16 citations · 42 across the 10 of their papers we have counts for
10 papers
Hamiltonian Adaptive Importance Sampling
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. In IS, the samples are simulated…
Deep Learning Applications for Lung Cancer Diagnosis: A systematic review
Hesamoddin Hosseini, Reza Monsefi, Shabnam Shadroo
Lung cancer has been one of the most prevalent disease in recent years. According to the research of this field, more than 200,000 cases are identified each year in the US. Uncontr…
Vector Transport Free Riemannian LBFGS for Optimization on Symmetric Positive Definite Matrix Manifolds
Reza Godaz, Benyamin Ghojogh, Reshad Hosseini +3
This work concentrates on optimization on Riemannian manifolds. The Limited-memory Broyden-Fletcher-Goldfarb-Shanno (LBFGS) algorithm is a commonly used quasi-Newton method for num…
A Framework to Enhance Generalization of Deep Metric Learning methods using General Discriminative Feature Learning and Class Adversarial Neural Networks
Karrar Al-Kaabi, Reza Monsefi, Davood Zabihzadeh
Metric learning algorithms aim to learn a distance function that brings the semantically similar data items together and keeps dissimilar ones at a distance. The traditional Mahala…
Accurate and fast matrix factorization for low-rank learning
Reza Godaz, Reza Monsefi, Faezeh Toutounian +1
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. By using the co…
Neural Generalization of Multiple Kernel Learning
Ahmad Navid Ghanizadeh, Kamaledin Ghiasi-Shirazi, Reza Monsefi +1
Multiple Kernel Learning is a conventional way to learn the kernel function in kernel-based methods. MKL algorithms enhance the performance of kernel methods. However, these method…
RELF: Robust Regression Extended with Ensemble Loss Function
Hamideh Hajiabadi, Reza Monsefi, Hadi Sadoghi Yazdi
Ensemble techniques are powerful approaches that combine several weak learners to build a stronger one. As a meta-learning framework, ensemble techniques can easily be applied to m…
Large Scale Local Online Similarity/Distance Learning Framework based on Passive/Aggressive
Baida Hamdan, Davood Zabihzadeh, Monsefi Reza
Similarity/Distance measures play a key role in many machine learning, pattern recognition, and data mining algorithms, which leads to the emergence of metric learning field. Many…
TRLF: An Effective Semi-fragile Watermarking Method for Tamper Detection and Recovery based on LWT and FNN
Behrouz Bolourian Haghighi, Amir Hossein Taherinia, Reza Monsefi
This paper proposes a novel method for tamper detection and recovery using semi-fragile data hiding, based on Lifting Wavelet Transform (LWT) and Feed-Forward Neural Network (FNN).…
On Extending Neural Networks with Loss Ensembles for Text Classification
Hamideh Hajiabadi, Diego Molla-Aliod, Reza Monsefi
Ensemble techniques are powerful approaches that combine several weak learners to build a stronger one. As a meta learning framework, ensemble techniques can easily be applied to m…