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Researcher profile

Jose Israel Rodriguez

Jose Israel Rodriguez contributes to research discovery and scholarly infrastructure.

ResearcherAffiliation not importedOpen to collaborate
math.AGmath.ATMachine Learningmath.NAmath.OCmath.STNumerical AnalysisStatistics Theory

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Published work

9 published item(s)

preprint2026arXiv

Minimal Filling Architectures of Polynomial Neural Networks: Counterexamples, Frontier Search, and Defects

We provide a counterexample to the minimal unimodal conjecture for polynomial neural networks (PNNs) with power activation functions. Fixing the input and output widths, the conjecture states that any minimal filling architecture has unimodal widths for the hidden layers. We found a counterexample via a frontier search and certified it using recursive dimension bounds and symbolic computation. Notably, several subarchitectures of this example exhibit large defect, in contrast with the predominantly small-defect behavior observed in prior examples.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

$u$-generation: solving systems of polynomials equation-by-equation

We develop a new method that improves the efficiency of equation-by-equation algorithms for solving polynomial systems. Our method is based on a novel geometric construction, and reduces the total number of homotopy paths that must be numerically continued. These improvements may be applied to the basic algorithms of numerical algebraic geometry in the settings of both projective and multiprojective varieties. Our computational experiments demonstrate significant savings obtained on several benchmark systems. We also present an extended case study on maximum likelihood estimation for rank-constrained symmetric $n\times n$ matrices, in which multiprojective $u$-generation allows us to complete the list of ML degrees for $n\le 6.$

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Logarithmic cotangent bundles, Chern-Mather classes, and the Huh-Sturmfels Involution conjecture

Using compactifications in the logarithmic cotangent bundle, we obtain a formula for the Chern classes of the pushforward of Lagrangian cycles under an open embedding with normal crossing complement. This generalizes earlier results of Aluffi and Wu-Zhou. The first application of our formula is a geometric description of Chern-Mather classes of an arbitrary very affine variety, generalizing earlier results of Huh which held under the smooth and schon assumptions. As the second application, we confirm an involution formula relating sectional maximum likelihood (ML) degrees and ML bidegrees, which was conjectured by Huh and Sturmfels in 2013.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

The maximum likelihood degree of sparse polynomial systems

We consider statistical models arising from the common set of solutions to a sparse polynomial system with general coefficients. The maximum likelihood degree counts the number of critical points of the likelihood function restricted to the model. We prove the maximum likelihood degree of a sparse polynomial system is determined by its Newton polytopes and equals the mixed volume of a related Lagrange system of equations.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

A Morse theoretic approach to non-isolated singularities and applications to optimization

Let $X$ be a complex affine variety in $\mathbb{C}^N$, and let $f:\mathbb{C}^N\to \mathbb{C}$ be a polynomial function whose restriction to $X$ is nonconstant. For $g:\mathbb{C}^N \to \mathbb{C}$ a general linear function, we study the limiting behavior of the critical points of the one-parameter family of $f_t: =f-tg$ as $t\to 0$. Our main result gives an expression of this limit in terms of critical sets of the restrictions of $g$ to the singular strata of $(X,f)$. We apply this result in the context of optimization problems. For example, we consider nearest point problems (e.g., Euclidean distance degrees) for affine varieties and a possibly nongeneric data point.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

A numerical toolkit for multiprojective varieties

A numerical description of an algebraic subvariety of projective space is given by a general linear section, called a witness set. For a subvariety of a product of projective spaces (a multiprojective variety), the corresponding numerical description is given by a witness collection, whose structure is more involved. We build on recent work to develop a toolkit for the numerical manipulation of multiprojective varieties that operates on witness collections, and use this toolkit in an algorithm for numerical irreducible decomposition of multiprojective varieties. The toolkit and decomposition algorithm are illustrated throughout in a series of examples.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Multiregeneration for polynomial system solving

We demonstrate our implementation of a continuation method as described in \cite{HR2015} for solving polynomials systems. Given a sequence of (multi)homogeneous polynomials, the software "multiregeneration" outputs the respective (multi)degree in a wide range of cases and partial multidegree in all others. We use Python for the file processing, while Bertini is needed for the continuation. Moreover, parallelization options and several strategies for solving structured polynomial systems are available.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

The algebraic matroid of the funtf variety

A finite unit norm tight frame is a collection of $r$ vectors in $\mathbb{R}^n$ that generalizes the notion of orthonormal bases. The affine finite unit norm tight frame variety is the Zariski closure of the set of finite unit norm tight frames. Determining the fiber of a projection of this variety onto a set of coordinates is called the algebraic finite unit norm tight frame completion problem. Our techniques involve the algebraic matroid of an algebraic variety, which encodes the dimensions of fibers of coordinate projections. This work characterizes the bases of the algebraic matroid underlying the variety of finite unit norm tight frames in $\mathbb{R}^3$. Partial results towards similar characterizations for finite unit norm tight frames in $\mathbb{R}^n$ with $n \ge 4$ are also given. We provide a method to bound the degree of the projections based off of combinatorial~data.

0 citations0 reviewsNo code linkedOpen access