pith. sign in

arxiv: 1807.08169 · v1 · pith:5SC262JOnew · submitted 2018-07-21 · 💻 cs.LG · cs.AI· stat.ML

Recent Advances in Deep Learning: An Overview

classification 💻 cs.LG cs.AIstat.ML
keywords learningdeepadvancesmachinerecentresearchtechniquestrends
0
0 comments X
read the original abstract

Deep Learning is one of the newest trends in Machine Learning and Artificial Intelligence research. It is also one of the most popular scientific research trends now-a-days. Deep learning methods have brought revolutionary advances in computer vision and machine learning. Every now and then, new and new deep learning techniques are being born, outperforming state-of-the-art machine learning and even existing deep learning techniques. In recent years, the world has seen many major breakthroughs in this field. Since deep learning is evolving at a huge speed, its kind of hard to keep track of the regular advances especially for new researchers. In this paper, we are going to briefly discuss about recent advances in Deep Learning for past few years.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Hessian based analysis of SGD for Deep Nets: Dynamics and Generalization

    cs.LG 2019-07 unverdicted novelty 4.0

    Provides Hessian-based theoretical characterizations of SGD dynamics and a scale-invariant generalization bound for deep nets, backed by experiments on synthetic data, MNIST, and CIFAR-10.