Results 221 to 230 of about 9,750,100 (244)
Some of the next articles are maybe not open access.
Machine learning and learning from machines
The Leading Edge, 2018Machine learning has been around for decades or, depending on your view, centuries. To consider the tools and underpinnings of machine learning, one would need to go back to the work of Bayes and Laplace, the derivation of least squares, and Markov chains, all of which form the basis and the probability construct used pervasively in machine learning ...
Ehsan Zabihi Naeini, Kenton Prindle
openaire +2 more sources
Machine Learning and Learning from Machines
Progress’19, 2019Summary Deep learning has demonstrated tremendous success in a variety of application domains in the past few years, and with some new modalities of applications it continues to open new opportunities. We see applications of machine learning in our daily lives, stretching from familiar applications such as spam filters dating back to the 1990s to more ...
A. Kozhenkov +2 more
openaire +2 more sources
Do Machine-Learning Machines Learn?
2018We answer the present paper’s title in the negative. We begin by introducing and characterizing “real learning” (\(\mathcal {RL}\)) in the formal sciences, a phenomenon that has been firmly in place in homes and schools since at least Euclid. The defense of our negative answer pivots on an integration of reductio and proof by cases, and constitutes a ...
Selmer Bringsjord +3 more
openaire +1 more source
2015
What the reader should know after reading in this chapter Supervised learning, Unsupervised learning, Semi-supervised learning, Reinforcement learning.
CAMASTRA, Francesco +1 more
openaire +2 more sources
What the reader should know after reading in this chapter Supervised learning, Unsupervised learning, Semi-supervised learning, Reinforcement learning.
CAMASTRA, Francesco +1 more
openaire +2 more sources
ACM Transactions on Intelligent Systems and Technology, 2019
Today’s artificial intelligence still faces two major challenges. One is that, in most industries, data exists in the form of isolated islands. The other is the strengthening of data privacy and security.
Qiang Yang +3 more
semanticscholar +1 more source
Today’s artificial intelligence still faces two major challenges. One is that, in most industries, data exists in the form of isolated islands. The other is the strengthening of data privacy and security.
Qiang Yang +3 more
semanticscholar +1 more source
Machine Learning: The Ghost in the Learning Machine
2009Since ancient time learning has played a significant role in building the basis of human intelligence. The tendency for learning with the increased dynamics and complexity of the global economy is growing. If in the past most of the learning efforts were concentrated in high-school and college years, in the 21st century learning becomes a continuous ...
openaire +2 more sources
Foundations of Machine Learning
Introduction to AI Techniques for Renewable Energy Systems, 2021N. Nathani, Abhishek Singh
semanticscholar +1 more source
Machine learning (ML) entails a set of tools and structures to acquire information from data. This chapter explains a wide range of tools to learn from data originating from distinct sources. The chapter reviews established learning concepts and details some classical tools to perform unsupervised and supervised learning. Then, deep learning algorithms
Mendonça, Marcele O.K. +3 more
openaire +2 more sources
Mendonça, Marcele O.K. +3 more
openaire +2 more sources