Search Results for author: Jared Miller

Found 7 papers, 1 papers with code

Frequency-Domain Identification of Discrete-Time Systems using Sum-of-Rational Optimization

no code implementations25 Dec 2023 Mohamed Abdalmoaty, Jared Miller, Mingzhou Yin, Roy S. Smith

We propose a computationally tractable method for the identification of stable canonical discrete-time rational transfer function models, using frequency domain data.

Peak Estimation and Recovery with Occupation Measures

no code implementations14 Sep 2020 Jared Miller, Didier Henrion, Mario Sznaier

Peak Estimation aims to find the maximum value of a state function achieved by a dynamical system.

Systems and Control Systems and Control Algebraic Geometry Dynamical Systems 37M99

Mediating Ribosomal Competition by Splitting Pools

1 code implementation1 Sep 2020 Jared Miller, M. Ali Al-Radhawi, Eduardo D. Sontag

The competition for resources between host and circuit genes can be ameliorated by splitting the ribosome pool by use of orthogonal ribosomes, where the circuit genes are exclusively translated by mutated ribosomes.

Translation

Solving Interpretable Kernel Dimensionality Reduction

no code implementations NeurIPS 2019 Chieh Wu, Jared Miller, Yale Chang, Mario Sznaier, Jennifer Dy

While KDR methods can be easily solved by keeping the most dominant eigenvectors of the kernel matrix, its features are no longer easy to interpret.

Clustering Dimensionality Reduction

Solving Interpretable Kernel Dimension Reduction

no code implementations6 Sep 2019 Chieh Wu, Jared Miller, Yale Chang, Mario Sznaier, Jennifer Dy

While KDR methods can be easily solved by keeping the most dominant eigenvectors of the kernel matrix, its features are no longer easy to interpret.

Clustering Dimensionality Reduction

Spectral Non-Convex Optimization for Dimension Reduction with Hilbert-Schmidt Independence Criterion

no code implementations6 Sep 2019 Chieh Wu, Jared Miller, Yale Chang, Mario Sznaier, Jennifer Dy

The Hilbert Schmidt Independence Criterion (HSIC) is a kernel dependence measure that has applications in various aspects of machine learning.

Clustering Dimensionality Reduction

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