The Disruptions of 5G on Data-driven Technologies and Applications. https://arxiv.org/abs/1909.08096
Adversarial Attacks and Defenses in Images, Graphs and Text: A Review. https://arxiv.org/abs/1909.08072
Megatron-LM: Training Multi-Billion Parameter Language Models Using GPU Model Parallelism. https://arxiv.org/abs/1909.08053
A Deep Learning Approach to Data Compression
Blog by Friso Kingma : https://bair.berkeley.edu/blog/2019/09/19/bit-swap/
#ArtificialIntelligence #DeepLearning #MachineLearning
Blog by Friso Kingma : https://bair.berkeley.edu/blog/2019/09/19/bit-swap/
#ArtificialIntelligence #DeepLearning #MachineLearning
The Berkeley Artificial Intelligence Research Blog
A Deep Learning Approach to Data Compression
The BAIR Blog
We're thrilled to announce that the Fall 2020 admissions applications are open! We're ready for the next cohort of future Data Scientists! Please click on the links below for more information! The application deadline for the MS Degree is January 22, 2020 and the deadline for the Ph.D. is December 12, 2019.
For MS Degree information please click the link below.:
https://cds.nyu.edu/ms-adm-req/
For Ph.D. information please click the link below:
https://cds.nyu.edu/academics/phd/
For MS Degree information please click the link below.:
https://cds.nyu.edu/ms-adm-req/
For Ph.D. information please click the link below:
https://cds.nyu.edu/academics/phd/
ns3-gym: Extending OpenAI Gym for Networking Research
Piotr Gawłowicz and Anatolij Zubow : https://arxiv.org/abs/1810.03943
#OpenAIGym #Networking #Research
Piotr Gawłowicz and Anatolij Zubow : https://arxiv.org/abs/1810.03943
#OpenAIGym #Networking #Research
arXiv.org
ns3-gym: Extending OpenAI Gym for Networking Research
OpenAI Gym is a toolkit for reinforcement learning (RL) research. It includes a large number of well-known problems that expose a common interface allowing to directly compare the performance...
Here's a list of 7 top research on arXiV on AI/deep learning for August 2019 as per Daniel Gutierrez
1) A Probabilistic Representation of Deep Learning
Link: https://arxiv.org/pdf/1908.09772v1.pdf
2) Inception-inspired LSTM for Next-frame Video Prediction
@ArtificialIntelligenceArticles
Link: https://arxiv.org/pdf/1909.05622.pdf
3) Systematic Analysis of Image Generation using GANs
Link: https://arxiv.org/ftp/arxiv/papers/1908/1908.11863.pdf
@ArtificialIntelligenceArticles
4) Dynamic Stale Synchronous Parallel Distributed Training for Deep Learning
Link: https://arxiv.org/pdf/1908.11848.pdf
5) Discovering Reliable Correlations in Categorical Data
Link: https://arxiv.org/pdf/1908.11682.pdf
6) Smaller Models, Better Generalization
Link: https://arxiv.org/pdf/1908.11250.pdf
7) An Auto-ML Framework Based on GBDT for Lifelong Learning
Link: https://arxiv.org/pdf/1908.11033.pdf
Source: https://insidebigdata.com/2019/09/18/best-of-arxiv-org-for-ai-machine-learning-and-deep-learning-august-2019/
@ArtificialIntelligenceArticles
1) A Probabilistic Representation of Deep Learning
Link: https://arxiv.org/pdf/1908.09772v1.pdf
2) Inception-inspired LSTM for Next-frame Video Prediction
@ArtificialIntelligenceArticles
Link: https://arxiv.org/pdf/1909.05622.pdf
3) Systematic Analysis of Image Generation using GANs
Link: https://arxiv.org/ftp/arxiv/papers/1908/1908.11863.pdf
@ArtificialIntelligenceArticles
4) Dynamic Stale Synchronous Parallel Distributed Training for Deep Learning
Link: https://arxiv.org/pdf/1908.11848.pdf
5) Discovering Reliable Correlations in Categorical Data
Link: https://arxiv.org/pdf/1908.11682.pdf
6) Smaller Models, Better Generalization
Link: https://arxiv.org/pdf/1908.11250.pdf
7) An Auto-ML Framework Based on GBDT for Lifelong Learning
Link: https://arxiv.org/pdf/1908.11033.pdf
Source: https://insidebigdata.com/2019/09/18/best-of-arxiv-org-for-ai-machine-learning-and-deep-learning-august-2019/
@ArtificialIntelligenceArticles
insideBIGDATA
Best of arXiv.org for AI, Machine Learning, and Deep Learning – August 2019
In this recurring monthly feature, we will filter all the recent research papers appearing in the arXiv.org preprint server for subjects relating to AI, [...]
A Friendly Introduction to Real-Time Object Detection using the Powerful SlimYOLOv3 Framework
https://www.analyticsvidhya.com/blog/2019/08/introduction-slimyolov3-real-time-object-detection/
https://www.analyticsvidhya.com/blog/2019/08/introduction-slimyolov3-real-time-object-detection/
Analytics Vidhya
Real-Time Object Detection using SlimYOLOv3 - A Detailed Introduction
Real-time object detection is the next big thing in computer vision and deep learning. Learn how to perform real-time object detection using SlimYOLOv3.
Senior Data Scientist – Digital
https://ai-jobs.net/job/senior-data-scientist-digital/
https://ai-jobs.net/job/senior-data-scientist-digital/
ai-jobs.net
Senior Data Scientist - Digital | ai-jobs.net
Senior Data Scientist – Digital Joining Capco means joining an organisation that is committed to an inclusive working environment where you’re encouraged to #BeYourselfAtWork. We celebrate individuality and recognize that diversity and inclusion, in all …
Metropolis Colorized with DeOldify https://www.youtube.com/watch?v=t75yctjjfx0
CS221: Artificial Intelligence: Principles and Techniques
https://web.stanford.edu/class/cs221/
https://youtu.be/OQQ-W_63UgQ?fbclid=IwAR2ig2e9oqHPwem0S_6FtLky7QRxIO3BBYyRdyFvHUmukV0cCuKnSDImzsg
https://web.stanford.edu/class/cs221/
https://youtu.be/OQQ-W_63UgQ?fbclid=IwAR2ig2e9oqHPwem0S_6FtLky7QRxIO3BBYyRdyFvHUmukV0cCuKnSDImzsg
YouTube
Lecture 1 | Natural Language Processing with Deep Learning
Lecture 1 introduces the concept of Natural Language Processing (NLP) and the problems NLP faces today. The concept of representing words as numeric vectors ...
Deep Multi-Agent Reinforcement Learning
Jakob N. Foerster : https://ora.ox.ac.uk/objects/uuid:a55621b3-53c0-4e1b-ad1c-92438b57ffa4
Jakob N. Foerster : https://ora.ox.ac.uk/objects/uuid:a55621b3-53c0-4e1b-ad1c-92438b57ffa4
The Mathematics of Machine Learning by UC Berkeley: Written by - Garret Thomas
Link: https://gwthomas.github.io/docs/math4ml.pdf?fbclid=IwAR2UsBgZW9MRgS3nEo8Zh_ukUFnwtFeQS8Ek3OjGxZtDa7UxTYgIs_9pzSI
Link: https://gwthomas.github.io/docs/math4ml.pdf?fbclid=IwAR2UsBgZW9MRgS3nEo8Zh_ukUFnwtFeQS8Ek3OjGxZtDa7UxTYgIs_9pzSI
HYPE: A Benchmark for Human eYe Perceptual Evaluation of Generative Models
Human evaluation for generative models have been ad-hoc.
They propose a standard human benchmark for generative realism that is grounded in psychophysics research in perception.
https://arxiv.org/abs/1904.01121
https://hype.stanford.edu/
Human evaluation for generative models have been ad-hoc.
They propose a standard human benchmark for generative realism that is grounded in psychophysics research in perception.
https://arxiv.org/abs/1904.01121
https://hype.stanford.edu/
arXiv.org
HYPE: A Benchmark for Human eYe Perceptual Evaluation of Generative Models
Generative models often use human evaluations to measure the perceived quality of their outputs. Automated metrics are noisy indirect proxies, because they rely on heuristics or pretrained...