Improving Generalization in Meta Reinforcement Learning using Learned Objectives
Louis Kirsch, Sjoerd van Steenkiste, Jürgen Schmidhuber : https://arxiv.org/abs/1910.04098
#ArtificialIntelligence #MetaReinforcementLearning #ReinforcementLearning
Louis Kirsch, Sjoerd van Steenkiste, Jürgen Schmidhuber : https://arxiv.org/abs/1910.04098
#ArtificialIntelligence #MetaReinforcementLearning #ReinforcementLearning
NIPS 2017 Invited talk
"Deep Reinforcement Learning with Subgoals"
By David Silver: https://vimeo.com/249557775
#ArtificialIntelligence #DeepLearning #MachineLearning #NeuralNetworks #ReinforcementLearning
"Deep Reinforcement Learning with Subgoals"
By David Silver: https://vimeo.com/249557775
#ArtificialIntelligence #DeepLearning #MachineLearning #NeuralNetworks #ReinforcementLearning
ArtificialIntelligenceArticles
interesting. https://www.biorxiv.org/content/10.1101/787101v2 https://www.youtube.com/watch?time_continue=40&v=nf-P3b2AnZw&fbclid=IwAR3Vtk9MKYPb6KFRIvk3Bgjeedw-i-8th1srJpbNQVHR_KpOzMa-p50RHx0
Tech Xplore
Neural network reconstructs human thoughts from brain waves in real time
Researchers from Russian corporation Neurobotics and the Moscow Institute of Physics and Technology have found a way to visualize a person's brain activity as actual images mimicking what they observe ...
PyRoboLearn: A Python Framework for Robot Learning Practitioners
Delhaisse et al.: https://robotlearn.github.io/pyrobolearn/
#ArtificialIntelligence #Python #Robotics
Delhaisse et al.: https://robotlearn.github.io/pyrobolearn/
#ArtificialIntelligence #Python #Robotics
Google PhD Fellowship program is now accepting applications.
Deadline is Dec 1st.
Google PhD Fellowships directly support graduate students as they pursue their PhD, as well as connect them to a Google Research Mentor.
https://ai.google/research/outreach/phd-fellowship/
Deadline is Dec 1st.
Google PhD Fellowships directly support graduate students as they pursue their PhD, as well as connect them to a Google Research Mentor.
https://ai.google/research/outreach/phd-fellowship/
research.google
Google PhD fellowship program
The Google PhD Fellowship Program recognizes outstanding graduate students doing exceptional work in computer science, related disciplines, or promising research areas.
The lighter side of Reinforcemnent Learning... 😂
"Encouraged to try to touch the ball as many times as it can, the robot develops a strategy of standing next to the ball and rapidly vibrating."
From "Rebooting AI: Building Artificial Intelligence We Can Trust|" by Gary Marcus and Ernest Davis.
https://www.amazon.com/Rebooting-AI-Building-Artificial-Intelligence/dp/1524748250
"Encouraged to try to touch the ball as many times as it can, the robot develops a strategy of standing next to the ball and rapidly vibrating."
From "Rebooting AI: Building Artificial Intelligence We Can Trust|" by Gary Marcus and Ernest Davis.
https://www.amazon.com/Rebooting-AI-Building-Artificial-Intelligence/dp/1524748250
Adversarial NLI: A New Benchmark for Natural Language Understanding
Nie et al.: https://arxiv.org/abs/1910.14599
#NaturalLanguageUnderstanding #MachineLearning #DeepLearning
Nie et al.: https://arxiv.org/abs/1910.14599
#NaturalLanguageUnderstanding #MachineLearning #DeepLearning
What does it mean for a machine to “understand”?
The use of words like “real”, “true”, and “genuine” imply that “understanding” is binary ... I argue that “understanding” exists along a continuous spectrum of capabilities.
In order for a system to understand, it must create linkages between different concepts, states, and actions. Today’s language translation systems correctly link “water” in English to “agua” in Spanish, but they don’t have any links between “water” and “electric shock”.
Seeking a definition of intelligence without including an agent’s environment is like seeking the sound of one hand clapping.
The other motivation of definitions of intelligence is that of Occam’s razor. This is what motivates the idea that compression is equal to intelligence.
Blogs
https://medium.com/@tdietterich/what-does-it-mean-for-a-machine-to-understand-555485f3ad40
https://medium.com/intuitionmachine/how-to-define-intelligence-b9bac630960b
The use of words like “real”, “true”, and “genuine” imply that “understanding” is binary ... I argue that “understanding” exists along a continuous spectrum of capabilities.
In order for a system to understand, it must create linkages between different concepts, states, and actions. Today’s language translation systems correctly link “water” in English to “agua” in Spanish, but they don’t have any links between “water” and “electric shock”.
Seeking a definition of intelligence without including an agent’s environment is like seeking the sound of one hand clapping.
The other motivation of definitions of intelligence is that of Occam’s razor. This is what motivates the idea that compression is equal to intelligence.
Blogs
https://medium.com/@tdietterich/what-does-it-mean-for-a-machine-to-understand-555485f3ad40
https://medium.com/intuitionmachine/how-to-define-intelligence-b9bac630960b
Medium
What does it mean for a machine to “understand”?
Critics of recent advances in artificial intelligence complain that although these advances have produced remarkable improvements in AI…
ArtificialIntelligenceArticles
Quantum Supremacy Using a Programmable Superconducting Processor Blog by John Martinis and Sergio Boixo : https://ai.googleblog.com/2019/10/quantum-supremacy-using-programmable.html #QuantumComputer #QuantumPhysics #QuantumSupremacy
Quantum supremacy using a programmable superconducting processor - J. Martinis - 11/1/2019
IQIM Seminar by John Martinis (Research Scientist and Professor of Physics Google and University of California, Santa Barbara), "Quantum supremacy using a programmable superconducting processor"
https://www.youtube.com/watch?v=FklMpRiTeTA
https://t.iss.one/ArtificialIntelligenceArticles
IQIM Seminar by John Martinis (Research Scientist and Professor of Physics Google and University of California, Santa Barbara), "Quantum supremacy using a programmable superconducting processor"
https://www.youtube.com/watch?v=FklMpRiTeTA
https://t.iss.one/ArtificialIntelligenceArticles
YouTube
Quantum supremacy using a programmable superconducting processor - J. Martinis - 11/1/2019
IQIM Seminar by John Martinis (Research Scientist and Professor of Physics Google and University of California, Santa Barbara), "Quantum supremacy using a programmable superconducting processor"
Presented in Caltech's Ramo Auditorium, November 1, 2019
…
Presented in Caltech's Ramo Auditorium, November 1, 2019
…
TensorFlow World 2019 Keynote
https://www.youtube.com/watch?v=MunFeX-0MD8&list=PLQY2H8rRoyvxcmHHRftsuiO1GyinVAwUg
https://www.youtube.com/watch?v=MunFeX-0MD8&list=PLQY2H8rRoyvxcmHHRftsuiO1GyinVAwUg
YouTube
TensorFlow World 2019 Keynote
O'Reilly and TensorFlow are teaming up to present the first TensorFlow World. It brings together the growing TensorFlow community to learn from each other an...
Making an Invisibility Cloak for evading Object Detectors!
https://www.profillic.com/paper/arxiv:1910.14667
(eg.the YOLOv2 detector is evaded using a pattern trained on the COCO dataset with a carefully constructed objective.)
Btw if you're interested in implementing this in your project/product, feel free to DM me
https://www.profillic.com/paper/arxiv:1910.14667
(eg.the YOLOv2 detector is evaded using a pattern trained on the COCO dataset with a carefully constructed objective.)
Btw if you're interested in implementing this in your project/product, feel free to DM me
Profillic
Making an Invisibility Cloak: Real World Adversarial Attacks on Object Detectors - Profillic
Explore state-of-the-art in machine learning, AI, and robotics. Browse models, source code, papers by topics and authors. Connect with researchers and engineers working on related problems in machine learning, deep learning, natural language processing, robotics…
Limitations of the Empirical Fisher Approximation
Kunstner et al.: https://arxiv.org/abs/1905.12558
#ArtificialIntelligence #MachineLearning
Kunstner et al.: https://arxiv.org/abs/1905.12558
#ArtificialIntelligence #MachineLearning
arXiv.org
Limitations of the Empirical Fisher Approximation for Natural...
Natural gradient descent, which preconditions a gradient descent update with the Fisher information matrix of the underlying statistical model, is a way to capture partial second-order...
Submitted to WACV 2020: Turning low-resolution pictures to super high resolution
https://www.profillic.com/paper/arxiv:1910.08761
a fully convolutional multi-stage neural network for 4× super-resolution for face images.
https://www.profillic.com/paper/arxiv:1910.08761
a fully convolutional multi-stage neural network for 4× super-resolution for face images.
Profillic
Component Attention Guided Face Super-Resolution Network: CAGFace: Model and Code
Click To Get Model/Code. To make the best use of the underlying structure of faces, the collective information through face datasets and the intermediate estimates during the upsampling process, here we introduce a fully convolutional multi-stage neural network…
On the Interaction Between Deep Detectors and Siamese Trackers in Video Surveillance
Kiran et al.: https://arxiv.org/abs/1910.14552
#ArtificialIntelligence #DeepLearning #MachineLearning
Kiran et al.: https://arxiv.org/abs/1910.14552
#ArtificialIntelligence #DeepLearning #MachineLearning
arXiv.org
On the Interaction Between Deep Detectors and Siamese Trackers in...
Visual object tracking is an important function in many real-time video
surveillance applications, such as localization and spatio-temporal recognition
of persons. In real-world applications, an...
surveillance applications, such as localization and spatio-temporal recognition
of persons. In real-world applications, an...