
Robust contrastive learning and nonlinear ICA in the presence of outliers
Nonlinear independent component analysis (ICA) is a general framework fo...
read it

ModeSeeking Clustering and Density Ridge Estimation via Direct Estimation of DensityDerivativeRatios
Modes and ridges of the probability density function behind observed dat...
read it

WhiteningFree LeastSquares NonGaussian Component Analysis
NonGaussian component analysis (NGCA) is an unsupervised linear dimensi...
read it

NonGaussian Component Analysis with LogDensity Gradient Estimation
NonGaussian component analysis (NGCA) is aimed at identifying a linear ...
read it

Direct Estimation of the Derivative of Quadratic Mutual Information with Application in Supervised Dimension Reduction
A typical goal of supervised dimension reduction is to find a lowdimens...
read it

Regularized MultiTask Learning for MultiDimensional LogDensity Gradient Estimation
Logdensity gradient estimation is a fundamental statistical problem and...
read it

Simultaneous Estimation of NonGaussian Components and their Correlation Structure
The statistical dependencies which independent component analysis (ICA) ...
read it

Direct DensityDerivative Estimation and Its Application in KLDivergence Approximation
Estimation of density derivatives is a versatile tool in statistical dat...
read it

Clustering via Mode Seeking by Direct Estimation of the Gradient of a LogDensity
Mean shift clustering finds the modes of the data probability density by...
read it

Nonlinear ICA Using Auxiliary Variables and Generalized Contrastive Learning
Nonlinear ICA is a fundamental problem for unsupervised representation l...
read it

NeuralKernelized Conditional Density Estimation
Conditional density estimation is a general framework for solving variou...
read it

Robust modal regression with direct logdensity derivative estimation
Modal regression is aimed at estimating the global mode (i.e., global ma...
read it
Hiroaki Sasaki
is this you? claim profile