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Found 4 papers, 3 papers with code
Retentive Network: A Successor to Transformer for Large Language Models
In this work, we propose Retentive Network (RetNet) as a foundation architecture for large language models, simultaneously achieving training parallelism, low-cost inference, and good performance.
A Neural Corpus Indexer for Document Retrieval
To this end, we propose Neural Corpus Indexer (NCI), a sequence-to-sequence network that generates relevant document identifiers directly for a designated query.
Manifold Fitting under Unbounded Noise
Numerical simulations are provided to validate our theoretical findings and demonstrate the advantages of our method over other relevant manifold fitting methods.
Minimal Sample Subspace Learning: Theory and Algorithms
Subspace segmentation or subspace learning is a challenging and complicated task in machine learning.
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