26 citations · 50 across the 7 of their papers we have counts for
10 papers
Enhancing Language Learning through Technology: Introducing a New English-Azerbaijani (Arabic Script) Parallel Corpus
Jalil Nourmohammadi Khiarak, Ammar Ahmadi, Taher Ak-bari Saeed +7
This paper introduces a pioneering English-Azerbaijani (Arabic Script) parallel corpus, designed to bridge the technological gap in language learning and machine translation (MT) f…
KartalOl: Transfer learning using deep neural network for iris segmentation and localization: New dataset for iris segmentation
Jalil Nourmohammadi Khiarak, Samaneh Salehi Nasab, Farhang Jaryani +4
Iris segmentation and localization in unconstrained environments is challenging due to long distances, illumination variations, limited user cooperation, and moving subjects. To ad…
Clinical Recommender System: Predicting Medical Specialty Diagnostic Choices with Neural Network Ensembles
Morteza Noshad, Ivana Jankovic, Jonathan H. Chen
The growing demand for key healthcare resources such as clinical expertise and facilities has motivated the emergence of artificial intelligence (AI) based decision support systems…
Learning to Benchmark: Determining Best Achievable Misclassification Error from Training Data
Morteza Noshad, Li Xu, Alfred Hero
We address the problem of learning to benchmark the best achievable classifier performance. In this problem the objective is to establish statistically consistent estimates of the…
Convergence Rates for Empirical Estimation of Binary Classification Bounds
Salimeh Yasaei Sekeh, Morteza Noshad, Kevin R. Moon +1
Bounding the best achievable error probability for binary classification problems is relevant to many applications including machine learning, signal processing, and information th…
Scalable Mutual Information Estimation using Dependence Graphs
Morteza Noshad, Yu Zeng, Alfred O. Hero
The Mutual Information (MI) is an often used measure of dependency between two random variables utilized in information theory, statistics and machine learning. Recently several MI…
Scalable Hash-Based Estimation of Divergence Measures
Morteza Noshad, Alfred O. Hero
We propose a scalable divergence estimation method based on hashing. Consider two continuous random variables and whose densities have bounded support. We consider a partic…
Direct Estimation of Information Divergence Using Nearest Neighbor Ratios
Morteza Noshad, Kevin R. Moon, Salimeh Yasaei Sekeh +1
We propose a direct estimation method for Rényi and f-divergence measures based on a new graph theoretical interpretation. Suppose that we are given two sample sets and , re…
Information Theoretic Structure Learning with Confidence
Kevin R. Moon, Morteza Noshad, Salimeh Yasaei Sekeh +1
Information theoretic measures (e.g. the Kullback Liebler divergence and Shannon mutual information) have been used for exploring possibly nonlinear multivariate dependencies in hi…
Low-Complexity Stochastic Generalized Belief Propagation
Farzin Haddadpour, Mahdi Jafari Siavoshani, Morteza Noshad
The generalized belief propagation (GBP), introduced by Yedidia et al., is an extension of the belief propagation (BP) algorithm, which is widely used in different problems involve…