ADVANCEMENTS IN MACHINE LEARNING in 2021

Top 4 Important Machine Learning and Deep Learning Papers You Should Read in 2021

These papers help us to keep up to date with the latest advancements in the world of AI.

Prem Kumar
Jan 19 · 7 min read
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Photo by Alfons Morales on Unsplash

“Key research papers in natural language processing, conversational AI, computer vision, reinforcement learning, and AI ethics are published yearly”

Single Headed Attention RNN: Stop Thinking With Your Head

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Source: Arvix (https://arxiv.org/pdf/1911.11423.pdf)
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Source: https://arxiv.org/pdf/1911.11423.pdf

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

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Source: Arvix (https://arxiv.org/abs/1905.11946)

GPT - 3

Image GPT

We find that, just as a large transformer model trained on language can generate coherent text, the same exact model trained on pixel sequences can generate coherent image completions and samples. By establishing a correlation between sample quality and image classification accuracy, we show that our best generative model also contains features competitive with top convolutional nets in the unsupervised setting.

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The input image is processed into a low-resolution 1D sequence. It goes through 2 different pipelines, auto-regressive next pixel prediction or masked pixel prediction. Finally, the learned representations are evaluated accordingly by fine-tuning. Source: ImageGPT paper

In the end

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