23 citations · 56 across the 12 of their papers we have counts for
13 papers
Robust Yield Curve Estimation for Mortgage Bonds Using Neural Networks
Sina Molavipour, Alireza M. Javid, Cassie Ye +2
Robust yield curve estimation is crucial in fixed-income markets for accurate instrument pricing, effective risk management, and informed trading strategies. Traditional approaches…
Neural Greedy Pursuit for Feature Selection
Sandipan Das, Alireza M. Javid, Prakash Borpatra Gohain +2
We propose a greedy algorithm to select important features among input features for a non-linear prediction problem. The features are selected one by one sequentially, in a…
Use of Deterministic Transforms to Design Weight Matrices of a Neural Network
Pol Grau Jurado, Xinyue Liang, Alireza M. Javid +1
Self size-estimating feedforward network (SSFN) is a feedforward multilayer network. For the existing SSFN, a part of each weight matrix is trained using a layer-wise convex optimi…
Statistical model-based evaluation of neural networks
Sandipan Das, Prakash B. Gohain, Alireza M. Javid +2
Using a statistical model-based data generation, we develop an experimental setup for the evaluation of neural networks (NNs). The setup helps to benchmark a set of NNs vis-a-vis m…
A ReLU Dense Layer to Improve the Performance of Neural Networks
Alireza M. Javid, Sandipan Das, Mikael Skoglund +1
We propose ReDense as a simple and low complexity way to improve the performance of trained neural networks. We use a combination of random weights and rectified linear unit (ReLU)…
A Low Complexity Decentralized Neural Net with Centralized Equivalence using Layer-wise Learning
Xinyue Liang, Alireza M. Javid, Mikael Skoglund +1
We design a low complexity decentralized learning algorithm to train a recently proposed large neural network in distributed processing nodes (workers). We assume the communication…
Predictive Analysis of COVID-19 Time-series Data from Johns Hopkins University
Alireza M. Javid, Xinyue Liang, Arun Venkitaraman +1
We provide a predictive analysis of the spread of COVID-19, also known as SARS-CoV-2, using the dataset made publicly available online by the Johns Hopkins University. Our main obj…
Asynchronous Decentralized Learning of a Neural Network
Xinyue Liang, Alireza M. Javid, Mikael Skoglund +1
In this work, we exploit an asynchronous computing framework namely ARock to learn a deep neural network called self-size estimating feedforward neural network (SSFN) in a decentra…
High-dimensional Neural Feature Design for Layer-wise Reduction of Training Cost
Alireza M. Javid, Arun Venkitaraman, Mikael Skoglund +1
We design a ReLU-based multilayer neural network by mapping the feature vectors to a higher dimensional space in every layer. We design the weight matrices in every layer to ensure…
SSFN -- Self Size-estimating Feed-forward Network with Low Complexity, Limited Need for Human Intervention, and Consistent Behaviour across Trials
Saikat Chatterjee, Alireza M. Javid, Mostafa Sadeghi +4
We design a self size-estimating feed-forward network (SSFN) using a joint optimization approach for estimation of number of layers, number of nodes and learning of weight matrices…
R3Net: Random Weights, Rectifier Linear Units and Robustness for Artificial Neural Network
Arun Venkitaraman, Alireza M. Javid, Saikat Chatterjee
We consider a neural network architecture with randomized features, a sign-splitter, followed by rectified linear units (ReLU). We prove that our architecture exhibits robustness t…
Progressive Learning for Systematic Design of Large Neural Networks
Saikat Chatterjee, Alireza M. Javid, Mostafa Sadeghi +2
We develop an algorithm for systematic design of a large artificial neural network using a progression property. We find that some non-linear functions, such as the rectifier linea…
Analysis of Network Coding in a Slotted ALOHA-based Two-Way Relay Network
Alireza Mahdavi Javid, Mehdi Setayesh, Farzaneh Farhadi +1
This paper deals with a two-way relay network (TWRN) based on a slotted ALOHA protocol which utilizes network coding to exchange the packets. We proposed an analytical approach to…