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Predicting movie ratings and recommender systems
A 195-page monograph by a top-1% Netflix Prize contestant. Learn about the famous machine learning competition. Improve your machine learning skills. Learn how to build recommender systems. What's inside:introduction to predictive modeling,a comprehensive summary of the Netflix Prize, the most known machine learning competition, with a $1M prize,detailed description of a top-50 Netflix Prize solution predicting movie ratings,summary of the most important methods published - RMSE's from different papers listed and grouped in one place,detailed analysis of matrix factorizations / regularized SVD,how to interpret the factorization results - new, most informative movie genres,how to adapt the algorithms developed for the Netflix Prize to calculate good quality personalized recommendations,dealing with the cold-start: simple content-based augmentation,description of two rating-based recommender systems,commentary on everything: novel and unique insights, know-how from over 9 years of practicing and analysing predictive modeling.
PRICAI 2006: Trends in Artificial Intelligence
This book constitutes the refereed proceedings of the 9th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2006, held in Guilin, China in August 2006. The book presents 81 revised full papers and 87 revised short papers together with 3 keynote talks. The papers are organized in topical sections on intelligent agents, automated reasoning, machine learning and data mining, natural language processing and speech recognition, computer vision, perception and animation, and more.
Introduction to Semi-Supervised Learning
Semi-supervised learning is a learning paradigm concerned with the study of how computers and natural systems such as humans learn in the presence of both labeled and unlabeled data. Traditionally, learning has been studied either in the unsupervised paradigm (e.g., clustering, outlier detection) where all the data are unlabeled, or in the supervised paradigm (e.g., classification, regression) where all the data are labeled. The goal of semi-supervised learning is to understand how combining labeled and unlabeled data may change the learning behavior, and design algorithms that take advantage of such a combination. Semi-supervised learning is of great interest in machine learning and data mi...
The Practice of Crowdsourcing
Many data-intensive applications that use machine learning or artificial intelligence techniques depend on humans providing the initial dataset, enabling algorithms to process the rest or for other humans to evaluate the performance of such algorithms. Not only can labeled data for training and evaluation be collected faster, cheaper, and easier than ever before, but we now see the emergence of hybrid human-machine software that combines computations performed by humans and machines in conjunction. There are, however, real-world practical issues with the adoption of human computation and crowdsourcing. Building systems and data processing pipelines that require crowd computing remains difficult. In this book, we present practical considerations for designing and implementing tasks that require the use of humans and machines in combination with the goal of producing high-quality labels.
The Cities of Song China I
This first volume of a two-volume set on Song Dynasty cities examines the innovative urban institutions and management practices that emerged during this period. The book compares the urban landscape and administrative system in the Song Dynasty with those of the Tang Dynasty. It challenges the conventional view that the transition from Tang to Song marked a shift from an enclosed ward system to a relatively open, compartmentalized system. Instead, it argues for a significant transformation of the ward system rather than its complete disappearance. The study examines the establishment of urban firefighting systems based on the concept of the "Corner", and analyzes the flourishing of urban markets under various forms of control and restriction. It also discusses the challenges posed by the emergence of a liberal commodity economy within traditional Chinese society. This volume will be essential reading for scholars and students of Chinese history and urban studies, as well as urban planners, historians, and policy-makers interested in understanding historical approaches to urban development and management.
Proceedings of the International Academic Summer Conference on Number Theory and Information Security (NTIS 2023)
This is an open access book. It is our great pleasure to have you at the Number Theory and Information Security (NTIS), which took place in Zhengzhou, China, from April 27 to 29, 2023. Number theory and information security, as important research directions in today's global technology field, are of great significance for national security and social development. To further strengthen research and cooperation in this field, this international academic conference aims to promote in-depth exchanges among international scholars, explore cutting-edge technologies and methods to solve information security problems, and promote the development and application of mathematics in the field of informa...
Journal of Machine Learning Research
An international forum covering all areas of machine learning.
Imagining Globalisation in China
Nick Knight's close reading of the debate on increased globalisation within China provides an essential analysis for anyone seeking to identify the dynamics of change in that country.
