Results 11 to 20 of about 2,045,405 (349)
A Survey on Nonconvex Regularization Based Sparse and Low-Rank Recovery in Signal Processing, Statistics, and Machine Learning [PDF]
IEEE Access, 2018 In the past decade, sparse and low-rank recovery has drawn much attention in many areas such as signal/image processing, statistics, bioinformatics, and machine learning.
Fei Wen +3 more
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Algorithmic statistics, prediction and machine learning [PDF]
, 2015 Algorithmic statistics considers the following problem: given a binary string $x$ (e.g., some experimental data), find a "good" explanation of this data. It uses algorithmic information theory to define formally what is a good explanation. In this paper we extend this framework in two directions.
Milovanov, Alexey
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Evaluation metrics and statistical tests for machine learning
Scientific ReportsAbstractResearch on different machine learning (ML) has become incredibly popular during the past few decades. However, for some researchers not familiar with statistics, it might be difficult to understand how to evaluate the performance of ML models and compare them with each other.
Oona Rainio, Jarmo Teuho, Riku Klén
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Statistics for Machine Learning with Mathematica Applications
, 2023 In recent years, the field of statistics has experienced a surge in interest and application, largely due to significant advances in computer technology. This progress has led to remarkable developments in statistics methods and algorithms, enabling their widespread adoption across various disciplines.
M. M. Hammad
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Technology- enabled advance in the worlds of statistics, machine learning and data mining
New Zealand Science Review, 2023 Advances in digital computing continue to have large effects on all aspects of life and society, including science. These advances are possible because we have computer languages that translate directly into computational steps that can be implemented ...
J. Maindonald
semanticscholar +1 more source
Machine learning and statistics to qualify environments through multi-traits in Coffea arabica. [PDF]
, 2021 Several factors such as genotype, environment, and post-harvest processing can affect the responses of important traits in the coffee production chain.
BARBOSA, I. de P. +5 more
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Matrix Factorization Techniques in Machine Learning, Signal Processing, and Statistics
Mathematics, 2023 Compressed sensing is an alternative to Shannon/Nyquist sampling for acquiring sparse or compressible signals. Sparse coding represents a signal as a sparse linear combination of atoms, which are elementary signals derived from a predefined dictionary ...
Ke-Lin Du +3 more
semanticscholar +1 more source
Statistics meets Machine Learning [PDF]
, 2020 Theory and application go hand in hand in most areas of statistics. In a world flooded with huge amounts of data waiting to be analyzed, classified and transformed into useful outputs, the designing of fast, robust and stable algorithms has never been as
core +2 more sources
Aerospace, 2022 The rapid growth of global aviation operations has made its negative environmental impact an international concern. Accurate modeling of aircraft fuel burn, emissions, and noise is the prerequisite for informing new operational procedures, technologies ...
Zhenyu Gao, D. Mavris
semanticscholar +1 more source
NMR in Metabolomics: From Conventional Statistics to Machine Learning and Neural Network Approaches
Applied Sciences, 2022 NMR measurements combined with chemometrics allow achieving a great amount of information for the identification of potential biomarkers responsible for a precise metabolic pathway. These kinds of data are useful in different fields, ranging from food to
C. Corsaro +5 more
semanticscholar +1 more source