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)A Blockwise Descent Algorithm for Group-penalized Multiresponse and Multinomial Regression
In this paper we purpose a blockwise descent algorithm for group-penalized multiresponse regression. Using a quasi-newton framework we extend this to group-penalized multinomial regression. We give a publicly available implementation for these in R, ...
A Fast Algorithm for the Minimum Covariance Determinant Estimator
The minimum covariance determinant (MCD) method of Rousseeuw is a highly robust estimator of multivariate location and scatter. Its objective is to find h observations (out of n) whose covariance matrix has the lowest determinant. Until now, applicat...
A Newton-CG Algorithm with Complexity Guarantees for Smooth Unconstrained Optimization
We consider minimization of a smooth nonconvex objective function using an iterative algorithm based on Newton's method and the linear conjugate gradient algorithm, with explicit detection and use of negative curvature directions for the Hessian of t...
An implementation of a randomized algorithm for principal component analysis.
This thesis addresses the language recognition problem with a special focus on phonotactic language recognition. A full description of different steps in a language recognition system is provided. We study state-of-the-art speech modeling techniques ...
Asymptotics for the minimum covariance determinant estimator
Consistency is shown for the minimum covariance determinant (MCD) estimators of multivariate location and scale and asymptotic normality is shown for the former. The proofs are made possible by showing a separating ellipsoid property for the MCD subs...
Gaussian processes for machine learning.
AbstractMachine learning clustering techniques are used to characterize and, after the training phase, to identify phases within an ignition process. For the ethanol mechanism used in this paper, four physically identifiable phases were found and cha...
Goodness of Fit and Related Inference Processes for Quantile Regression
Abstract We introduce a goodness-of-fit process for quantile regression analogous to the conventional R2 statistic of least squares regression. Several related inference processes designed to test composite hypotheses about the combined effect of sev...
Inter-Coder Agreement for Computational Linguistics
This article is a survey of methods for measuring agreement among corpus annotators. It exposes the mathematics and underlying assumptions of agreement coefficients, covering Krippendorff's alpha as well as Scott's pi and Cohen's kappa; discusses the...
Least Median of Squares Regression
Abstract Classical least squares regression consists of minimizing the sum of the squared residuals. Many authors have produced more robust versions of this estimator by replacing the square by something else, such as the absolute value. In this arti...
Modern Information Retrieval - the concepts and technology behind search, Second edition
Intelligent interaction between humans and computers has been a dream of artificial intelligence since the beginning of digital era and one of the original motivations behind the creation of artificial intelligence. A key step towards the achievement...
Pattern Recognition and Machine Learning
The Journal of Electronic Imaging (JEI), copublished bimonthly with the Society for Imaging Science and Technology, publishes peer-reviewed papers that cover research and applications in all areas of electronic imaging science and technology.
Shrinkage Algorithms for MMSE Covariance Estimation
We address covariance estimation in the sense of minimum mean-squared error (MMSE) for Gaussian samples. Specifically, we consider shrinkage methods which are suitable for high dimensional problems with a small number of samples (large p small n). Fi...
Small sample corrections for LTS and MCD
The least trimmed squares estimator and the minimum covariance determinant estimator Rousseeuw (1984) are frequently used robust estimators of regression and of location and scatter. Consistency factors can be computed for both methods to make the es...