Zobrazeno 1 - 10
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pro vyhledávání: '"Karimi, Mohammad"'
This work considers the problem of sampling from a probability distribution known up to a normalization constant while satisfying a set of statistical constraints specified by the expected values of general nonlinear functions. This problem finds app
Externí odkaz:
http://arxiv.org/abs/2411.00568
Autor:
Khiarak, Jalil Nourmohammadi, Ahmadi, Ammar, Saeed, Taher Ak-bari, Asgari-Chenaghlu, Meysam, Atabay, Toğrul, Karimi, Mohammad Reza Baghban, Ceferli, Ismail, Hasanvand, Farzad, Mousavi, Seyed Mahboub, Noshad, Morteza
This paper introduces a pioneering English-Azerbaijani (Arabic Script) parallel corpus, designed to bridge the technological gap in language learning and machine translation (MT) for under-resourced languages. Consisting of 548,000 parallel sentences
Externí odkaz:
http://arxiv.org/abs/2407.05189
Autor:
Karimi, Mohammad
Nonlinear optics represents a significant area of research and technology concerned with the modification of material optical properties using light. The interaction between light and such materials gives rise to a multitude of nonlinear optical effe
Externí odkaz:
http://hdl.handle.net/10393/45660
Many modern machine learning applications - from online principal component analysis to covariance matrix identification and dictionary learning - can be formulated as minimization problems on Riemannian manifolds, and are typically solved with a Rie
Externí odkaz:
http://arxiv.org/abs/2311.02374
Autor:
Chalaki, Mahdi Abdollah, Maroufi, Daniyal, Robati, Mahdi, Karimi, Mohammad Javad, Sadighi, Ali
Despite the recent success in data-driven fault diagnosis of rotating machines, there are still remaining challenges in this field. Among the issues to be addressed, is the lack of information about variety of faults the system may encounter in the f
Externí odkaz:
http://arxiv.org/abs/2309.12765
Autor:
Shirvan, Ali Parandeh1, Karimi, Mohammad1, Afshari-Safavi, Alireza2, Taghavi, Mohammad Reza3, Mollazadeh, Samaneh4, Amani, Amir4,5, Nazari, Ali6 a.nazari@nkums.ac.ir
Publikováno v:
Iranian Journal of Psychiatry & Behavioral Sciences / Progress in Psychiatry & Behavioral Sciences. Sep2024, Vol. 18 Issue 3, p1-6. 6p.
We propose a principled way to define Gaussian process priors on various sets of unweighted graphs: directed or undirected, with or without loops. We endow each of these sets with a geometric structure, inducing the notions of closeness and symmetrie
Externí odkaz:
http://arxiv.org/abs/2211.01689
Non-convex sampling is a key challenge in machine learning, central to non-convex optimization in deep learning as well as to approximate probabilistic inference. Despite its significance, theoretically there remain many important challenges: Existin
Externí odkaz:
http://arxiv.org/abs/2210.13867
This paper proposes a self-explainable Deep Learning (SE-DL) system for an image classification problem that performs self-error detection. The self-error detection is key to improving the DL system's safe operation, especially in safety-critical app
Externí odkaz:
http://arxiv.org/abs/2210.08210
We examine a wide class of stochastic approximation algorithms for solving (stochastic) nonlinear problems on Riemannian manifolds. Such algorithms arise naturally in the study of Riemannian optimization, game theory and optimal transport, but their
Externí odkaz:
http://arxiv.org/abs/2206.06795