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Con-Detect: Detecting adversarially perturbed natural language inputs to deep classifiers through holistic analysis
Published 2023“…Deep Learning (DL) algorithms have shown wonders in many Natural Language Processing (NLP) tasks such as language-to-language translation, spam filtering, fake-news detection, and comprehension understanding. …”
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Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management
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Federated Transfer Learning for Authentication and Privacy Preservation Using Novel Supportive Twin Delayed DDPG (S-TD3) Algorithm for IIoT
Published 2021“…This paper proposes an Federated Transfer Learning for Authentication and Privacy Preservation Using Novel Supportive Twin Delayed DDPG (S-TD3) Algorithm for IIoT. …”
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Exploring New Parameters to Advance Surface Roughness Prediction in Grinding Processes for the Enhancement of Automated Machining
Published 2024“…To evaluate a robust algorithm, a method is devised that involves different networks utilizing various activation functions and neuron sizes to distinguish and select the best architecture for this study. …”
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UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data
Published 2024“…To improve the effectiveness and efficiency of the UniBFS algorithm, Redundant Features Elimination algorithm (RFE) is presented in this paper. …”
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Con-Detect: Detecting Adversarially Perturbed Natural Language Inputs to Deep Classifiers Through Holistic Analysis
Published 2023“…<p>Deep Learning (DL) algorithms have shown wonders in many Natural Language Processing (NLP) tasks such as language-to-language translation, spam filtering, fake-news detection, and comprehension understanding. …”
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Distilling Wisdom: A Review on Optimizing Learning From Massive Language Models
Published 2025“…This survey provides a detailed discussion of the basic principles, algorithms, and implementation methods of knowledge distillation. …”
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Severity-Based Prioritized Processing of Packets with Application in VANETs
Published 2019“…In this study, we propose a generic prioritization and resource management algorithm that can be used to prioritize processing of received packets in vehicular networks. …”
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A Quasi-Oppositional Method for Output Tracking Control by Swarm-Based MPID Controller on AC/HVDC Interconnected Systems With Virtual Inertia Emulation
Published 2021“…The potential possibility for achieving a suitable assessment about the velocity reaction, the flexibility response, and the accuracy of the tracking process is provided by four different scenarios which are operated by step load changes as essential inputs in AC/HVDC interconnected MIMO system. …”
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Towards Scalable Process Mining Pipelines
Published 2023“…Contributions have covered the spectrum of better algorithms, richer comparison metrics, and movement towards online analysis for process data. …”
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Day-Ahead Load Demand Forecasting in Urban Community Cluster Microgrids Using Machine Learning Methods
Published 2022“…Thus, load forecasting is a complicated operation that requires more than statistical methods. There are different machine learning methods available in the literature that are applied to single microgrid cases. …”
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Navigating the Landscape of Deep Reinforcement Learning for Power System Stability Control: A Review
Published 2023“…This review aims to support research in this area of DRL algorithms to embrace PSS against unseen faults and different PS topologies.…”
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Process Mining over Unordered Event Streams
Published 2020“…In this paper, we provide the first contribution towards handling unordered event streams in process mining. Specifically, we formalize the notion of out-of-order arrival of events, where an online analysis algorithm needs to process events in an order different from their generation. …”
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Deep learning-based user experience evaluation in distance learning
Published 2023“…More than 160,000 tweets, addressing conditions related to the major change in the education system, were gathered from Twitter social network and deep learning-based sentiment analysis models and topic models based on latent dirichlet allocation (LDA) algorithm were developed and analyzed. …”
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