ideas and to explore new ground. The goal of the conference was to push the application of modern computing technologies to science, engineering, and information technologies to a new level of sophistication and understanding. Theinitialideatoorganizesuchaconferencewithafocusoncomputationand applicationswasoriginatedbyDr.JunZhang,duringhisvisittoChinainAugust 2003, in consultation with a few friends, including Dr. Jing Liu at the Chinese Academy of Sciences, Dr. Jun-Hai Yong at Tsinghua University, D...
Knowledge Discovery in Databases: PKDD 2005
The European Conference on Machine Learning (ECML) and the European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD) were jointly organized this year for the ?fth time in a row, after some years of mutual independence before. After Freiburg (2001), Helsinki (2002), Cavtat (2003) and Pisa (2004), Porto received the 16th edition of ECML and the 9th PKDD in October 3–7. Having the two conferences together seems to be working well: 585 di?erent paper submissions were received for both events, which maintains the high s- mission standard of last year. Of these, 335 were submitted to ECML only, 220 to PKDD only and 30 to both. Such a high volume of scienti?c work ...
Big Data
This volume constitutes the proceedings of the 6th CCF Conference, Big Data 2018, held in Xi'an, China, in October 2018. The 32 revised full papers presented in this volume were carefully reviewed and selected from 880 submissions. The papers are organized in topical sections on natural language processing and text mining; big data analytics and smart computing; big data applications; the application of big data in machine learning; social networks and recommendation systems; parallel computing and storage of big data; data quality control and data governance; big data system and management.
Intelligence Science and Big Data Engineering. Image and Video Data Engineering
The two-volume set LNCS 9242 + 9243 constitutes the proceedings of the 5th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2015, held in Suzhou, China, in June 2015. The total of 126 papers presented in the proceedings was carefully reviewed and selected from 416 submissions. They deal with big data, neural networks, image processing, computer vision, pattern recognition and graphics, object detection, dimensionality reduction and manifold learning, unsupervised learning and clustering, anomaly detection, semi-supervised learning.
Advances in Image and Video Technology
This book constitutes the refereed proceedings of the First Pacific Rim Symposium on Image and Video Technology, PSIVT 2006, held in Hsinchu, Taiwan in December 2006. The 76 revised full papers and 58 revised poster papers cover a wide range of topics, including all aspects of video and multimedia, both technical and artistic perspectives and both theoretical and practical issues.
