ai, deep-learning, Machine Learning

Thoughts on the BagNet Paper

Some thoughts on the interesting BagNet paper (accepted at ICLR 2019) currently being circulated around the Machine Learning Twitter Community.

Disclaimer: I wasn’t a reviewer of this paper for ICLR. I think it was worthy of acceptance to the c…

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Generalized Language Models

[Updated on 2019-02-14: add ULMFiT and GPT-2.]
[Updated on 2020-02-29: add ALBERT.]
[Updated on 2020-10-25: add RoBERTa.]
[Updated on 2020-12-13: add T5.]
[Updated on 2020-12-30: add GPT-3.]
[Updated on 2021-11-13: add XLNet, BART and ELECTRA; Also up…

ai, finance, Machine Learning, statistics

Uncertainty: a Tutorial

A PDF version of this post can be found here.
Chinese translation by Xiaoyi Yin

Notions of uncertainty are tossed around in conversations around AI safety, risk management, portfolio optimization, scientific measurement, and insurance. Here are a few …

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Object Detection Part 4: Fast Detection Models

In Part 3, we have reviewed models in the R-CNN family. All of them are region-based object detection algorithms. They can achieve high accuracy but could be too slow for certain applications such as autonomous driving. In Part 4, we only focus on fas…

Research

How AI training scales

We’ve discovered that the gradient noise scale, a simple statistical metric, predicts the parallelizability of neural network training on a wide range of tasks. Since complex tasks tend to have noisier gradients, increasingly large batch sizes are like…

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