Density Estimation

In probability and statistics,density estimation is the construction of an estimate, based on observed data, of an unobservable underlying probability density function. The unobservable density function is thought of as the density according to which a large population is distributed; the data are usually thought of as a random sample from that population.A variety of approaches to density estimation are used, including Parzen windows and a range of data clustering techniques, including vector quantization. The most basic form of density estimation is a rescaled histogram.
Posts about Density Estimation
  • Vladimir Vapnik Joins Facebook AI Research

    … the capacity of a learning machine. Vladimir is rejoining some of his long-time collaborators: Jason Weston, Ronan Collobert and Yann LeCun. He is working on a new book and will be collaborating with FAIR (Fundamentals of Artificial Intelligence Research) research scientists to develop some of his new ideas on conditional density estimation, learning with privileged information and other topics. According to VentureBeat, Vapnik, Weston, Collobert and LeCun worked together at AT&T. …

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