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  /  Project   /  Blog: Microsoft Build and Google I/O Pledge Better AI; ICLR 2019 Announces Best Papers

Blog: Microsoft Build and Google I/O Pledge Better AI; ICLR 2019 Announces Best Papers



I/O 2019 | Your Data Stays on Your Phone: Google Promises a Better AI
The success of artificial intelligence is built on large corpuses of centralized data collection, but rising concerns over user privacy and data misuse have left many people wary of fully embracing AI on their mobile devices. Google wants to change that.
(Synced)




Papers from ICLR 2019
MILA, Microsoft, and MIT Share Best Paper Honours
Best Paper of ICLR 2019 | Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks
Best Paper of ICLR 2019 | The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks
Tsinghua, Google and ByteDance Propose Neural Networks for Inductive Learning & Logic Reasoning

Technology

MixMatch: A Holistic Approach to Semi-Supervised Learning
In this work, researchers unify the current dominant approaches for semi-supervised learning to produce a new algorithm, MixMatch, that works by guessing low-entropy labels for data-augmented unlabeled examples and mixing labeled and unlabeled data using MixUp.
(Ian Goodfellow & Google Research)


Few-Shot Unsupervised Image-to-Image Translation
Researchers seek a few-shot, unsupervised image-to-image translation algorithm that works on previously unseen target classes that are specified, at test time, only by a few example images. Their model achieves this few-shot generation capability by coupling an adversarial training scheme with a novel network design. 
(NVIDIA & Cornell University & Aalto University)


Adversarial Examples Are Not Bugs, They Are Features
Researchers demonstrate that adversarial examples can be directly attributed to the presence of non-robust features: features derived from patterns in the data distribution that are highly predictive, yet brittle and incomprehensible to humans.
(MIT)

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An Introductory Guide to Computer Vision
In this guide, you’ll learn about the basic concept of computer vision and how it’s used in the real world. It’s a simple examination of a complex problem for anybody who has ever heard of computer vision but isn’t quite sure what it’s all about and how it’s applied.
(Tryolabs)


‘Abandon US’ Petition Protests AI Conference Visa Denials
A French-based research scientist has collected almost 300 signatures on an online petition calling for organizers of major computer science conferences such as SIGGRAPH, NeurIPS, ICML, CVPR, etc. to exclude the US as a host. 
(Synced)

Global AI Events

May 23–24: Deep Learning Summit in Boston, United States

May 27–28: SingularityU Nordic Summit in Helsinki, Finland

June 4–7: Amazon re:MARS in Las Vegas, United States

June 15–21: Computer Vision and Pattern Recognition in Long Beach, United States

June 10–12:World Conference on Robotics and AI (WCRAI) in Osaka, Japan

Global AI Opportunities

Research Scientist, Google Brain Toronto

OpenAI is looking for software engineers and deep learning

DeepMind is Recruiting

DeepMind Scholarship: Access to Science

Postdoctoral Researcher (AI) — Self-Supervised Learning

LANDING AI is recruiting



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Source: Artificial Intelligence on Medium

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