Zobrazeno 1 - 10
of 12 785
pro vyhledávání: '"Miklos, P."'
Autor:
Nyáry, Anna, Balogh, Zoltán, Sánta, Botond, Lázár, György, Olalla, Nadia Jimenez, Leuthold, Juerg, Csontos, Miklós, Halbritter, András
Reproducibility, endurance, driftless data retention, and fine resolution of the programmable conductance weights are key technological requirements against memristive artificial synapses in neural network applications. However, the inherent fluctuat
Externí odkaz:
http://arxiv.org/abs/2412.16080
Autor:
Rasonyi, Miklos
We present a Fourier-analytic method for estimating convergence rates in total variation distance in terms of various metrics related to weak convergence. Applications are provided in the areas of Malliavin calculus, normal approximation and stochast
Externí odkaz:
http://arxiv.org/abs/2412.04013
Autor:
Rácz, Miklós Z., Zhang, Jifan
We study the problem of learning latent community structure from multiple correlated networks, focusing on edge-correlated stochastic block models with two balanced communities. Recent work of Gaudio, R\'acz, and Sridhar (COLT 2022) determined the pr
Externí odkaz:
http://arxiv.org/abs/2412.02796
Autor:
Chai, Shuwen, Rácz, Miklós Z.
We study learning problems on correlated stochastic block models with two balanced communities. Our main result gives the first efficient algorithm for graph matching in this setting. In the most interesting regime where the average degree is logarit
Externí odkaz:
http://arxiv.org/abs/2412.02661
Autor:
Chau, Huy N., Rasonyi, Miklos
In this paper, a new approach for solving the problems of pricing and hedging derivatives is introduced in a general frictionless market setting. The method is applicable even in cases where an equivalent local martingale measure fails to exist. Our
Externí odkaz:
http://arxiv.org/abs/2411.19206
We present a dichotomy theorem on the parameterized complexity of the 3-uniform hypergraphicality problem. Given $0
Externí odkaz:
http://arxiv.org/abs/2411.19049
Autor:
Zhang, Yunuo, Luo, Baiting, Mukhopadhyay, Ayan, Stojcsics, Daniel, Elenius, Daniel, Roy, Anirban, Jha, Susmit, Maroti, Miklos, Koutsoukos, Xenofon, Karsai, Gabor, Dubey, Abhishek
Efficient path optimization for drones in search and rescue operations faces challenges, including limited visibility, time constraints, and complex information gathering in urban environments. We present a comprehensive approach to optimize UAV-base
Externí odkaz:
http://arxiv.org/abs/2411.12967
Autor:
Egri-Nagy, Attila, Hoffmann, Miklós
Morphisms, structure preserving maps, are everywhere in Mathematics as useful tools for thinking and problem solving, or as objects to study. Here, we argue that the idea of operations being compatible across two domains goes beyond its mathematical
Externí odkaz:
http://arxiv.org/abs/2411.06806
Autor:
Arad, Itai, Santha, Miklos
We introduce $k$-local quasi-quantum states: a superset of the regular quantum states, defined by relaxing the positivity constraint. We show that a $k$-local quasi-quantum state on $n$ qubits can be 1-1 mapped to a distribution of assignments over $
Externí odkaz:
http://arxiv.org/abs/2410.13549
Autor:
Valli, Angelo, Moca, Cătălin Paşcu, Werner, Miklós Antal, Kormos, Márton, Krajnik, Žiga, Prosen, Tomaž, Zaránd, Gergely
We propose a numerical method to efficiently compute quantum generating functions (QGF) for a wide class of observables in one-dimensional quantum systems at high temperature. We obtain high-accuracy estimates for the cumulants and reconstruct full c
Externí odkaz:
http://arxiv.org/abs/2409.14442