In the last years, organizations and companies in general have found the true potential value of collecting and using data for supporting decision-making. As a consequence, data are being collected at an unprecedented rate. This poses several challenges, including, for example, regarding the storage and processing of these data. Machine Learning (ML) is also not an exception, in the sense that algorithms must now deal with novel challenges, such as learn from streaming data or deal with concept drift. ML engineers also have a harder task when it comes to selecting the most appropriate model, given the wealth of algorithms and possible configurations that exist nowadays. At the same time, training time is a stronger restriction as the comput...
International audienceThe Machine Learning (ML) world is in constant evolution, as the amount of dif...
Choosing the most suitable algorithm to perform a machine learning task for a new problem is a recur...
Meta-learning from learning curves is an important yet often neglected research area in the Machine ...
Day by day, machine learning is changing our lives in ways we could not have imagined just 5 years a...
First published: 29 November 2021Machine learning has been facing significant challenges over the la...
Dynamic real-world applications that generate data continuously have introduced new challenges for t...
Algorithm Selection and configuration are increasingly relevant today. Researchers and practitioners...
Meta-learning, or learning to learn, is the science of systematically observing how different machin...
While a valid intellectual challenge in its own right, meta-learning finds its real raison d’être in...
The many machine learning and data mining techniques produced over the last decades can prove invalu...
In order to make predictions with high accuracy, conventional deep learning systems require large tr...
The field of artificial intelligence has been throughout its history repeatedly inspired by human co...
There is no free lunch, no single learning algorithm that will outperform other algorithms on all da...
The exponential growth of volume, variety and velocity of data is raising the need for investigation...
With the evolution of algorithms and solutions in the artificial intelligence field, new and modern ...
International audienceThe Machine Learning (ML) world is in constant evolution, as the amount of dif...
Choosing the most suitable algorithm to perform a machine learning task for a new problem is a recur...
Meta-learning from learning curves is an important yet often neglected research area in the Machine ...
Day by day, machine learning is changing our lives in ways we could not have imagined just 5 years a...
First published: 29 November 2021Machine learning has been facing significant challenges over the la...
Dynamic real-world applications that generate data continuously have introduced new challenges for t...
Algorithm Selection and configuration are increasingly relevant today. Researchers and practitioners...
Meta-learning, or learning to learn, is the science of systematically observing how different machin...
While a valid intellectual challenge in its own right, meta-learning finds its real raison d’être in...
The many machine learning and data mining techniques produced over the last decades can prove invalu...
In order to make predictions with high accuracy, conventional deep learning systems require large tr...
The field of artificial intelligence has been throughout its history repeatedly inspired by human co...
There is no free lunch, no single learning algorithm that will outperform other algorithms on all da...
The exponential growth of volume, variety and velocity of data is raising the need for investigation...
With the evolution of algorithms and solutions in the artificial intelligence field, new and modern ...
International audienceThe Machine Learning (ML) world is in constant evolution, as the amount of dif...
Choosing the most suitable algorithm to perform a machine learning task for a new problem is a recur...
Meta-learning from learning curves is an important yet often neglected research area in the Machine ...