4 papers
PADRe: A Unifying Polynomial Attention Drop-in Replacement for Efficient Vision Transformer
Pierre-David Letourneau, Manish Kumar Singh, Hsin-Pai Cheng +6
We present Polynomial Attention Drop-in Replacement (PADRe), a novel and unifying framework designed to replace the conventional self-attention mechanism in transformer models. Not…
An Efficient Framework for Global Non-Convex Polynomial Optimization with Algebraic Constraints
Mitchell Tong Harris, Pierre-David Letourneau, Dalton Jones +1
We present an efficient framework for solving algebraically-constrained global non-convex polynomial optimization problems over subsets of the hypercube. We prove the existence of…
A Sparse Fast Chebyshev Transform for High-Dimensional Approximation
Dalton Jones, Pierre-David Letourneau, Matthew J. Morse +1
We present the Fast Chebyshev Transform (FCT), a fast, randomized algorithm to compute a Chebyshev approximation of functions in high-dimensions from the knowledge of the location…
An Efficient Framework for Global Non-Convex Polynomial Optimization over the Hypercube
Pierre-David Letourneau, Dalton Jones, Matthew Morse +1
We present a novel efficient theoretical and numerical framework for solving global non-convex polynomial optimization problems. We analytically demonstrate that such problems can…