6 papers
Finding Optimal Trading History in Reinforcement Learning for Stock Market Trading
Sina Montazeri, Haseebullah Jumakhan, Amir Mirzaeinia
This paper investigates the optimization of temporal windows in Financial Deep Reinforcement Learning (DRL) models using 2D Convolutional Neural Networks (CNNs). We introduce a nov…
Real-time Motion Planning for autonomous vehicles in dynamic environments
Mohammad Dehghani Tezerjani, Dominic Carrillo, Deyuan Qu +3
Recent advancements in self-driving car technologies have enabled them to navigate autonomously through various environments. However, one of the critical challenges in autonomous…
Gradient Reduction Convolutional Neural Network Policy for Financial Deep Reinforcement Learning
Sina Montazeri, Haseebullah Jumakhan, Sonia Abrasiabian +1
Building on our prior explorations of convolutional neural networks (CNNs) for financial data processing, this paper introduces two significant enhancements to refine our CNN model…
Deep Reinforcement Learning Strategies in Finance: Insights into Asset Holding, Trading Behavior, and Purchase Diversity
Alireza Mohammadshafie, Akram Mirzaeinia, Haseebullah Jumakhan +1
Recent deep reinforcement learning (DRL) methods in finance show promising outcomes. However, there is limited research examining the behavior of these DRL algorithms. This paper a…
Analyzing Gender Polarity in Short Social Media Texts with BERT: The Role of Emojis and Emoticons
Saba Yousefian Jazi, Amir Mirzaeinia, Sina Yousefian Jazi
In this effort we fine tuned different models based on BERT to detect the gender polarity of twitter accounts. We specially focused on analyzing the effect of using emojis and emot…
Wireguard: An Efficient Solution for Securing IoT Device Connectivity
Haseebullah Jumakhan, Amir Mirzaeinia
The proliferation of vulnerable Internet-of-Things (IoT) devices has enabled large-scale cyberattacks. Solutions like Hestia and HomeSnitch have failed to comprehensively address I…