Results 11 to 20 of about 1,259,133 (314)
A Review of Causality for Learning Algorithms in Medical Image Analysis [PDF]
, 2022 Medical image analysis is a vibrant research area that offers doctors and medical practitioners invaluable insight and the ability to accurately diagnose and monitor disease. Machine learning provides an additional boost for this area.
Vlontzos, Athanasios +2 more
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Greedy structure learning from data that contain systematic missing values [PDF]
, 2022 Learning from data that contain missing values represents a common phenomenon in many domains. Relatively few Bayesian Network structure learning algorithms account for missing data, and those that do tend to rely on standard approaches that assume ...
Liu, Y +5 more
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Mathematics, 2023 Considering the worst-case scenario, the junction-tree algorithm remains the most general solution for exact MAP inference with polynomial run-time guarantees.
Alexander Bauer +2 more
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Machine Learned Learning Machines
CoRR, 2017 There are two common approaches for optimizing the performance of a machine: genetic algorithms and machine learning. A genetic algorithm is applied over many generations whereas machine learning works by applying feedback until the system meets a performance threshold. Though these are methods that typically operate separately, we combine evolutionary
Leigh Sheneman, Arend Hintze
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Quantum machine learning [PDF]
Nature, 2017 Fuelled by increasing computer power and algorithmic advances, machine learning techniques have become powerful tools for finding patterns in data. Since quantum systems produce counter-intuitive patterns believed not to be efficiently produced by classical systems, it is reasonable to postulate that quantum computers may outperform classical computers
Jacob D. Biamonte +5 more
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Polytopes and machine learning
International Journal of Data Science in the Mathematical Sciences, 2023 We introduce machine learning methodology to the study of lattice polytopes. With supervised learning techniques, we predict standard properties such as volume, dual volume, and reflexivity with accuracies up to 100%. We focus on 2d polygons and 3d polytopes with Plücker coordinates as input, which outperform the usual vertex representation.
Jiakang Bao +5 more
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Exploring and Exploiting Conditioning of Reinforcement Learning Agents
IEEE Access, 2020 The outcome of Jacobian singular values regularization was studied for supervised learning problems. In supervised learning settings for linear and nonlinear networks, Jacobian regularization allows for faster learning.
Arip Asadulaev +3 more
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Ideal Learning Machines* [PDF]
Cognitive Science, 1982 We examine the prospects for finding “best possible” or “ideal” computing machines for various learning tasks. For this purpose, several precise senses of “ideal machine” are considered within the context of formal learning theory. Generally negative results are provided concerning the existence of ideal learning‐machines in the senses considered.
Daniel N. Osherson +2 more
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Quantum machine learning [PDF]
, 2020 Click on the DOI link to access the article (may not be free).Quantum-enhanced machine learning refers to quantum algorithms that solve tasks in machine learning, thereby improving a classical machine learning method.
De, Sourav +5 more
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Artificial intelligence and the future of radiographic scoring in rheumatoid arthritis: a viewpoint
Arthritis Research & Therapy, 2022 Rheumatoid arthritis is an autoimmune condition that predominantly affects the synovial joints, causing joint destruction, pain, and disability. Historically, the standard for measuring the long-term efficacy of disease-modifying antirheumatic drugs has ...
Alix Bird +8 more
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