Machine Learning
Machine learning frameworks, algorithms, and training systems
Repositories
(7)huggingface/transformers
microsoft/onnxruntime
mlflow/mlflow
pytorch/pytorch
ray-project/ray
scikit-learn/scikit-learn
tensorflow/tensorflow
Papers
(373)Fast and scalable polynomial kernels via explicit feature maps
Approximation of non-linear kernels using random feature mapping has been successfully employed in large-scale data analysis applications, accelerating the training of kernel machines. While previous random feature mappings run in O(ndD) time for $n$...
Generalized Boosted Models: A guide to the gbm package
This article provides an introduction to ensemble statistical procedures as a special case of algorithmic methods. The discussion begins with classification and regression trees (CART) as a didactic device to introduce many of the key issues. Followi...
Greedy function approximation: A gradient boosting machine.
Function estimation/approximation is viewed from the perspective\nof numerical optimization in function space, rather than parameter space. A\nconnection is made between stagewise additive expansions and steepest-descent\nminimization. A general grad...
In Defense of One-Vs-All Classification
Nested dichotomies are a standard statistical technique for tackling certain polytomous classification problems with logistic regression. They can be represented as binary trees that recursively split a multi-class classification task into a system o...
Least angle regression
The purpose of model selection algorithms such as All Subsets, Forward Selection and Backward Elimination is to choose a linear model on the basis of the same set of data to which the model will be applied. Typically we have available a large collect...
Machine Learning Applications to Land and Structure Valuation
In some applications of supervised machine learning, it is desirable to trade model complexity with greater interpretability for some covariates while letting other covariates remain a “black box”. An important example is hedonic property valuation m...
MICE: Multivariate Imputation by Chained Equations in R
The R package mice imputes incomplete multivariate data by chained equations. The software mice 1.0 appeared in the year 2000 as an S-PLUS library, and in 2001 as an R package. mice 1.0 introduced predictor selection, passive imputation and automatic...
Missing value estimation methods for DNA microarrays.
Abstract Motivation: Gene expression microarray experiments can generate data sets with multiple missing expression values. Unfortunately, many algorithms for gene expression analysis require a complete matrix of gene array values as input. For examp...
On Grouping for Maximum Homogeneity
Abstract Given a set of arbitrary numbers, what is a practical procedure for grouping them so that the variance within groups is minimized? An answer to this question, including a description of an automatic computer program, is given for problems up...
On the “degrees of freedom” of the lasso
We study the effective degrees of freedom of the lasso in the framework of Stein’s unbiased risk estimation (SURE). We show that the number of nonzero coefficients is an unbiased estimate for the degrees of freedom of the lasso—a conclusion that requ...
Properties of the Hubert-Arabie adjusted Rand index.
This article provides an investigation of cluster validation indices that relates 4 of the indices to the L. Hubert and P. Arabie (1985) adjusted Rand index--the cluster validation measure of choice (G. W. Milligan & M. C. Cooper, 1986). It is shown ...
Self-Organizing Feature Maps Identify Proteins Critical to Learning in a Mouse Model of Down Syndrome
Down syndrome (DS) is a chromosomal abnormality (trisomy of human chromosome 21) associated with intellectual disability and affecting approximately one in 1000 live births worldwide. The overexpression of genes encoded by the extra copy of a normal ...
Unsupervised Word Sense Disambiguation Rivaling Supervised Methods
This paper presents an unsupervised learning algorithm for sense disambiguation that, when trained on unannotated English text, rivals the performance of supervised techniques that require time-consuming hand annotations. The algorithm is based on tw...