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Found 6 papers, 1 papers with code
Row-clustering of a Point Process-valued Matrix
Structured point process data harvested from various platforms poses new challenges to the machine learning community.
Distributed Adaptive Nearest Neighbor Classifier: Algorithm and Theory
When data is of an extraordinarily large size or physically stored in different locations, the distributed nearest neighbor (NN) classifier is an attractive tool for classification.
Second order semi-parametric inference for multivariate log Gaussian Cox processes
We assume a semi-parametric model for the multivariate intensity function containing an unspecified complex factor common to all types of points.
Model Selection
Methodology
Nonparametric Inference under B-bits Quantization
Statistical inference based on lossy or incomplete samples is often needed in research areas such as signal/image processing, medical image storage, remote sensing, signal transmission.
Optimal Tuning for Divide-and-conquer Kernel Ridge Regression with Massive Data
Divide-and-conquer is a powerful approach for large and massive data analysis.
Distributed Generalized Cross-Validation for Divide-and-Conquer Kernel Ridge Regression and its Asymptotic Optimality
Tuning parameter selection is of critical importance for kernel ridge regression.
