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Carver Mead. John Hopfield. Website. ai .google /research /people /JohnPlatt. John Carlton Platt (born 1963) is an American computer scientist. He is currently a distinguished scientist at Google. [1] Formerly he was a deputy managing director at Microsoft Research Redmond Labs. [2] Platt worked for Microsoft from 1997 to 2015.
John Rader Platt (June 29, 1918 – June 17, 1992) was an American physicist and biophysicist, professor at the University of Chicago, noted for his pioneering work on strong inference in the 1960s and his analysis of social science in the 1970s.
John Platt is best known for his work in machine learning: the SMO algorithm for support vector machines and calibrating the output of models. He was an early adopter of convolutional neural networks in the 1990s. However, John has worked in many different fields: data systems, computational geometry, object recognition, media UIs, analog ...
Fast training of support vector machines using sequential minimal optimization. JC Platt. Advances in kernel methods, 185-208. , 1999. 9239. 1999. Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods. J Platt. Advances in large margin classifiers 10 (3), 61-74.
- Optimization Problem
- Algorithm
- Related Work
Consider a binary classification problem with a dataset (x1, y1), ..., (xn, yn), where xi is an input vector and yi ∈ {-1, +1} is a binary label corresponding to it. A soft-margin support vector machine is trained by solving a quadratic programming problem, which is expressed in the dual formas follows: 1. max α ∑ i = 1 n α i − 1 2 ∑ i = 1 n ∑ j = ...
SMO is an iterative algorithm for solving the optimization problem described above. SMO breaks this problem into a series of smallest possible sub-problems, which are then solved analytically. Because of the linear equality constraint involving the Lagrange multipliers α i {\\displaystyle \\alpha _{i}} , the smallest possible problem involves two suc...
The first approach to splitting large SVM learning problems into a series of smaller optimization tasks was proposed by Bernhard Boser, Isabelle Guyon, Vladimir Vapnik.It is known as the "chunking algorithm". The algorithm starts with a random subset of the data, solves this problem, and iteratively adds examples which violate the optimality condit...
John Platt Emmy Award Winning Executive Producer, Writer, Director, Creator - TV, FILM & STREAMING Los Angeles, CA. John Platt Greater Boston. John Platt Portland, Oregon Metropolitan Area ...
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Oct 24, 2019 · John C. Platt As web search providers seek to improve both relevance and response times, they are challenged by the ever-increasing tax of automated search query traf-fic.
