Deep Learning
New computational algorithms make it possible to build neural networks with many input nodes and many layers, and distinguish "deep learning" of these networks from previous work on artificial neural nets.
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Transformers to SSMs: Distilling Quadratic Knowledge to Subquadratic Models
Neural Information Processing Systems
Authors contributed equally to this work.
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Boosting Learning for LDPC Codes to Improve the Error-Floor Performance
Neural Information Processing Systems
These works assume an arbitrary neural network with no prior knowledge of decoding algorithms, and accordingly, face the challenge of learning a decoding algorithm.
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