By Vaishnavh Nagarajan and Jeffrey Li
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Fig 1: A formal relationship between interpretability and complexity. Going from left to right, we consider increasingly complex functions. As...
We propose a method for using offline data to build a prediction model that only requires access to the available subset of confounders at prediction time.
Welcome to our April 2021 monthly digest where you can catch up with any AIhub stories you may have missed, get the low-down on recent events, and much more.
Our method learns a task in a fixed, simulated environment and quickly adapts to new environments (e.g. the real world) solely from online interaction during deployment.
By Nicklas Hansen and Xiaol...
What’s hot on arXiv? Here are the most tweeted papers that were uploaded onto arXiv during March 2021.
Results are powered by Arxiv Sanity Preserver....
Welcome to our March 2021 monthly digest where you can catch up with any AIhub stories you may have missed, get the low-down on recent conferences, and much more.
We present a probabilistic perspective that generalizes and improves upon federated optimization and enables a new class of efficient federated learning algorithms.
At AAAI 2021, Daphne Koller gave a plenary talk about digital learning. In this presentation she discussed the different motivations for online learning, what we know about effective learning, digital...
To celebrate International Women's Day, we take a look back over the past year of AIhub content and highlight some of our favourite articles, interviews, podcasts and videos, by, or featuring, women i...