23 citations · 24 across the 4 of their papers we have counts for
6 papers
Recovery Limits for Eigenvector Alignment in HDLSS Spiked Covariance Models
Hubeyb Gurdogan, Alex Shkolnik
In a spiked covariance model, let and be selected sample and population eigenvector matrices. Their alignment matrix is…
A Sharp Signal-to-Noise Threshold for Quasi-Maximum Likelihood Breakpoint Estimation
Hubeyb Gurdogan, Georg Menz
We establish a sharp pathwise signal-to-noise criterion for quasi-maximum-likelihood (QML) estimation of a dominant breakpoint in the second-moment structure of a multivariate time…
Humanity's Last Exam
Long Phan, Alice Gatti, Ziwen Han +1168
Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achi…
The Quadratic Optimization Bias Of Large Covariance Matrices
Hubeyb Gurdogan, Alex Shkolnik
We describe a puzzle involving the interactions between an optimization of a multivariate quadratic function and a "plug-in" estimator of a spiked covariance matrix. When the large…
Multi Anchor Point Shrinkage for the Sample Covariance Matrix (Extended Version)
Hubeyb Gurdogan, Alec Kercheval
Portfolio managers faced with limited sample sizes must use factor models to estimate the covariance matrix of a high-dimensional returns vector. For the simplest one-factor market…
A polynomial invariant for plane curve complements: Krammer polynomials
Mehmet Emin Aktas, Serdar Cellat, Hubeyb Gurdogan
We use the Krammer representation of the braid group in Libgober's invariant and construct a new multivariate polynomial invariant for curve complements: Krammer polynomial. We sho…