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Articles 1231 - 1260 of 6253
Full-Text Articles in Entire DC Network
Enrichment Of Turkish Question Answering Systems Using Knowledge Graphs, Okan Çi̇ftçi̇, Fati̇h Soygazi̇, Selma Teki̇r
Enrichment Of Turkish Question Answering Systems Using Knowledge Graphs, Okan Çi̇ftçi̇, Fati̇h Soygazi̇, Selma Teki̇r
Turkish Journal of Electrical Engineering and Computer Sciences
Recent capabilities of large language models (LLMs) have transformed many tasks in Natural Language Processing (NLP), including question answering. The state-of-the-art systems do an excellent job of responding in a relevant, persuasive way but cannot guarantee factuality. Knowledge graphs, representing facts as triplets, can be valuable for avoiding errors and inconsistencies with real-world facts. This work introduces a knowledge graph-based approach to Turkish question answering. The proposed approach aims to develop a methodology capable of drawing inferences from a knowledge graph to answer complex multihop questions. We construct the Beyazperde Movie Knowledge Graph (BPMovieKG) and the Turkish Movie Question Answering …
Documentation Of Norm Negotiation In A Secondary Mathematics Classroom, Michelle R. Bagley
Documentation Of Norm Negotiation In A Secondary Mathematics Classroom, Michelle R. Bagley
Theses and Dissertations
While previous mathematics education research has shown that norms can change in mathematics classrooms, little research has closely documented the struggles, concessions, and compromises involved in the negotiation process. Negotiating norms is a complex process entailing deliberate teacher moves intended to promote norms, often met with misunderstandings or resistance from students. This thesis documented the negotiation process that occurred when a teacher attempted to require conceptual explanations from students who had not previously been accustomed to doing so. I recorded six days of instruction in a 9th grade algebra unit, transcribed the class discussions, and inferred norms "at play" for …
Memetic Memory As Vital Conduits Of Troublemakers In Digital Culture, Alexander O. Smith, Jordan Loewen-Colón
Memetic Memory As Vital Conduits Of Troublemakers In Digital Culture, Alexander O. Smith, Jordan Loewen-Colón
School of Information Studies - Post-doc and Student Scholarship
Recent fears of data capitalism and colonialism often argue using implicit assumptions about cybernetic technology’s ability to automate data about culture. As such, the level of data granularity made possible by cybernetic engineering can be used to dominate society and culture. Here we unpack these implicit assumptions about the datafication of culture through memes, which both act as cultural data and cultural memory. Using Alexander Galloway’s critical method of protocological analysis and descriptions of media tactics, we respond to fears of cybernetic domination. Protocols – the source by which cybernetic technologies enable automated datafication – enables us to respond to …
From Classroom Interaction To Academic Success: Tracing The Mediating Role Of Effective Communication In Faculty-Student Dynamics, Nadia Dahmani, Wael Ali, Mohammed Aboelenein, Mohammad A.K. Alsmairat, Mursal Faizi
From Classroom Interaction To Academic Success: Tracing The Mediating Role Of Effective Communication In Faculty-Student Dynamics, Nadia Dahmani, Wael Ali, Mohammed Aboelenein, Mohammad A.K. Alsmairat, Mursal Faizi
All Works
This paper aimed to determine the impact of faculty communication style, student proactiveness, and academic discipline on student academic performance and student-faculty relationship quality in the United Arab Emirates (UAE) higher education context. This study also aimed to contribute to the literature by verifying the mediating impact of communication effectiveness between the selected factors. Using a cross-sectional survey design, the study sample comprised 193 university students, and it was analyzed using partial least squares structural equation modeling (PLS-SEM). The results revealed that academic discipline and the professor’s communication style enhanced communication effectiveness, whereas student proactiveness had a minimal effect. The …
Heritage Preservation In Egyptian Villages And Centers, Azza Elsakka Ahmed Abdalwahaab , Ebtehal Fady Shareef
Heritage Preservation In Egyptian Villages And Centers, Azza Elsakka Ahmed Abdalwahaab , Ebtehal Fady Shareef
Journal of Engineering Research
Heritage holds deep significance as a collective memory and a source of pride for any society. However, in today's world, it has evolved beyond its symbolic status and emerged as a crucial factor in human development across various dimensions. Preserving and restoring heritage has thus become an urgent issue that demands extensive cooperation between governments, international society, and community associations.
When Overextended Surface Allocation Turns To Groundwater: A Q Methodology Of Well Users In Oregon’S High Desert, Melissa Haeffner, Janet Cowal, Brandy Walker, Clare Mcclellan
When Overextended Surface Allocation Turns To Groundwater: A Q Methodology Of Well Users In Oregon’S High Desert, Melissa Haeffner, Janet Cowal, Brandy Walker, Clare Mcclellan
Environmental Science and Management Faculty Publications and Presentations
As legal battles over surface water allocation in Klamath County, Oregon, USA have gained national attention, earning the name “Water Wars,” authorities have been increasingly turning to groundwater to compensate for water shortfalls. This case study aims to identify the nuanced perspectives of household groundwater well users who are affected by groundwater extraction. Using Q methodology, we uncover groundwater well users’ perceptions and to what extent they think water problems are dealt with fairly. We identify four water perspectives that differ in the degree to which respondents prioritize clean water accessibility, industry accountability, individual responsibility for water management, and trust …
Trec Ikat 2023: A Test Collection For Evaluating Conversational And Interactive Knowledge Assistants, Mohammad Aliannejadi, Zahra Abbasiantaeb, Shubham Chatterjee, Jeffrey Dalton, Leif Azzopardi
Trec Ikat 2023: A Test Collection For Evaluating Conversational And Interactive Knowledge Assistants, Mohammad Aliannejadi, Zahra Abbasiantaeb, Shubham Chatterjee, Jeffrey Dalton, Leif Azzopardi
Computer Science Faculty Research & Creative Works
Conversational information seeking has evolved rapidly in the last few years with the development of Large Language Models (LLMs), providing the basis for interpreting and responding in a naturalistic manner to user requests. The extended TREC Interactive Knowledge Assistance Track (iKAT) collection aims to enable researchers to test and evaluate their Conversational Search Agent (CSA). The collection contains a set of 36 personalized dialogues over 20 different topics each coupled with a Personal Text Knowledge Base (PTKB) that defines the bespoke user personas. A total of 344 turns with approximately 26,000 passages are provided as assessments on relevance, as well …
Doing Personal Laps: Llm-Augmented Dialogue Construction For Personalized Multi-Session Conversational Search, Hideaki Joko, Shubham Chatterjee, Andrew Ramsay, Arjen P. De Vries, Jeff Dalton, Faegheh Hasibi
Doing Personal Laps: Llm-Augmented Dialogue Construction For Personalized Multi-Session Conversational Search, Hideaki Joko, Shubham Chatterjee, Andrew Ramsay, Arjen P. De Vries, Jeff Dalton, Faegheh Hasibi
Computer Science Faculty Research & Creative Works
The future of conversational agents will provide users with personalized information responses. However, a significant challenge in developing models is the lack of large-scale dialogue datasets that span multiple sessions and reflect real-world user preferences. Previous approaches rely on experts in a wizard-of-oz setup that is difficult to scale, particularly for personalized tasks. Our method, LAPS, addresses this by using large language models (LLMs) to guide a single human worker in generating personalized dialogues. This method has proven to speed up the creation process and improve quality. LAPS can collect large-scale, human-written, multi-session, and multi-domain conversations, including extracting user preferences. …
A Systematic Approach For Evaluating And Selecting Healthcare Waste Treatment Devices Using Owcm-Codas And Triangular Neutrosophic Sets, Asmaa Elsayed, Bilal Arain
A Systematic Approach For Evaluating And Selecting Healthcare Waste Treatment Devices Using Owcm-Codas And Triangular Neutrosophic Sets, Asmaa Elsayed, Bilal Arain
Neutrosophic Systems with Applications
Healthcare is a fundamental aspect of human life, impacting individuals, communities, and societies. Investing in healthcare infrastructure, services, and education is essential for fostering a healthy, thriving population. Healthcare waste management is a critical aspect of public health, and it requires a concerted effort from healthcare facilities, governments, and communities to ensure that waste is managed in a way that minimizes risks to human health and the environment. This paper proposes a hybrid methodology combining the Opinion Weight Criteria Method (OWCM) and the Combinative Distance-Based Assessment (CODAS) within the framework of Triangular Neutrosophic Sets (TNS) to evaluate and select the …
Leveraging An Uncertainty Methodology To Appraise Risk Factors Threatening Sustainability Of Food Supply Chain, Rehab Mohamed, Mahmoud M. Ismail
Leveraging An Uncertainty Methodology To Appraise Risk Factors Threatening Sustainability Of Food Supply Chain, Rehab Mohamed, Mahmoud M. Ismail
Neutrosophic Systems with Applications
By diminishing the risk factors associated with the food supply chain (FSC), we have recourse to strengthen the food supply chain's resilience, decrease food waste, and increase its sustainability. Prioritizing and identifying the risk factors impacting the sustainability of the food supply chain is essential for managing uncertainty and averting unfavorable consequences. This study attempts to identify and rank the most significant risks affecting the sustainability of the food supply chain under an uncertain environment. We use the α-Discounting multi-criteria decision-making (α-D MCDM) method for the main three risk factors: the risks of supply, the risks of demand, and the …
Unified Training Of Universal Time Series Forecasting Transformers, Gerald Woo, Chenghao Liu, Akshat Kumar, Caiming Xiong, Silvio Savarese, Doyen Sahoo
Unified Training Of Universal Time Series Forecasting Transformers, Gerald Woo, Chenghao Liu, Akshat Kumar, Caiming Xiong, Silvio Savarese, Doyen Sahoo
Research Collection School Of Computing and Information Systems
Deep learning for time series forecasting has traditionally operated within a one-model-per-dataset framework, limiting its potential to leverage the game-changing impact of large pre-trained models. The concept of universal forecasting, emerging from pre-training on a vast collection of time series datasets, envisions a single Large Time Series Model capable of addressing diverse downstream forecasting tasks. However, constructing such a model poses unique challenges specific to time series data: i) cross-frequency learning, ii) accommodating an arbitrary number of variates for multivariate time series, and iii) addressing the varying distributional properties inherent in large-scale data. To address these challenges, we present novel …
Creating And Delivering Audio Descriptions For Videos, Rosiana Natalie
Creating And Delivering Audio Descriptions For Videos, Rosiana Natalie
Dissertations and Theses Collection (Open Access)
Despite anti-discrimination regulations mandating the provision of audio descriptions (ADs), the majority of online video content remains inaccessible to blind and low-vision (BLV) individuals. This is because these ADs are either absent or fail to adequately address the diverse and unique needs of the audience. Traditionally, content creators have relied on professionals to author ADs. However, this gold standard may not be accessible for some content creators because this method is still costly and has a long turnaround time. Moreover, when ADs are available, they tend to be static and unalterable, failing to cater to the unique preferences of BLV …
How People Prompt Generative Ai To Create Interactive Vr Scenes, Setareh Aghel Manesh, Tianyi Zhang, Yuki Onishi, Kotaro Hara, Scott Bateman, Jiannan Li, Anthony Tang
How People Prompt Generative Ai To Create Interactive Vr Scenes, Setareh Aghel Manesh, Tianyi Zhang, Yuki Onishi, Kotaro Hara, Scott Bateman, Jiannan Li, Anthony Tang
Research Collection School Of Computing and Information Systems
Generative AI tools can provide people with the ability to create virtual environments and scenes with natural language prompts. Yet, how people will formulate such prompts is unclear---particularly when they inhabit the environment that they are designing. For instance, it is likely that a person might say, "Put a chair here,'' while pointing at a location. If such linguistic and embodied features are common to people's prompts, we need to tune models to accommodate them. In this work, we present a Wizard of Oz elicitation study with 22 participants, where we studied people's implicit expectations when verbally prompting such programming …
Towards Human-Centered Proactive Conversational Agents, Yang Deng, Lizi Liao, Zhonghua Zheng, Grace Hui Yang, Tat-Seng Chua
Towards Human-Centered Proactive Conversational Agents, Yang Deng, Lizi Liao, Zhonghua Zheng, Grace Hui Yang, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Recent research on proactive conversational agents (PCAs) mainly focuses on improving the system's capabilities in anticipating and planning action sequences to accomplish tasks and achieve goals before users articulate their requests. This perspectives paper highlights the importance of moving towards building human-centered PCAs that emphasize human needs and expectations, and that considers ethical and social implications of these agents, rather than solely focusing on technological capabilities. The distinction between a proactive and a reactive system lies in the proactive system's initiative-taking nature. Without thoughtful design, proactive systems risk being perceived as intrusive by human users. We address the issue by …
Transformer Models With Explainability For It Telemetry And Business Events, Shiau Hong Lim, Laura Wynter
Transformer Models With Explainability For It Telemetry And Business Events, Shiau Hong Lim, Laura Wynter
Research Collection School Of Computing and Information Systems
Temporal event data are commonly encountered in software applications across a wide range of domains, from IT telemetry and system logs to business process automation. Temporal event data in software applications carry information in various forms: both structured and unstructured, and with both regular and irregular occurrence frequency, making the representation of temporal event data challenging. Further chal-lenges come from the diversity in terms of the scale and volume of events that need to be summarized by the representation. We propose a general and unified approach to handle temporal event data for the purpose of learning a predictive transformer model. …
Broadening The View: Demonstration-Augmented Prompt Learning For Conversational Recommendation, Quang Huy Dao, Yang Deng, Dung D. Le, Lizi Liao
Broadening The View: Demonstration-Augmented Prompt Learning For Conversational Recommendation, Quang Huy Dao, Yang Deng, Dung D. Le, Lizi Liao
Research Collection School Of Computing and Information Systems
Conversational Recommender Systems (CRSs) leverage natural language dialogues to provide tailored recommendations. Traditional methods in this field primarily focus on extracting user preferences from isolated dialogues. It often yields responses with a limited perspective, confined to the scope of individual conversations. Recognizing the potential in collective dialogue examples, our research proposes an expanded approach for CRS models, utilizing selective analogues from dialogue histories and responses to enrich both generation and recommendation processes. This introduces significant research challenges, including: (1) How to secure high-quality collections of recommendation dialogue exemplars? (2) How to effectively leverage these exemplars to enhance CRS models?To tackle …
Comparative Analysis Of Hate Speech Detection: Traditional Vs. Deep Learning Approaches, Haibo Pen, Nicole Anne Huiying Teo, Zhaoxia Wang
Comparative Analysis Of Hate Speech Detection: Traditional Vs. Deep Learning Approaches, Haibo Pen, Nicole Anne Huiying Teo, Zhaoxia Wang
Research Collection School Of Computing and Information Systems
Detecting hate speech on social media poses a significant challenge, especially in distinguishing it from offensive language, as learning-based models often struggle due to nuanced differences between them, which leads to frequent misclassifications of hate speech instances, with most research focusing on refining hate speech detection methods. Thus, this paper seeks to know if traditional learning-based methods should still be used, considering the perceived advantages of deep learning in this domain. This is done by investigating advancements in hate speech detection. It involves the utilization of deep learning-based models for detailed hate speech detection tasks and compares the results with …
Raemap: Real-Time Advanced Eye Movements Analysis Pipeline, Gavindya Jayawardena
Raemap: Real-Time Advanced Eye Movements Analysis Pipeline, Gavindya Jayawardena
Computer Science Theses & Dissertations
Eye-tracking offers insights into human cognition and attention allocation by capturing and interpreting eye movements. Traditionally, eye tracking research has relied on offline analysis methods, requiring post-experiment processing to derive insights from gaze data. This approach limits its applicability in contexts requiring immediate feedback and adaptive responses based on real-time gaze behaviors. Recent advancements in computing power and eye tracking technology have enabled a shift towards real-time analysis, allowing modern systems to interpret gaze data with minimal latency, facilitating integration into interactive applications and experiments. Despite these advancements, existing tools often face challenges with real-time computation of advanced gaze measures …
Who Wrote The Scientific News? Improving The Discernibility Of Llms To Human-Written Scientific News, Dominik Soós
Who Wrote The Scientific News? Improving The Discernibility Of Llms To Human-Written Scientific News, Dominik Soós
Computer Science Theses & Dissertations
Large Language Models (LLMs) have rapidly advanced the field of Natural Language Processing and become powerful tools for generating and evaluating scientific text. Although LLMs have demonstrated promising as evaluators for certain text generation tasks, there is still a gap until they are used as reliable text evaluators for general purposes. In this thesis project, I attempted to fill this gap by examining the discernibility of LLMs from human-written and LLM-generated scientific news. This research demonstrated that although it was relatively straightforward for humans to discern scientific news written by humans from scientific news generated by GPT-3.5 using basic prompts, …
Harnessing Social Media For Disaster Response: Intelligent Identification Of Reliable Rescue Requests During Hurricanes, Wael Khallouli
Harnessing Social Media For Disaster Response: Intelligent Identification Of Reliable Rescue Requests During Hurricanes, Wael Khallouli
Engineering Management & Systems Engineering Theses & Dissertations
Hurricanes pose a significant threat to both human lives and infrastructure. Decision-makers face substantial challenges during such events, as they must act quickly to address victims’ needs. Social media platforms provide a valuable source for quick and real-time information. Recent hurricane events have shown that people turn to social media to call for help when official communication channels, such as 911, are overwhelmed. However, extracting actionable information from the massive number of messages posted on social media is challenging. Furthermore, verifying social media messages posted by the public is a critical concern for disaster response practitioners, making them hesitant to …
Exploring The Application Of Digital Twin Technology In The Energy Sector Using Merec And Mairca Methods, Asmaa Elsayed, Bilal Arain, Karam M. Sallam
Exploring The Application Of Digital Twin Technology In The Energy Sector Using Merec And Mairca Methods, Asmaa Elsayed, Bilal Arain, Karam M. Sallam
Neutrosophic Systems with Applications
Smart city sustainability initiatives prioritize creating environmentally, economically, and socially sustainable urban environments. Digital Twin (DT) technology creates precise digital replicas of physical assets, systems, or processes. These digital twins play a crucial role in advancing the goals of smart city sustainability. This paper explores the development and application of DT technology for integrated regional energy systems in smart cities, emphasizing its potential to optimize energy consumption, reduce costs, and enhance overall system performance. The CloudIEPS platform, an energy internet planning platform based on digital twin technology, is a great example of how digital twin technology can be applied in …
Single-Valued Neutrosophic Mcdm Approaches Integrated With Merec And Ram For The Selection Of Uavs In Forest Fire Detection And Management, Mai Mohamed, Amira Salam, Jun Ye, Rui Yong
Single-Valued Neutrosophic Mcdm Approaches Integrated With Merec And Ram For The Selection Of Uavs In Forest Fire Detection And Management, Mai Mohamed, Amira Salam, Jun Ye, Rui Yong
Neutrosophic Systems with Applications
In recent times, the world has experienced a rise in the frequency of forest fires. These fires cause severe economic damage and pose a significant threat to human lives. Therefore, it is essential to search for solutions that can help combat fires and detect them early. Once a fire reaches a certain level, it becomes challenging to control it. Various systems have been proposed to collect data and detect forest fires, such as satellites and other traditional methods. However, these solutions have been ineffective in terms of cost, coverage of large areas, accuracy, and the safety of human lives. To …
An Inference-Centric Approach To Natural Language Processing And Cognitive Modeling, Animesh Nighojkar
An Inference-Centric Approach To Natural Language Processing And Cognitive Modeling, Animesh Nighojkar
USF Tampa Graduate Theses and Dissertations
Reasoning over natural text is highly nuanced, and interpretations can vary widely depending on cultural background, financial status, age, gender, or even mood. This doctoral dissertation seeks to not only mimic human reasoning behaviors but also improve the task used in natural language processing (NLP) to capture naturalistic reasoning, known as the Natural Language Inference (NLI) task. NLI involves determining whether a hypothesis is true (entailment), false (contradiction), or indeterminate (neutral) based on a given premise. Initially, we will investigate the extent to which NLP systems designed to capture semantic equivalence actually measure meaning equivalence. After establishing that they do …
A Robust Data-Driven Framework For Artificial Intelligent Systems, Quoc H. Nguyen
A Robust Data-Driven Framework For Artificial Intelligent Systems, Quoc H. Nguyen
USF Tampa Graduate Theses and Dissertations
Artificial Intelligence (AI) systems have demonstrated remarkable performance across various domains. However, their robustness remains a critical concern, particularly in terms of data and model reliability. This dissertation aims to address the challenges associated with building robust AI systems by focusing on two key aspects: data robustness and model robustness. Data robustness poses significant challenges, including data shift, concept shifting, limited and imbalanced datasets, and interoperability issues in IoT systems for data collection. Existing methods fall short in handling dynamic business objectives and evolving data landscapes effectively. To bridge these gaps, we propose an IoT framework that ensures interoperability, seamless …
Social Messaging Application With Translation And Speech-To-Text Transformation, Kang Qin Yip, Pey Yun Goh, Lee Ying Chong
Social Messaging Application With Translation And Speech-To-Text Transformation, Kang Qin Yip, Pey Yun Goh, Lee Ying Chong
Journal of Informatics and Web Engineering
Unlike traditional SMS or MMS, messaging apps offer a broader range of data transmission capabilities. The application utilizes a WIFI or internet connection and enables users to exchange information through various means such as text, voice, and multimedia files. However, popular messaging applications such as WeChat, Telegram, and WhatsApp have limitations in language translation and file uploading size. Thus, this project aims to address these limitations by developing a social messaging application that serves as a comprehensive communication tool. The application will facilitate both written and verbal communication by providing translation services for various languages, including voice messages. The proposed …
Sentiment Analysis In Social Media: A Case Study Of Hike In University School Fees In Selected Nigerian Universities, Abdulahi Olarewaju Aremu, Isah Muhammad
Sentiment Analysis In Social Media: A Case Study Of Hike In University School Fees In Selected Nigerian Universities, Abdulahi Olarewaju Aremu, Isah Muhammad
Journal of Informatics and Web Engineering
Faced with escalating operational costs and government disinvestment, Nigerian public universities are implementing tuition fee increases to maintain institutional functionality. This necessary fiscal measure comes in the wake of 2022 industrial action, which exacerbated pre-existing financial strain through extended work stoppages and potentially higher costs associated with resuming activities, while leaving unaddressed the longstanding demands of academics for improved welfare and working conditions. The court-mandated resumption of academic activities without resolution of these core issues further strained university finances, leading to a significant increase in tuition fees. Using VADER, this study investigated social media sentiments related to the increase in …
Knowledge-Based Word Tokenization System For Urdu, Asif Khan, Khairullah Khan, Wahab Khan, Sadiq Nawaz Khan, Rafiul Haq
Knowledge-Based Word Tokenization System For Urdu, Asif Khan, Khairullah Khan, Wahab Khan, Sadiq Nawaz Khan, Rafiul Haq
Journal of Informatics and Web Engineering
Word tokenization, a foundational step in natural language processing (NLP), is critical for tasks like part-of-speech tagging, named entity recognition, and parsing, as well as various independent NLP applications. In our tech-driven era, the exponential growth of textual data on the World Wide Web demands sophisticated tools for effective processing. Urdu, spoken widely across the globe, is experiencing a surge in, presents unique challenges due to its distinct writing style, the absence of capitalization features, and the prevalence of compound words. This study introduces a novel knowledge-based word tokenization system tailored for Urdu. Central to this system is a maximum …
Wix For Web Development And The Application Of The Waterfall Model And Project Based Learning For Project Completion: A Case Study, Mawar Madiah, Ng Kai Xuen, Tan Yew Wen, Tan Zhi Heng, Chong Zhi Tian, Chan Jia Xuan
Wix For Web Development And The Application Of The Waterfall Model And Project Based Learning For Project Completion: A Case Study, Mawar Madiah, Ng Kai Xuen, Tan Yew Wen, Tan Zhi Heng, Chong Zhi Tian, Chan Jia Xuan
Journal of Informatics and Web Engineering
Website development without prior knowledge of HTML or programming experience would be a significant challenge. This study aims to share the students' experiences developing a website using Wix, a user-friendly website builder. The website was assigned as a project-based assessment of one of the courses required to complete a Foundation programme. The course was delivered using a project-based learning (PBL) approach in this context. The students worked as a group to write a project proposal, plan activities, develop the website, write reports, and present the outcome. As for the website development process, the study demonstrates the completion of the project …
Machine Learning Multimodal Framework For Fake News Detection And Mitigation, Nada A. Gaballah
Machine Learning Multimodal Framework For Fake News Detection And Mitigation, Nada A. Gaballah
Theses and Dissertations
Social media has become our new reality, people wake up every morning and the first thing they do before getting out of bed, is check their social media. Nowadays, people rarely read newspapers, they even rarely watch TV news or listen to radio broadcasts. In recent years, we have witnessed lots of fake news roaming social media every second, with people simply believing it and spreading it even more without checking the credibility of this news. This fake news affected several domains like what happened in the US election in 2016 and again in 2020, the false information about Covid-19 …
Leveraging Biological Mechanisms In Machine Learning, Kyle J. Rogers
Leveraging Biological Mechanisms In Machine Learning, Kyle J. Rogers
Theses and Dissertations
This thesis integrates biologically-inspired mechanisms into machine learning to develop novel tuning algorithms, gradient abstractions for depth-wise parallelism, and an original bias neuron design. We introduce neuromodulatory tuning, which uses neurotransmitter-inspired bias adjustments to enhance transfer learning in spiking and non-spiking neural networks, significantly reducing parameter usage while maintaining performance. Additionally, we propose a novel approach that decouples the backward pass of backpropagation using layer abstractions, inspired by feedback loops in biological systems, enabling depth-wise training parallelization. We further extend neuromodulatory tuning by designing spiking bias neurons that mimic dopamine neuron mechanisms, leading to the development of volumetric tuning. This …