Wikipedia
Deep Learning

a set of algorithms in machine learning that attempt to model high-level abstractions in data by using architectures composed of multiple non-linear transformations. Deep learning is part of a broader family of machine learning methods based on learning representations of data.

One of the promises of deep learning is replacing handcrafted features with efficient algorithms for unsupervised or semi-supervised feature learning and hierarchical feature extraction

With Deep Learning, Ng says, you just give the system a lot of data ‘so it can discover by itself what some of the concepts in the world are.’(cf.)

One of the promises of deep learning is replacing handcrafted features with efficient algorithms for unsupervised or semi-supervised feature learning and hierarchical feature extraction

With Deep Learning, Ng says, you just give the system a lot of data ‘so it can discover by itself what some of the concepts in the world are.’(cf.)

- AI black box
- Alphago
- Attention mechanism
- Coursera: Deep Learning
- Deep latent variable models
- Deep learning: implementing
- Deep Learning: Optimization methods
- Deep Learning Book
- Deep Learning frameworks
- Deep NLP
- DL: why does it work?
- Domain Knowledge + Deep Learning
- fast.ai
- Natural Language Semantic Search
- NIPS 2017
- Uncertainty in Deep Learning

47 Documents (Long List)

- A Radical New Neural Network Design Could Overcome Big Challenges in AI
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2018-12-22 - The major advancements in Deep Learning in 2018 | Tryolabs Blog
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2018-12-20 - Neural Information Processing Systems - Tutorial Sessions: Unsupervised Deep Learning "predict everything"
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This tutorial Unsupervised Deep Learning will cover in detail, the approach to simply 'predict everything' in the data, typically with a probabilistic model, which can be seen through the lens of the Minimum Description Length principle as an effort to compress the data as compactly as possible.

2018-12-06 - Learning Deep Architectures for AI By Yoshua Bengio (2009)
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2018-11-06 - From Deep Learning of Disentangled Representations to Higher-level Cognition - YouTube
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> What's wrong with our unsupervised training objectives ? They are in pixel space rather than in abstract space > Many more entropy bits in acoustics details than linguistic content Related to [this paper](/doc/?uri=https%3A%2F%2Farxiv.org%2Fabs%2F1709.08568)

2018-09-28 - Differentiable Programming
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2018-01-14 - MIT 6.S094: Deep Learning for Self-Driving Cars
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2018-01-09 - Deep Learning: A Critical Appraisal (arxiv)
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2018-01-03 - AI and Deep Learning in 2017 – A Year in Review – WildML
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2018-01-01 - Welcoming the Era of Deep Neuroevolution - Uber Engineering Blog
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> a suite of five papers that support the emerging realization that neuroevolution, where neural networks are optimized through evolutionary algorithms, is also an effective method to train deep neural networks for reinforcement learning (RL) problems.

2017-12-19 - Hello Edge: Keyword Spotting on Microcontrollers
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2017-12-15 - Deep Learning: Practice and Trends (NIPS 2017 Tutorial, parts I & II) - YouTube
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2017-12-12 - The Case for Learned Index Structures
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> we believe that the idea of replacing core components of a data management system through learned models has far reaching implications for future systems designs

2017-12-11 - Can A.I. Be Taught to Explain Itself? - The New York Times
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2017-11-23 - Theories of Deep Learning (STATS 385)
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2017-11-09 - Theories of Deep Learning by Hatef Monajemi | Research Project on ResearchGate
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2017-11-09 - What product breakthroughs will recent advances in deep learning enable? - Quora
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Eric Jang, Research Engineer at Google Brain

2017-10-03 - WildML – Artificial Intelligence, Deep Learning, and NLP
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2017-09-26 - Neural networks and deep learning
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free online book

2017-09-12 - What should I do to increase my skills in deep learning? - Quora
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2017-08-16 - Heroes of Deep Learning: Andrew Ng interviews Geoffrey Hinton - YouTube
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"A thought is just a big vector of neural activity" - not a symbolic expression

2017-08-16 - Google's neural networks invent their own encryption | New Scientist
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2016-11-06 - The Extraordinary Link Between Deep Neural Networks and the Nature of the Universe
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Nobody understands why deep neural networks are so good at solving complex problems. Now physicists say the secret is buried in the laws of physics.

2016-09-11 - Computational Linguistics and Deep Learning
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2016-09-10 - Stacked Approximated Regression Machine: A Simple Deep Learning Approach
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This paper seems too good to be true! They can train a VGG-like net VERY quickly to good accuracy, without backprop.

2016-09-03 - One Genius’ Lonely Crusade to Teach a Computer Common Sense | WIRED
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2016-03-27 - Introduction to Deep Neural Networks - Deeplearning4j: Open-source, distributed deep learning for the JVM
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2016-02-13 - Software links « Deep Learning
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2016-01-12 - 10 Free Deep Learning Tools - Butler Analytics
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2016-01-12 - Colorizing Black and White Photos with deep learning
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2016-01-09 - Deeplearning4j - Open-source, distributed deep learning for the JVM
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2016-01-03 - Attention and Memory in Deep Learning and NLP – WildML
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2016-01-03 - Facebook’s open-sourcing of AI hardware is the start of the deep-learning revolution | Ars Technica
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2015-12-22 - Talk: Memory-based Bayesian Reasoning and Deep Learning ← The Spectator
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2015-11-20 - Autograd for Torch
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new framework for simplifying deep learning research: autograd for Torch

2015-11-07 - Deep Learning, NLP, and Representations - colah's blog
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2015-10-16 - Deep Learning Machine Teaches Itself Chess in 72 Hours, Plays at International Master Level | MIT Technology Review
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Giraffe: Using Deep Reinforcement Learning to Play Chess

2015-09-15 - IBM's 'Rodent Brain' Chip Could Make Our Phones Hyper-Smart | WIRED
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2015-08-18 - Random Ponderings: A Brief Overview of Deep Learning
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2015-01-15 - ConvNetJS: Deep Learning in your browser
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ConvNetJS is a Javascript library for training Deep Learning models (mainly Neural Networks) entirely in your browser

2014-12-31 - Bay Area Vision Meeting: Unsupervised Feature Learning and Deep Learning - YouTube
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Lessons from neuroscience: one algorithm for all kinds of learning

Looking for better representations of the input (features)

Feature learning via sparse coding (sparse linear combinations. Edge detection, quantitatively similar to primary visual cortex)

Then learning features hierarchies (several layers. "sparse DBN" "deep belief nets")

Scaling see 25'07 (algos) ; using GPUs

Learning recursive representations. "Generic" hierarchies on text doesn't make sense; learn feature vector that represent sentences

2014-10-06 - Do Deep Nets Really Need to be Deep?
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2014-10-06 - AlchemyAPI rolls out deep-learning-based computer vision as a service — Tech News and Analysis
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2014-05-14 - DARPA is working on its own deep-learning project for natural-language processing — Tech News and Analysis
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2014-05-10 - An Introduction to Deep Learning (in Java): From Perceptrons to Deep Networks | Toptal
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2014-03-28 - Plumbing The Depths Of Deep Learning - Semanticweb.com
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2014-03-07 - Scientists See Advances in Deep Learning, a Part of Artificial Intelligence - NYTimes.com
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A voice recognition program translated a speech given by Richard F. Rashid, Microsoft’s top scientist, into Mandarin Chinese.

2012-11-30

Properties

- sl:creationDate : 2012-11-30
- sl:creationTime : 2012-11-30T22:49:11Z
- sl:describedBy : https://en.wikipedia.org/wiki/Deep_learning
- rdf:type : sl:Tag
- skos:prefLabel : Deep Learning