Zobrazeno 1 - 10
of 546
pro vyhledávání: '"Măcriş, A."'
The $k$-QSAT problem is a quantum analog of the famous $k$-SAT constraint satisfaction problem. We must determine the zero energy ground states of a Hamiltonian of $N$ qubits consisting of a sum of $M$ random $k$-local rank-one projectors. It is know
Externí odkaz:
http://arxiv.org/abs/2404.18447
Autor:
Pourkamali, Farzad, Macris, Nicolas
We consider estimating a matrix from noisy observations coming from an arbitrary additive bi-rotational invariant perturbation. We propose an estimator which is optimal among the class of rectangular rotational invariant estimators and can be applied
Externí odkaz:
http://arxiv.org/abs/2403.04615
Autor:
Pryor, Mitchell, Navarro, Alex, Panthi, Janak, Torres, Kevin, Tebben, Mary, Meza, Daniel, Horan, Caleb, Macris, Alex
Nuclear facilities must routinely survey their infrastructure for radiation contamination. Generally, this is done by trained professionals, wearing personal protective equipment (PPE) that swipe potentially contaminated surfaces and test the wipes u
Externí odkaz:
http://arxiv.org/abs/2402.15008
We investigate the test risk of continuous-time stochastic gradient flow dynamics in learning theory. Using a path integral formulation we provide, in the regime of a small learning rate, a general formula for computing the difference between test ri
Externí odkaz:
http://arxiv.org/abs/2402.07626
Autor:
Pourkamali, Farzad, Macris, Nicolas
We consider a statistical model for matrix factorization in a regime where the rank of the two hidden matrix factors grows linearly with their dimension and their product is corrupted by additive noise. Despite various approaches, statistical and alg
Externí odkaz:
http://arxiv.org/abs/2306.04592
The inference of a large symmetric signal-matrix $\mathbf{S} \in \mathbb{R}^{N\times N}$ corrupted by additive Gaussian noise, is considered for two regimes of growth of the rank $M$ as a function of $N$. For sub-linear ranks $M=\Theta(N^\alpha)$ wit
Externí odkaz:
http://arxiv.org/abs/2306.01412
Autor:
Pourkamali, Farzad, Macris, Nicolas
We propose a rectangular rotational invariant estimator to recover a real matrix from noisy matrix observations coming from an arbitrary additive rotational invariant perturbation, in the large dimension limit. Using the Bayes-optimality of this esti
Externí odkaz:
http://arxiv.org/abs/2304.12264
Autor:
Bodin, Antoine, Macris, Nicolas
In this work, we present a new approach to analyze the gradient flow for a positive semi-definite matrix denoising problem in an extensive-rank and high-dimensional regime. We use recent linear pencil techniques of random matrix theory to derive fixe
Externí odkaz:
http://arxiv.org/abs/2303.09474
Autor:
Bodin, Antoine, Macris, Nicolas
A recent line of work has shown remarkable behaviors of the generalization error curves in simple learning models. Even the least-squares regression has shown atypical features such as the model-wise double descent, and further works have observed tr
Externí odkaz:
http://arxiv.org/abs/2212.06757
Autor:
Young, Edward D., Macris, Catherine A., Tang, Haolan, Hogan, Arielle A., Shollenberger, Quinn R.
We use new experiments and a theoretical analysis of the results to show that the isotopic fractionation associated with laser-heating aerodynamic levitation experiments is consistent with the velocity of flowing gas as the primary control on the fra
Externí odkaz:
http://arxiv.org/abs/2204.13020