Multi-layer Perceptrons (MLPs) are the most fundamental type of neural network, so they play an important role in many machine learning systems and are the most theoretically studied type of neural network. A new paper from researchers at ETH Zurich pushes the limits of pure MLPs, and shows that scaling them up allows much better performance than expected from MLPs in the past. These findings may have important implications for the study of inductive biases, the theory of deep learning, and neural scaling laws.
Research Highlights: Deep Neural Networks and Tabular Data: A Survey
April 9, 2022 by Leave a Comment
In this regular column, we take a look at highlights for important research topics of the day for big data, data science, machine learning, AI and deep learning. It’s important to keep connected with the research arm of the field in order to see where we’re headed. In this edition, we feature a new paper showing that for tabular data, algorithms based on gradient-boosted tree ensembles still outperform the deep learning models. Enjoy!
Best of arXiv.org for AI, Machine Learning, and Deep Learning – November 2021
December 17, 2021 by Leave a Comment
In this recurring monthly feature, we will filter all the recent research papers appearing in the arXiv.org preprint server for subjects relating to AI, machine learning and deep learning – from disciplines including statistics, mathematics and computer science – and provide you with a useful “best of” list for the month.
Best of arXiv.org for AI, Machine Learning, and Deep Learning – September 2021
October 15, 2021 by Leave a Comment
In this recurring monthly feature, we will filter all the recent research papers appearing in the arXiv.org preprint server for subjects relating to AI, machine learning and deep learning – from disciplines including statistics, mathematics and computer science – and provide you with a useful “best of” list for the month.
Best of arXiv.org for AI, Machine Learning, and Deep Learning – August 2021
September 14, 2021 by Leave a Comment
In this recurring monthly feature, we will filter all the recent research papers appearing in the arXiv.org preprint server for subjects relating to AI, machine learning and deep learning – from disciplines including statistics, mathematics and computer science – and provide you with a useful “best of” list for the month.
Best of arXiv.org for AI, Machine Learning, and Deep Learning – July 2021
August 16, 2021 by Leave a Comment
In this recurring monthly feature, we will filter all the recent research papers appearing in the arXiv.org preprint server for subjects relating to AI, machine learning and deep learning – from disciplines including statistics, mathematics and computer science – and provide you with a useful “best of” list for the month.
Best of arXiv.org for AI, Machine Learning, and Deep Learning – June 2021
July 19, 2021 by Leave a Comment
In this recurring monthly feature, we will filter all the recent research papers appearing in the arXiv.org preprint server for subjects relating to AI, machine learning and deep learning – from disciplines including statistics, mathematics and computer science – and provide you with a useful “best of” list for the month.
Best of arXiv.org for AI, Machine Learning, and Deep Learning – May 2021
June 9, 2021 by Leave a Comment
In this recurring monthly feature, we will filter all the recent research papers appearing in the arXiv.org preprint server for subjects relating to AI, machine learning and deep learning – from disciplines including statistics, mathematics and computer science – and provide you with a useful “best of” list for the month.
Best of arXiv.org for AI, Machine Learning, and Deep Learning – April 2021
May 17, 2021 by Leave a Comment
In this recurring monthly feature, we will filter all the recent research papers appearing in the arXiv.org preprint server for subjects relating to AI, machine learning and deep learning – from disciplines including statistics, mathematics and computer science – and provide you with a useful “best of” list for the month.
Best of arXiv.org for AI, Machine Learning, and Deep Learning – February 2021
March 17, 2021 by Leave a Comment
In this recurring monthly feature, we will filter all the recent research papers appearing in the arXiv.org preprint server for subjects relating to AI, machine learning and deep learning – from disciplines including statistics, mathematics and computer science – and provide you with a useful “best of” list for the month.
