Results 51 to 60 of about 9,750,100 (244)
Synthetic learning machines [PDF]
BioData Mining, 2014 Using a collection of different terminal nodesize constructed random forests, each generating a synthetic feature, a synthetic random forest is defined as a kind of hyperforest, calculated using the new input synthetic features, along with the original features.Using a large collection of regression and multiclass datasets we show that synthetic random
Hemant Ishwaran, James D. Malley
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IEEE Access, 2020 Colorectal cancer has become one of the most common cause of cancer mortality worldwide, with a five-year survival rate of over 50%. Additionally, the potential of some common polyp types to progress to colorectal cancer is considered high.
Ngoc-Quang Nguyen +2 more
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The scientific evaluation of music content analysis systems: Valid empirical foundations for future real-world impact [PDF]
, 2016 We discuss the problem of music content analysis within the formal framework of experimental ...
Grossmann, H +4 more
core
Deep Learning for Forecasting Stock Returns in the Cross-Section
, 2018 Many studies have been undertaken by using machine learning techniques, including neural networks, to predict stock returns. Recently, a method known as deep learning, which achieves high performance mainly in image recognition and speech recognition ...
A Subrahmanyam +12 more
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Fairness in Machine Learning [PDF]
, 2020 Machine learning based systems are reaching society at large and in many aspects of everyday life. This phenomenon has been accompanied by concerns about the ethical issues that may arise from the adoption of these technologies. ML fairness is a recently established area of machine learning that studies how to ensure that biases in the data and model ...
Oneto L., Chiappa S.
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Equivariant diffusion for structure-based de novo ligand generation with latent-conditioning
Journal of CheminformaticsWe introduce PoLiGenX, a novel generative model for de novo ligand design that employs latent-conditioned, target-aware equivariant diffusion. Our approach leverages the conditioning of the ligand generation process on reference molecules located within ...
Tuan Le +3 more
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What is the machine learning? [PDF]
Physical Review D, 2018 Applications of machine learning tools to problems of physical interest are often criticized for producing sensitivity at the expense of transparency. To address this concern, we explore a data planing procedure for identifying combinations of variables -- aided by physical intuition -- that can discriminate signal from background.
Chang, Spencer +2 more
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Machine Learning in Bioelectrocatalysis
Advanced Science, 2023 AbstractAt present, the global energy crisis and environmental pollution coexist, and the demand for sustainable clean energy has been highly concerned. Bioelectrocatalysis that combines the benefits of biocatalysis and electrocatalysis produces high‐value chemicals, clean biofuel, and biodegradable new materials.
Jiamin Huang +5 more
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Identifying gene-specific subgroups: an alternative to biclustering
BMC Bioinformatics, 2019 Background Transcriptome analysis aims at gaining insight into cellular processes through discovering gene expression patterns across various experimental conditions.
Vincent Branders +2 more
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Learning machine learning [PDF]
Communications of the ACM, 2018 A discussion of the rapidly evolving realm of machine learning.
Peter J. Denning, Ted G. Lewis
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