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About: A general purpose library to process and predict sequences of elements using echo state networks. Changes:Initial Announcement on mloss.org.
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About: Metropolis-Hastings alogrithm is a Markov chain Monte Carlo method for obtaining a sequence of random samples from a probability distribution for which direct sampling is difficult. Thi sequence can be used to approximate the distribution. Changes:Initial Announcement on mloss.org.
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About: ReFr is a software architecture for specifying, training and using reranking models. Changes:Initial Announcement on mloss.org.
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About: An implementation of MROGH descriptor. For more information, please refer to: “Bin Fan, Fuchao Wu and Zhanyi Hu, Aggregating Gradient Distributions into Intensity Orders: A Novel Local Image Descriptor, CVPR 2011, pp.2377-2384.” The most up-to-date information can be found at : http://vision.ia.ac.cn/Students/bfan/index.htm Changes:Initial Announcement on mloss.org.
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About: Bayesian state-space modelling and inference on high-performance computer hardware. Changes:Initial Announcement on mloss.org.
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About: Data-efficient policy search framework using probabilistic Gaussian process models Changes:Initial Announcement on mloss.org.
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About: This letter proposes a new multiple linear regression model using regularized correntropy for robust pattern recognition. First, we motivate the use of correntropy to improve the robustness of the classicalmean square error (MSE) criterion that is sensitive to outliers. Then an l1 regularization scheme is imposed on the correntropy to learn robust and sparse representations. Based on the half-quadratic optimization technique, we propose a novel algorithm to solve the nonlinear optimization problem. Second, we develop a new correntropy-based classifier based on the learned regularization scheme for robust object recognition. Extensive experiments over several applications confirm that the correntropy-based l1 regularization can improve recognition accuracy and receiver operator characteristic curves under noise corruption and occlusion. Changes:Initial Announcement on mloss.org.
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About: Jubatus is a general framework library for online and distributed machine learning. It currently supports classification, regression, clustering, recommendation, nearest neighbors, anomaly detection, and graph analysis. Loose model sharing provides higher scalability, better performance, and real-time capabilities, by combining online learning with distributed computations. Changes:0.5.0 add new supports for clustering and nearest neighbors. For more detail, see http://t.co/flMcTcYZVs
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About: LDPar is an efficient data-driven dependency parser. You can train your own parsing model on treebank data and parse new data using the induced model. Changes:Initial Announcement on mloss.org.
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About: Text-to-Speech (TTS) is a kind of speech processing technology that converts text into speech. It involves phonetics, linguistics, digital signal processing technology, computer technology, multimedia technology, and other technologies. It is a frontier technology in Chinese information processing field. With TTS technology, any text used to be read by eyes can also be listened by ears. Changes:Initial Announcement on mloss.org.
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