2 citations · 2 across the 8 of their papers we have counts for
11 papers
Convergence of Kikuchi matrices to -independent and -Gaussian limits
Afonso S. Bandeira, Dmitriy Kunisky, Petar Nizić-Nikolac +2
Kikuchi matrices are a family of structured matrices that were introduced to study problems involving tensors and hypergraphs. We show that, as the ambient dimension grows, dense r…
Matrix Concentration and Equivalent Operators on Fock Spaces
Afonso S. Bandeira, Dmitriy Kunisky, Petar Nizić-Nikolac +2
We develop a method for proving matrix concentration inequalities by identifying random matrices with associated deterministic operators acting on suitable Fock spaces and controll…
The Hypergraph Moore Bound
Afonso S. Bandeira, Dmitriy Kunisky, Petar Nizić-Nikolac +2
The hypergraph Moore bound conjectured by Feige (2008) controls the size of the smallest even cover in a -uniform hypergraph in terms of the average density of hyperedges. An ev…
Norm Bounds for Sparse Random Tensors and Spectral Gap of Random Hypergraphs
Kevin Lucca, Lucas Pesenti
Friedman and Wigderson (1995) introduced a notion of second eigenvalue for hypergraphs that generalizes the second eigenvalue of the adjacency matrix of a graph. We show that -u…
Universality of first-order methods on random and deterministic matrices
Nicola Gorini, Chris Jones, Dmitriy Kunisky +1
General first-order methods (GFOM) are a flexible class of iterative algorithms which update a state vector by matrix-vector multiplications and entrywise nonlinearities. A long li…
Agnostic learning in (almost) optimal time via Gaussian surface area
Lucas Pesenti, Lucas Slot, Manuel Wiedmer
The complexity of learning a concept class under Gaussian marginals in the difficult agnostic model is closely related to its -approximability by low-degree polynomials. For a…
Fourier Analysis of Iterative Algorithms
Chris Jones, Lucas Pesenti
We study a general class of nonlinear iterative algorithms which includes power iteration, belief propagation and approximate message passing, and many forms of gradient descent. W…
New SDP Roundings and Certifiable Approximation for Cubic Optimization
Jun-Ting Hsieh, Pravesh K. Kothari, Lucas Pesenti +1
We give new rounding schemes for SDP relaxations for the problems of maximizing cubic polynomials over the unit sphere and the -dimensional hypercube. In both cases, the resulti…
Discrepancy Minimization via Regularization
Lucas Pesenti, Adrian Vladu
We introduce a new algorithmic framework for discrepancy minimization based on regularization. We demonstrate how varying the regularizer allows us to re-interpret several breakthr…
Quantum zero point electromagnetic energy difference between the superconducting and the normal phase in a HTc superconducting metal bulk sample
Annalisa Allocca, Saverio Avino, Sergio Balestrieri +31
We provide a novel methodological approach to the estimate of the change of the Quantum Vacuum electromagnetic energy density in a High critical Temperature superconducting metal b…
Casimir energy for N superconducting cavities: a model for the YBCO (BSCCO)
A. Allocca, S. Avino, S. Balestrieri +31
In this paper we study the Casimir energy of a sample made by N cavities, with N >> 1, across the transition from the metallic to the superconducting phase of the constituting plat…