3 citations · 3 across the 1 of their papers we have counts for
5 papers
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 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…
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…