Day 4 at ICML 2017 — more Adversarial NNs

The morning talk was about Deep Reinforcement Learning in Complex environment by Raia Hadsell from Deep Mind.  In overall lots of great talks on the conference from DeepMind and Google Brain. The talk was generously sprinkled with newly published papers by DeepMind researches in Reinforcement Learning\Gaming space. Angry Birds are not yet solved, just FYI if somebody is up for a challenge.

Main algos\approaches covered in talk were: hierarchical reinforcement learning,  continual learning,  continuous control, multimodal agents, auxiliary tasks. See quite entertaining and nicely annotated demos here.

Deep learning & hardware

Main  theme: let’s use CPUs effectively and make NN computation effective on mobile devices.

Brain endurance or Day 2 at ICML 2017

Amount of content is astounding. Learning a lot and truly impressed  on magnitude of high promising research happening around the world.

Day 2  at ICML had great variety of parallel tracks with topics covering Online Learning,  Probabalistic Learning,  Deep Generative Models,  Deep Learning Theory, Supervised Learning,  Latent Feature Models, Reinforcement Learning, Continuous Optimization,  Matrix Factorization,  Metalearning and etc.

Bernhard Schölkopf kicked off the day with talk on Causal Learning (book) and how causal ideas could be exploited for classical machine learning problems.

Deep Generative Models

Lots of interest in this area (no surprise).  Here are what few memorable talks were about (no links  to papers as they are easy to find using your fav search engine ;)… maybe I will add those later).