Welcome to ICML 2019 Tutorial session: Never-Ending Learning

Presented by Tom Mitchell and Partha Talukdar


https://www.youtube.com/watch?v=0TADiY7iPAc

https://t.iss.one/ArtificialIntelligenceArticles

Welcome to the ICML 2019 Tutorial session: A Tutorial on Attention in Deep Learning

Presented by Alex Smola and Aston Zhang

https://www.youtube.com/watch?v=nS1Lse2B48w

New DeepMind Unsupervised Image Model Challenges AlexNet
https://medium.com/syncedreview/new-deepmind-unsupervised-image-model-challenges-alexnet-d658ef92ab1e

ICML 2019 Best Paper Award
https://proceedings.mlr.press/v97/locatello19a.html https://t.iss.one/ArtificialIntelligenceArticles

Rates of Convergence for Sparse Variational Gaussian Process Regression
arxiv.org/abs/1903.03571 https://t.iss.one/ArtificialIntelligenceArticles

CVPR’19 paper on speech-to-gesture prediction. Given raw speech audio, predict arm/hand motion to go along with it. Check out video, or download 128 hours of video for 10 speakers
Learning Individual Styles of Conversational Gesture
https://people.eecs.berkeley.edu/~shiry/speech2gesture/

Congratulations to the Best Papers at the ongoing #ICML2019
The Thirty-sixth International Conference on Machine Learning, Long Beach, USA

(1)Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations https://arxiv.org/pdf/1811.12359.pdf
Congratulations to the GoogleAI team of Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain Gelly,Bernhard Schölkopf, Olivier Bachem

(2)Rates of Convergence for Sparse Variational Gaussian Process Regression
https://arxiv.org/pdf/1903.03571.pdf
Kudos to David R. Burt, Carl E. Rasmussen, Mark van der Wilk of University of Cambridge

ICML is one of the premier machine learning conferences. VideoKen is proud to power deep indexing of the entire ICML 2019 video content. Catch up with all of the exciting tutorials here:

https://search.videoken.com/?orgId=133


#MachineLearning #AI #DeepLearning #AIplayer #ICML2019

Language, trees, and geometry in neural networks
code https://pair-code.github.io/interpretability/bert-tree/
paper https://arxiv.org/pdf/1906.02715.pdf

ICYMI: A project that aims to generate images that depict accurate, vivid, and personalized outcomes of climate change using Cycle-Consistent Adversarial Networks (CycleGANs).

https://www.profillic.com/paper/arxiv:1905.03709

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/

Deep Learning Tools

PDF Version: https://drive.google.com/file/d/1XhngKISDpQgwGlvU-hjXWZb_qfyIYjqN/view

Source: Kdnuggets

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/

Adaptive Neural Trees (ANTs) - icml2019 paper
combined benefits of decision trees and deep neural networks.
code https://github.com/rtanno21609/AdaptiveNeuralTrees
paper https://proceedings.mlr.press/v97/tanno19a.html

CVPR 2019

Papers: https://openaccess.thecvf.com/CVPR2019.py

Workshops: https://openaccess.thecvf.com/CVPR2019_workshops/menu.py

Good summary article about GANs
https://machinelearningmastery.com/resources-for-getting-started-with-generative-adversarial-networks/