Gradient-Based Learning Applied to Document Recognition
of learning techniques has been a crucial factor in the recent success of pattern recognition applications such as continuous speech recognition and handwriting recognition. The main message of this paper is that better pattern recognition systems can be built by relying more on auto-matic learning and less on hand-designed heuristics. This
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SVM Example - Brigham Young University
axon.cs.byu.eduNow, computing the dot products results in 3 1 + 5 2 = 1 5 1 + 9 2 = +1 And the solution to this system of equations is 1 = 7 and 2 = 4. Finally, we can again look at the discriminating hyperplane in input space that corresponds to these . w~ = X i is~ i 7. Figure 8: The discriminating hyperplane corresponding to the values 1 = 7 and
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