no code implementations • 27 Sep 2022 • Ali Mousavi, Reza Monsefi, Víctor Elvira
Importance sampling (IS) is a powerful Monte Carlo (MC) methodology for approximating integrals, for instance in the context of Bayesian inference.
no code implementations • 1 Jan 2022 • Hesamoddin Hosseini, Reza Monsefi, Shabnam Shadroo
This research is superior to other review articles in this field due to the complete review of relevant articles and systematic write up.
1 code implementation • 25 Aug 2021 • Reza Godaz, Benyamin Ghojogh, Reshad Hosseini, Reza Monsefi, Fakhri Karray, Mark Crowley
Riemannian LBFGS (RLBFGS) is an extension of this method to Riemannian manifolds.
1 code implementation • 11 Jun 2021 • Karrar Al-Kaabi, Reza Monsefi, Davood Zabihzadeh
To address this limitation, we propose a framework to enhance the generalization power of existing DML methods in a Zero-Shot Learning (ZSL) setting by general yet discriminative representation learning and employing a class adversarial neural network.
1 code implementation • 21 Apr 2021 • Reza Godaz, Reza Monsefi, Faezeh Toutounian, Reshad Hosseini
In this paper, we tackle two important problems in low-rank learning, which are partial singular value decomposition and numerical rank estimation of huge matrices.
Matrix Factorization / Decomposition Riemannian optimization
no code implementations • 26 Feb 2021 • Ahmad Navid Ghanizadeh, Kamaledin Ghiasi-Shirazi, Reza Monsefi, Mohammadreza Qaraei
By this interpretation, we propose a Neural Generalization of Multiple Kernel Learning (NGMKL), which extends the conventional multiple kernel learning framework to a multi-layer neural network with nonlinear activation functions.
1 code implementation • Knowledge-Based Systems 2019 • Davood Zabihzadeh, Reza Monsefi, Hadi Sadoghi Yazdi
Also, the present work is extended for learning in the feature space induced by an RKHS kernel.
no code implementations • 25 Oct 2018 • Hamideh Hajiabadi, Reza Monsefi, Hadi Sadoghi Yazdi
Ensemble techniques are powerful approaches that combine several weak learners to build a stronger one.
no code implementations • ALTA 2017 • Hamideh Hajiabadi, Diego Molla-Aliod, Reza Monsefi
Ensemble techniques are powerful approaches that combine several weak learners to build a stronger one.