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Stock AI

Using Natural Language Processing and Reinforcement Learning to predict stock prices from google news feed using techniques from many state of the art papers

Transformer mock data test run

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Currently implementing

Longformer (Sliding window attention to scale compute linearly with sequence length)

https://arxiv.org/pdf/2004.05150.pdf

Big Bird (Window attention combined with random attention)

https://arxiv.org/pdf/2007.14062.pdf

Transformer XL (Using cached query and keys for extra long sequences)

https://arxiv.org/pdf/1901.02860.pdf

Papers implemented in this algorithm

Seed RL (Scalable and Efficient Deep RL with Centralized Inference):

https://arxiv.org/abs/1910.06591

R2D2 (Rainbow Deep Q Network with LSTM):

https://openreview.net/pdf?id=r1lyTjAqYX

PCGrad (Gradient Surgery for Multi Task Learning):

https://arxiv.org/pdf/2001.06782.pdf

Block Recurrent Transformer (Variant of Transformer with Recurrent Attention):

https://arxiv.org/abs/2203.07852

Implicit Quantile Network (Distributed RL for accelerated learning and risk sensitive policies):

https://arxiv.org/abs/1806.06923

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