Best paper award at #CVPR2018 :
"Taskonomy: Disentangling Task Transfer Learning"
Abstract : Do visual tasks have a relationship, or are they unrelated? For instance, could having surface normals simplify estimating the depth of an image? Intuition answers these questions positively, implying existence of a structure among visual tasks. Knowing this structure has notable values; it is the concept underlying transfer learning and provides a principled way for identifying redundancies across tasks, e.g., to seamlessly reuse supervision among related tasks or solve many tasks in one system without piling up the complexity. We proposes a fully computational approach for modeling the structure of space of visual tasks (...).
Paper: https://arxiv.org/pdf/1804.08328.pdf
Data: https://taskonomy.stanford.edu
#award #artificialintelligence #deeplearning #transferlearning
"Taskonomy: Disentangling Task Transfer Learning"
Abstract : Do visual tasks have a relationship, or are they unrelated? For instance, could having surface normals simplify estimating the depth of an image? Intuition answers these questions positively, implying existence of a structure among visual tasks. Knowing this structure has notable values; it is the concept underlying transfer learning and provides a principled way for identifying redundancies across tasks, e.g., to seamlessly reuse supervision among related tasks or solve many tasks in one system without piling up the complexity. We proposes a fully computational approach for modeling the structure of space of visual tasks (...).
Paper: https://arxiv.org/pdf/1804.08328.pdf
Data: https://taskonomy.stanford.edu
#award #artificialintelligence #deeplearning #transferlearning
ICYMI: Best Paper Award talk #ICRA2019!
Making Sense of Vision and Touch: Self-Supervised Learning of Multimodal Representations for Contact-Rich Tasks
paper: https://www.profillic.com/paper/arxiv:1810.10191
They present their results in simulation and on a real robot!
For more like this: https://www.profillic.com
Making Sense of Vision and Touch: Self-Supervised Learning of Multimodal Representations for Contact-Rich Tasks
paper: https://www.profillic.com/paper/arxiv:1810.10191
They present their results in simulation and on a real robot!
For more like this: https://www.profillic.com
Profillic
Profillic: AI research & source code to supercharge your projects
Explore state-of-the-art in machine learning, AI, and robotics research. Browse papers, source code, models, and more by topics and authors. Connect with researchers and engineers working on related problems in machine learning, deep learning, natural language…
Top 8 Free Must-Read Books on Deep Learning
https://www.kdnuggets.com/2018/04/top-free-books-deep-learning.html
https://www.kdnuggets.com/2018/04/top-free-books-deep-learning.html
KDnuggets
Top 8 Free Must-Read Books on Deep Learning - KDnuggets
Deep Learning is the newest trend coming out of Machine Learning, but what exactly is it? And how do I learn more? With that in mind, here's a list of 8 free books on deep learning.
In case that you didn't read that awesome research about wellness. So if you asked yourself why, that's real answer
https://arxiv.org/abs/1802.07068
https://arxiv.org/abs/1802.07068
arXiv.org
Talent vs Luck: the role of randomness in success and failure
The largely dominant meritocratic paradigm of highly competitive Western cultures is rooted on the belief that success is due mainly, if not exclusively, to personal qualities such as talent,...
ML Resources
By Sam Finlayson: https://sgfin.github.io/learning-resources/
#ArtificialIntelligence #DeepLearning #MachineLearning
By Sam Finlayson: https://sgfin.github.io/learning-resources/
#ArtificialIntelligence #DeepLearning #MachineLearning
Overlooked No More: Alan Turing never had an obituary in the New York Times.
Until now.
By Alan Cowell: https://www.nytimes.com/2019/06/05/obituaries/alan-turing-overlooked.html
#AlanTuring #ArtificialIntelligence #Mathematics
Until now.
By Alan Cowell: https://www.nytimes.com/2019/06/05/obituaries/alan-turing-overlooked.html
#AlanTuring #ArtificialIntelligence #Mathematics
Deep learning can already predict where you’re going to walk next. Now it can predict your future actions too: https://bit.ly/2Ky1jFw
Unsupervised Object Segmentation by Redrawing
Chen et al.: https://arxiv.org/abs/1905.13539
#ArtificialIntelligence #DeepLearning #MachineLearning
Chen et al.: https://arxiv.org/abs/1905.13539
#ArtificialIntelligence #DeepLearning #MachineLearning
See comment on new Chinese AI ethics principles: https://www.technologyreview.com/s/613610/why-does-china-suddenly-care-about-ai-ethics-and-privacy/
MIT Technology Review
Why does Beijing suddenly care about AI ethics?
New guidelines on freedom and privacy protection signal that the Chinese state is open to dialogue about how it uses technology.
This new paper shows how to use #machinelearning to steal pins and passwords using only the sound you make when typing them on your phone or tablet.
Download Link: https://arxiv.org/pdf/1903.11137.pdf
Download Link: https://arxiv.org/pdf/1903.11137.pdf
Deep Learning Gallery - a curated list of awesome deep learning projects
https://deeplearninggallery.com/
https://deeplearninggallery.com/
Deeplearninggallery
Deep Learning Gallery - a curated list of awesome deep learning projects
Showcase of the best deep learning algorithms and deep learning applications.
Deep Learning with MATLAB: Deep Learning in 11 Lines of MATLAB Code
https://nl.mathworks.com/videos/deep-learning-in-11-lines-of-matlab-code-1481229977318.html
https://nl.mathworks.com/videos/deep-learning-in-11-lines-of-matlab-code-1481229977318.html
Mathworks
Deep Learning: Deep Learning in 11 Lines of MATLAB Code
See how to use MATLAB, a simple webcam, and a deep neural network to identify objects in your surroundings. This demo uses AlexNet, a pretrained deep convolutional neural network that has been trained on over a million images.
Energy and Policy Considerations for Deep Learning in NLP.
https://drive.google.com/file/d/1v3TxkqPuzvRfiV_RVyRTTFbHl1pZq7Ab/view
https://drive.google.com/file/d/1v3TxkqPuzvRfiV_RVyRTTFbHl1pZq7Ab/view
Google Docs
acl2019.pdf
Quantum entanglement begat space-time.
Fascinating.
Those AdS spaces look a lot like Maximilian Nickel's hyperbolic space embeddings.
And those MERA tensor networks look a lot like ConvNets.
https://www.nature.com/news/the-quantum-source-of-space-time-1.18797
Fascinating.
Those AdS spaces look a lot like Maximilian Nickel's hyperbolic space embeddings.
And those MERA tensor networks look a lot like ConvNets.
https://www.nature.com/news/the-quantum-source-of-space-time-1.18797
Nature News & Comment
The quantum source of space-time
Many physicists believe that entanglement is the essence of quantum weirdness — and some now suspect that it may also be the essence of space-time geometry.
New slides: "Pretraining for Generation" at neuralgen 2019 Includes
overview of methods and new gpt-2 experiments on "pseudo-self attention"
Alexander Rush(Zack Ziegler, Luke Melas-Kyriazi, Sebastian Gehrmann)HarvardNLP / Cornell Tech
https://nlp.seas.harvard.edu/slides/Pre-training%20for%20Generation.pdf
overview of methods and new gpt-2 experiments on "pseudo-self attention"
Alexander Rush(Zack Ziegler, Luke Melas-Kyriazi, Sebastian Gehrmann)HarvardNLP / Cornell Tech
https://nlp.seas.harvard.edu/slides/Pre-training%20for%20Generation.pdf
Reliability in Reinforcement Learning
https://www.microsoft.com/en-us/research/blog/reliability-in-reinforcement-learning/?ocid=msr_blog_reliabrl_tw
https://www.microsoft.com/en-us/research/blog/reliability-in-reinforcement-learning/?ocid=msr_blog_reliabrl_tw
Encrypted Deep Learning Classification with PyTorch &
PySyft
https://blog.openmined.org/encrypted-deep-learning-classification-with-pysyft/
PySyft
https://blog.openmined.org/encrypted-deep-learning-classification-with-pysyft/
Driver Behavior Analysis Using Lane Departure Detection Under Challenging Conditions. arxiv.org/abs/1906.00093