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Found 5 papers, 5 papers with code
Prompt-prompted Mixture of Experts for Efficient LLM Generation
With the development of transformer-based large language models (LLMs), they have been applied to many fields due to their remarkable utility, but this comes at a considerable computational cost at deployment.
Get More with LESS: Synthesizing Recurrence with KV Cache Compression for Efficient LLM Inference
Many computational factors limit broader deployment of large language models.
A Lightweight Transformer for Faster and Robust EBSD Data Collection
Three dimensional electron back-scattered diffraction (EBSD) microscopy is a critical tool in many applications in materials science, yet its data quality can fluctuate greatly during the arduous collection process, particularly via serial-sectioning.
Deep Unfolded Tensor Robust PCA with Self-supervised Learning
Tensor robust principal component analysis (RPCA), which seeks to separate a low-rank tensor from its sparse corruptions, has been crucial in data science and machine learning where tensor structures are becoming more prevalent.
Fast and Provable Tensor Robust Principal Component Analysis via Scaled Gradient Descent
An increasing number of data science and machine learning problems rely on computation with tensors, which better capture the multi-way relationships and interactions of data than matrices.
