Lip Reading
Multi-Modal Methods: Visual Speech Recognition (Lip Reading) —- hundreds of thousands of people with speech impairments, every year, could one day benefit from this technology https://t.co/lZMN6a62UW
— Nando de Freitas (@NandoDF) June 19, 2018
Best Paper Award at #CVPR2018
Best paper award at #CVPR2018 main idea: study twenty five different visual tasks to understand how & when transfer learning works from one task to another, reducing demand for labelled data.
— Reza Zadeh (@Reza_Zadeh) June 19, 2018
Paper: https://t.co/18HUu6QnHx
Data: https://t.co/HIBR1mR9yq pic.twitter.com/Ya0jAGh5pp
Congratulations to Best Paper Award by @zamir_ar @silviocinguetta @StanfordCVGL & collaborators at #CVPR2018, a computational map of perceptual task transfer learning!! https://t.co/1pLD4hVwmO
— Fei-Fei Li (@drfeifei) June 19, 2018
Graph RNN
GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Model by @youjiaxuan, R. Ying, @xiangrenUSC, @williamleif, and @jure#ICML2018 Paper: https://t.co/OsM0cIAH1o@PyTorch Code: https://t.co/Z8AiTSCOIt
— Brandon Amos (@brandondamos) June 20, 2018
Unofficial Slides: https://t.co/hz6sWugVBn pic.twitter.com/8cg7JobrX2
GCP Pre-emptive TPU
Google Cloud TPUs now offer preemptible pricing at ~70% off the reserved instance pricing. This means, for example, that you can train a ResNet-50 model for ~$7.50 instead of $25, or a Transformer neural translation model for ~$13 instead of $41.
— Jeff Dean (@JeffDean) June 19, 2018
See:https://t.co/EnJXQjbuhN pic.twitter.com/2fBmY3P6Bf
Spot-pricing on TPUs is getting good. We have prototyped TPU-PyTorch support (w. Google engineers), hammering coverage and performance now. Promising times.... https://t.co/v7Lz6I2JWH
— Soumith Chintala (@soumithchintala) June 19, 2018
DensePose Open-Sourced
DensePose is now open source (and at the top of Hacker News yesterday). https://t.co/uJ0pwkgw5P
— Yann LeCun (@ylecun) June 20, 2018
[ethics] MS Employees Speaking Out
In a letter to @satyanadella, Microsoft employees are asking the company to terminate its contract with ICE https://t.co/ZVParowmr5
— kate conger (@kateconger) June 19, 2018
Microsoft workers request MS:
— Lilly Irani (@gleemie) June 20, 2018
1. Cancel the existing Azure Gov contract with ICE immediately.
2. Draft, publicize, enforce clear policy stating that neither MS nor its contractors will work w/clients who violate int'l human rights law.
3. Commit to transparency and review... https://t.co/gAHL0bAbUm
Tech employees should question what applications their tech is being used for. Employees have more power now as tech companies have evolved to be run by engineers and scientists over the past decade. https://t.co/DxpQqjyMDc
— hardmaru (@hardmaru) June 19, 2018
Here’s @satyanadella echoing our earlier reporting, saying Microsoft’s ICE contract doesn’t involve facial recognition. No explanation for the January blog that claimed otherwise https://t.co/4Puv7629fD
— kate conger (@kateconger) June 20, 2018
Notable Research
Interesting: https://t.co/VxldDWw8h1 "modern" CNN classifiers, using less pooling layers (compensated by strided conv), are more accurate than older ones, but at the same time less invariant to translation because of Shannon's theorem @rasbt @fhuszar @roydanroy @TacoCohen
— andrea panizza (@unsorsodicorda) June 19, 2018
"Deep Neural Decision Trees," Yang et al.: https://t.co/655f9uBWQz
— Miles Brundage (@Miles_Brundage) June 20, 2018
Tutorials and Resources
Horizon charts of realtime data. https://t.co/SpBlpdwDCn
— Mike Bostock (@mbostock) June 19, 2018
What is the role of qualitative methods in addressing issues of replicability, reproducibility, and rigor? https://t.co/aJ33RXF8wx
— Andrew Gelman (@StatModeling) June 19, 2018
"Deep Learning for Dialogue Systems" - great [TUTORIAL] by @YunNungChen https://t.co/Dq8xmHriLe
— Xavier 🎗🤖🏃 (@xamat) June 20, 2018
Monte Carlo Tree Search - beginners tutorial https://t.co/Na5k8mhrJv
— Nando de Freitas (@NandoDF) June 19, 2018
Apex is a PyTorch extension from @nvidia that makes it easy to use mixed-precision training and use Volta Tensor Cores to full potential. Read more at: https://t.co/9xuOLAyGJT
— PyTorch (@PyTorch) June 19, 2018
Value-Suppressing Uncertainty Palettes
How might visualizations help people reason more cautiously in the face of uncertainty? Value-Suppressing Uncertainty Palettes intentionally make uncertain values harder to distinguish! https://t.co/TciyeqjSHs
— Interactive Data Lab (@uwdata) June 19, 2018
rstats
I love do 🖤 a good workflow…
— Mara Averick (@dataandme) June 19, 2018
"File organization best practices" by @abtran https://t.co/PE7lLypdkX #rstats pic.twitter.com/ZvRX244aAr
ICYMI, 🎞 step-by-step monte carlo w/ magick!
— Mara Averick (@dataandme) June 19, 2018
"Animating a Monte Carlo Simulation" by Thomas Rohhttps://t.co/YOCtIYLZBM #rstats #dataviz #infovis pic.twitter.com/XZJsXI2YNS
Miscellaneous
Remember engineers, have ethics. If you are asked to do something illegal or morally wrong then say no. You can go to jail for doing what the boss says. https://t.co/wY7Hh51Y80
— Jim Bennett ☁️ (@jimbobbennett) June 19, 2018
Kjell and I are writing another book on predictive modeling, this time focused on all the things that you can do with predictors. It's about 60% done and we'd love to get feedback. Check it out at https://t.co/sU9nyCcSql #rstats #MachineLearning pic.twitter.com/T1tVcZAmcL
— Max Kuhn (@topepos) May 14, 2018
Deep Learning; The study of neural networks and the art of making all kinds of stuff differentiable (including things that really shouldn’t be)
— Denny Britz (@dennybritz) June 19, 2018
Official launch of the competition for software developers to use graduate salary & employment outcomes data to create apps to shape prospective students' choices about universities & degrees - open to 'an organisation of any size'... https://t.co/20K2DS6hL0
— Ben Williamson (@BenPatrickWill) June 19, 2018
Surprise! Patent trolls don't lead to innovation or knowledge sharing. Largest survey yet. https://t.co/cIOCJ49X7c
— James Bessen (@JamesBessen) June 19, 2018
An important lesson that I wish I could impart on everybody: A metric is usually a proxy. Getting very good at the metric means it is time to perform qualitative analysis whether the metric achieves the qualitative improvements it was designed to proxy for.
— halvarflake (@halvarflake) June 19, 2018