96 citations · 109 across the 4 of their papers we have counts for
10 papers
A Concern Analysis of FOMC Statements Comparing The Great Recession and The COVID-19 Pandemic
Luis Felipe Gutiérrez, Sima Siami-Namini, Neda Tavakoli +1
It is important and informative to compare and contrast major economic crises in order to confront novel and unknown cases such as the COVID-19 pandemic. The 2006 Great Recession a…
Fast Fourier Transformation for Optimizing Convolutional Neural Networks in Object Recognition
Varsha Nair, Moitrayee Chatterjee, Neda Tavakoli +2
This paper proposes to use Fast Fourier Transformation-based U-Net (a refined fully convolutional networks) and perform image convolution in neural networks. Leveraging the Fast Fo…
Clustering Time Series Data through Autoencoder-based Deep Learning Models
Neda Tavakoli, Sima Siami-Namini, Mahdi Adl Khanghah +2
Machine learning and in particular deep learning algorithms are the emerging approaches to data analysis. These techniques have transformed traditional data mining-based analysis r…
Locality Sensitive Hashing-based Sequence Alignment Using Deep Bidirectional LSTM Models
Neda Tavakoli
Bidirectional Long Short-Term Memory (LSTM) is a special kind of Recurrent Neural Network (RNN) architecture which is designed to model sequences and their long-range dependencies…
A Comparative Analysis of Forecasting Financial Time Series Using ARIMA, LSTM, and BiLSTM
Sima Siami-Namini, Neda Tavakoli, Akbar Siami Namin
Machine and deep learning-based algorithms are the emerging approaches in addressing prediction problems in time series. These techniques have been shown to produce more accurate r…
On Computing Average Common Substring Over Run Length Encoded Sequences
Sahar Hooshmand, Neda Tavakoli, Paniz Abedin +1
The Average Common Substring (ACS) is a popular alignment-free distance measure for phylogeny reconstruction. The ACS can be computed in O(n) space and time, where n=x+y is the inp…