A school in China is monitoring students with facial-recognition technology that scans the classroom every 30 seconds
https://www.businessinsider.com/china-school-facial-recognition-technology-2018-5
https://www.businessinsider.com/china-school-facial-recognition-technology-2018-5
Business Insider
A school in China is monitoring students with facial-recognition technology that scans the classroom every 30 seconds
The system is analyzing students' emotions and actions in the classroom to tell whether they are happy, angry, or confused and to monitor whether they are working or sleeping at their desk. The facial-recognition technology has also replaced ID cards and…
A free resource for researchers and practitioners to find and follow the latest state-of-the-art ML papers and code.
https://paperswithcode.com/sota?fbclid=IwAR0r0_RDwcrNUFjNCXlVkQXkarmXlgEKk4Vy5Zn6XQ7nAGq1D1yBlCZhXY8
https://paperswithcode.com/sota?fbclid=IwAR0r0_RDwcrNUFjNCXlVkQXkarmXlgEKk4Vy5Zn6XQ7nAGq1D1yBlCZhXY8
Paperswithcode
Papers with Code - Browse the State-of-the-Art in Machine Learning
5452 leaderboards • 2466 tasks • 4859 datasets • 54930 papers with code.
This is my neck of the woods. - DL
https://www.wbur.org/news/2019/11/25/boston-dynamics-robot-dog-massachusetts-state-police
https://www.wbur.org/news/2019/11/25/boston-dynamics-robot-dog-massachusetts-state-police
WBUR
Mass. State Police Tested Out Boston Dynamics’ Spot The Robot Dog. Civil Liberties Advocates Want To Know More
Massachusetts State Police is the first law enforcement agency in the country to use Boston Dynamics' dog-like robot, called Spot. That's raising questions from civil rights advocates about how much oversight there should be over police robotics programs.
DeepSynth: Program Synthesis for Automatic Task Segmentation in Deep Reinforcement Learning. https://arxiv.org/abs/1911.10244
SWAG: Item Recommendations using Convolutions on Weighted Graphs. https://arxiv.org/abs/1911.10232
ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation Anchoring. https://arxiv.org/abs/1911.09785
arXiv.org
ReMixMatch: Semi-Supervised Learning with Distribution Alignment...
We improve the recently-proposed "MixMatch" semi-supervised learning algorithm by introducing two new techniques: distribution alignment and augmentation anchoring. Distribution alignment...
Single Headed Attention RNN: Stop Thinking With Your Head
Stephen Merity : https://arxiv.org/abs/1911.11423
#ArtificialIntelligence #NeuralComputing #NLP
Stephen Merity : https://arxiv.org/abs/1911.11423
#ArtificialIntelligence #NeuralComputing #NLP
arXiv.org
Single Headed Attention RNN: Stop Thinking With Your Head
The leading approaches in language modeling are all obsessed with TV shows of my youth - namely Transformers and Sesame Street. Transformers this, Transformers that, and over here a bonfire worth...
Causality for Machine Learning
Bernhard Schölkopf : https://arxiv.org/abs/1911.10500
#MachineLearning #DeepLearning #ArtificialIntelligence
Bernhard Schölkopf : https://arxiv.org/abs/1911.10500
#MachineLearning #DeepLearning #ArtificialIntelligence
arXiv.org
Causality for Machine Learning
Graphical causal inference as pioneered by Judea Pearl arose from research on artificial intelligence (AI), and for a long time had little connection to the field of machine learning.
This...
This...
Richard S. Sutton: intelligence is trying to build a model of the world.
Exactly.
https://www.youtube.com/watch?v=XqzT-rBDTPU&fbclid=IwAR3jWkhrWorNDr9Wyvd_zS71O3jrspT3aPzYCJ93ussUPiOnOd7ZRO_EWUc
Exactly.
https://www.youtube.com/watch?v=XqzT-rBDTPU&fbclid=IwAR3jWkhrWorNDr9Wyvd_zS71O3jrspT3aPzYCJ93ussUPiOnOd7ZRO_EWUc
YouTube
The Brains Behind AI: Rich Sutton
Solving the mysteries of machine intelligence could lead to more profound answers about our own human intelligence. Rich Sutton is pioneering the field of reinforcement learning, a type of machine learning that allows machines to learn from interactions with…
This is an exhaustive list of Monte Carlo tree search papers from major conferences including NIPS, ICML, and AAAI. Some of them with publicly available implementations.
https://github.com/benedekrozemberczki/awesome-monte-carlo-tree-search-papers
#datascience #machinelearning #deeplearning #python #ai #analytics #datamining
https://github.com/benedekrozemberczki/awesome-monte-carlo-tree-search-papers
#datascience #machinelearning #deeplearning #python #ai #analytics #datamining
GitHub
GitHub - benedekrozemberczki/awesome-monte-carlo-tree-search-papers: A curated list of Monte Carlo tree search papers with implementations.
A curated list of Monte Carlo tree search papers with implementations. - GitHub - benedekrozemberczki/awesome-monte-carlo-tree-search-papers: A curated list of Monte Carlo tree search papers with ...
Iteratively-Refined Interactive 3D Medical Image Segmentation with Multi-Agent Reinforcem... https://arxiv.org/abs/1911.10334
arXiv.org
Iteratively-Refined Interactive 3D Medical Image Segmentation with...
Existing automatic 3D image segmentation methods usually fail to meet the clinic use. Many studies have explored an interactive strategy to improve the image segmentation performance by...
Compressing Representations for Embedded Deep Learning. https://arxiv.org/abs/1911.10321
arXiv.org
Compressing Representations for Embedded Deep Learning
Despite recent advances in architectures for mobile devices, deep learning
computational requirements remains prohibitive for most embedded devices. To
address that issue, we envision sharing the...
computational requirements remains prohibitive for most embedded devices. To
address that issue, we envision sharing the...
PlantDoc: A Dataset for Visual Plant Disease Detection. https://arxiv.org/abs/1911.10317
Deep learning achieved great success in modeling sensory processing. However, such models raise questions about the very nature of explanation in neuroscience. Are we simply replacing one complex system (biological circuit) with another (a deep net), without understanding either? https://papers.nips.cc/paper/9060-from-deep-learning-to-mechanistic-understanding-in-neuroscience-the-structure-of-retinal-prediction https://t.iss.one/ArtificialIntelligenceArticles
Deep learning from the topological, metric, information, causal, physics, computational, and neuroscience perspective. A nice assay by Raul Vicente: "The many faces of deep learning:" https://arxiv.org/abs/1908.10206