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Differentiable Beam search Decoder (DBD): training a speech recognition system by backpropagating through the decoder leads to smaller models and better word error rates.

Paper from FAIRies Ronan Collobert, Awni Hannun and Gabriel Synnaeve here: https://arxiv.org/abs/1902.06022

Awesome stuff. We were doing a simple version of thise to train our check recognition system in the mid-1990s.

https://ai.facebook.com/blog/combining-acoustic-and-language-model-training-for-speech-recognition/
ICML 2019 Tutorial Videos

A Neural Approaches to Conversational UI
https://www.youtube.com/watch?v=nr3P1VrFleo
Algorithm configuration: learning in the space of algorithm designs
https://www.youtube.com/watch?v=bIsRNgg20xo
After everything that has happened this year, I'm glad Schmidhuber still has the fire in him. 🔥 https://arxiv.org/abs/1906.04493
Shapes and Context:
In-the-wild Image Synthesis & Manipulation

https://www.cs.cmu.edu/~aayushb/OpenShapes/
"Likelihood Ratios for Out-of-Distribution Detection"
Ren et al.: https://arxiv.org/abs/1906.02845
#artificialintelligence #deeplearning #machinelearning
Invertible Residual Networks
Official Pytorch implementation of i-ResNets.
By Jorn Jacobsen: https://github.com/jhjacobsen/invertible-resnet
#pytorch #technology #machinelearning