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Gary Miller

2 accepted papers

2024

Metric Transforms and Low Rank Representations of Kernels for Fast Attention

NeurIPS 2024spotlight

We introduce a new linear-algebraic tool based on group representation theory, and use it to address three key problems in machine learning. 1. Past researchers have proposed fast attention algorithms for LLMs by approximating or replace softmax attention with other functions, such as low-degree po…

Cited by 1SourcePDFScholar
2016

Simple and Scalable Constrained Clustering: a Generalized Spectral Method

AISTATS 2016poster

We present a simple spectral approach to the well-studied constrained clustering problem. It captures constrained clustering as a generalized eigenvalue problem with graph Laplacians. The algorithm works in nearly-linear time and provides concrete guarantees for the quality of the clusters, at least…

Cited by 64SourcePDFScholar