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Daria Cherniuk

2 accepted papers

2024

Quantization of Large Language Models with an Overdetermined Basis

UAI 2024poster

In this paper, we introduce an algorithm for data quantization based on the principles of Kashin representation. This approach hinges on decomposing any given vector, matrix, or tensor into two factors. The first factor maintains a small infinity norm, while the second exhibits a similarly constrain…

Cited by 1SourcePDFScholar
2022

Survey on Efficient Training of Large Neural Networks

IJCAI 2022poster

Modern Deep Neural Networks (DNNs) require significant memory to store weight, activations, and other intermediate tensors during training. Hence, many models don’t fit one GPU device or can be trained using only a small per-GPU batch size. This survey provides a systematic overview of the approache…