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NlogN Entropy Optimization. 1. Sarit Shwartz Yoav Y. Schechner Michael Zibulevsky. Sponsors: ISF, Dvorah Foundation. 49. Kernel Estimators: Parzen Windows. Estimated PDF. Data. True PDF. Shwartz, Schechner & Zibulevsky, NlogN entropy optimization. Previous Work.
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NlogN Entropy Optimization 1 Sarit Shwartz Yoav Y. Schechner Michael Zibulevsky Sponsors: ISF, Dvorah Foundation
49 Kernel Estimators: Parzen Windows Estimated PDF Data True PDF Shwartz, Schechner & Zibulevsky, NlogN entropy optimization
Previous Work Parametric PDF:Hyvärinen 98, Bell; Sejnowski 95, Pham; Garrat 97. Cumulants:Cardoso ; Souloumiac 93. Not accurate
Order statistics:Vasicek 76, Learned-Miller; Fisher 03. KD trees:Gray; Moore 03. Previous Work Not differentiable
Entropy Estimation Kernel Estimators: reduced complexityPham, 03, .Erdogmus; Principe; Hild, 03, Morejon; Principe 04,Schraudolph 04, (Stochastic gradient).
50 Parzen Windows Estimator Shwartz, Schechner & Zibulevsky, NlogN entropy optimization
51 Minimization of Mutual Information Differentiable Computationally efficient - Currently O(K N) online code (see website) 2 2 Independent Component Analysis Shwartz, Schechner & Zibulevsky, NlogN entropy optimization
Parzen Windows as a Convolution 52 Wish it was … Discrete convolution Convolution Sampling Shwartz, Schechner & Zibulevsky, NlogN entropy optimization
53 Efficient Kernel Estimator Samples of estimated sources PDF estimation Fan; Marron 94, Silverman 82. A Shwartz, Schechner & Zibulevsky, NlogN entropy optimization
53 Samples of estimated sources Interpolation to uniform grid (histogram) PDF estimation Fan; Marron 94, Silverman 82. Efficient Kernel Estimator A B Shwartz, Schechner & Zibulevsky, NlogN entropy optimization
53 Samples of estimated sources Interpolation to uniform grid(histogram) Discrete convolution with Parzen window C PDF estimation Fan; Marron 94, Silverman 82. Efficient Kernel Estimator A B Shwartz, Schechner & Zibulevsky, NlogN entropy optimization
54 Efficient Entropy Estimator C D A • Interpolation to original values Shwartz, Schechner & Zibulevsky, NlogN entropy optimization
55 Can it be Used for Optimization? • Iterations exploiting derivatives of . W separate Shwartz, Schechner & Zibulevsky, NlogN entropy optimization
56 Can it be Used for Optimization? W separate • Binning fluctuations of . • Fluctuations amplified by differentiation. • Fluctuations slow convergence, false minima. Shwartz, Schechner & Zibulevsky, NlogN entropy optimization
57 Quantization and Optimization Function Quantized function Shwartz, Schechner & Zibulevsky, NlogN entropy optimization
57 Quantization and Optimization Function Quantized function Function with a quantized derivative Shwartz, Schechner & Zibulevsky, NlogN entropy optimization
Analytic Entropy Gradient Accurate derivative Efficient calculation Shwartz, Schechner & Zibulevsky, NlogN entropy optimization
Analytic Entropy Gradient Complexity K- number of sources, N-data length. Shwartz, Schechner & Zibulevsky, NlogN entropy optimization
58 Entropy Gradient by Convolutions Convolution Convolution Convolution Shwartz, Schechner & Zibulevsky, NlogN entropy optimization
59 Entropy Gradient by Convolutions • Calculation of using convolutions. • Approximation of convolutions with complexity. • Distinct quantization of the derivative. Not differentiation of a quantized function. Shwartz, Schechner & Zibulevsky, NlogN entropy optimization
60 Super ICA performance Non-parametric algorithms. Parametric algorithms. K=6 random sources, N= 3000 samples. Shwartz, Schechner & Zibulevsky, NlogN entropy optimization