An R package for regression analysis of data from extreme sampling
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Updated
May 3, 2022 - R
An R package for regression analysis of data from extreme sampling
Statistical inference in sparse high-dimensional additive models
PH-tree (Permutation Hierarchical Tree) implementation in Go.
The Artificial Bee Colony (ABC) algorithm that optimizes high dimensional continuous model parameters.
Implementation MWPCR with R
R package for Non-local Prior Based Iterative Variable Selection for Genome-Wide Association Studies, or Other High-Dimensional Data
This is a repository associated with the paper "Near-optimal sampling strategies for multivariate function on general domains" by Ben Adcock and Juan M. Cardenas available at https://epubs.siam.org/doi/10.1137/19M1279459 and https://arxiv.org/abs/1908.01249
Optimal Transport - Monge, Bregman and Occam Estimator (A Short Tutorial)
Lossless conversion algorithm for converting Cortical Learning Algorithm binary vectors to Modular Composite Representation vectors. Implements Integer Sparse Distributed Memory.
A Dual Surrogate-based Evolutionary Algorithm for High-Dimensional Expensive Multiobjective Optimization Problems
High-Dimensional Expensive Optimization by Classification-based Multiobjective Evolutionary Algorithm with Dimensionality Reduction
This is a repository associated with the chapter book "Towards optimal sampling for learning sparse approximations in high dimensions" by Ben Adcock, Juan M. Cardenas, Nick Dexter and Sebastian Moraga to be published by Springer in late 2021, available at https://arxiv.org/abs/2202.02360
Evolutionary multiobjective optimization assisted by scalarization function approximation for high-dimensional expensive problems
Characterization of intra-individual variability using physiologically relevant measurements provides important insights into fundamental biological questions ranging from cell type identity to tumor development. For each individual, the data measurements can be written as a matrix with the different subsamples of the individual recorded in the …
Codes for Chandra, et al. (2021+). Escaping the curse of dimensionality in Bayesian model based clustering. Please refer to the original paper for details https://arxiv.org/abs/2006.02700
Multiple Classifiers-Assisted Evolutionary Algorithm Based on Decomposition for High-Dimensional Multiobjective Problems
A Bayesian multiscale deep learning framework for flows in random media
R Package: Adaptively weighted group lasso for semiparametic quantile regression models
Replicate the results of nowcasting housing sales by Google Queries, using Bayesian Structural Time-Series Model (Choi & Varian, 2009, 2012).
Random Forest Two Sample Testing
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