9 citations · 27 across the 9 of their papers we have counts for
10 papers
Free Decompression with Algebraic Spectral Curves
Siavash Ameli, Chris van der Heide, Liam Hodgkinson +1
Tools from random matrix theory have become central to deep learning theory, using spectral information to provide mechanisms for modeling generalization, robustness, scaling, and…
Spectral Estimation with Free Decompression
Siavash Ameli, Chris van der Heide, Liam Hodgkinson +1
Computing eigenvalues of very large matrices is a critical task in many machine learning applications, including the evaluation of log-determinants, the trace of matrix functions,…
Determinant Estimation under Memory Constraints and Neural Scaling Laws
Siavash Ameli, Chris van der Heide, Liam Hodgkinson +2
Calculating or accurately estimating log-determinants of large positive definite matrices is of fundamental importance in many machine learning tasks. While its cubic computational…
A Statistical Framework for Ranking LLM-Based Chatbots
Siavash Ameli, Siyuan Zhuang, Ion Stoica +1
Large language models (LLMs) have transformed natural language processing, with frameworks like Chatbot Arena providing pioneering platforms for evaluating these models. By facilit…
Optimizing the cloud? Don't train models. Build oracles!
Tiemo Bang, Conor Power, Siavash Ameli +2
We propose cloud oracles, an alternative to machine learning for online optimization of cloud configurations. Our cloud oracle approach guarantees complete accuracy and explainabil…
Development of an Efficient and Flexible Pipeline for Lagrangian Coherent Structure Computation
Siavash Ameli, Yogin Desai, Shawn C. Shadden
The computation of Lagrangian coherent structures (LCS) has become a standard tool for the analysis of advective transport in unsteady flow applications. LCS identification is prim…
A Singular Woodbury and Pseudo-Determinant Matrix Identities and Application to Gaussian Process Regression
Siavash Ameli, Shawn C. Shadden
We study a matrix that arises from a singular form of the Woodbury matrix identity. We present generalized inverse and pseudo-determinant identities for this matrix, which have dir…
Noise Estimation in Gaussian Process Regression
Siavash Ameli, Shawn C. Shadden
We develop a computational procedure to estimate the covariance hyperparameters for semiparametric Gaussian process regression models with additive noise. Namely, the presented met…
Interpolating Log-Determinant and Trace of the Powers of Matrix
Siavash Ameli, Shawn C. Shadden
We develop heuristic interpolation methods for the functions and $t \mapsto \operatorname{trace}\left( (\mathbf{A} +…
A transport method for restoring incomplete ocean current measurements
Siavash Ameli, Shawn C. Shadden
Remote sensing of oceanographic data often yields incomplete coverage of the measurement domain. This can limit interpretability of the data and identification of coherent features…