Blar i AURA på forfatter "Bhattarai, Bimal"

Viser treff 1-6 av 6

    • Building Concise Logical Patterns by Constraining Tsetlin Machine Clause Size 

      Abeyrathna, Kuruge Darshana; Abouzeid, Ahmed Abdulrahem Othman; Bhattarai, Bimal; Giri, Charul; Glimsdal, Sondre; Granmo, Ole-Christoffer; Lei, Jiao; Saha, Rupsa; Sharma, Jivitesh; Tunheim, Svein Anders; Zhang, Xuan (Academic article, 2023)
      Tsetlin machine (TM) is a logic-based machine learning approach with the crucial advantages of being transparent and hardware-friendly. While TMs match or surpass deep learning accuracy for an increasing number of applications, ...

    • Indoor Space Classification Using Cascaded LSTM 

      Yadav, Rohan Kumar; Bhattarai, Bimal; Lei, Jiao; Goodwin, Morten; Granmo, Ole-Christoffer (Journal article; Peer reviewed, 2020)
      Indoor space classification is an important part of localization that helps in precise location extraction, which has been extensively utilized in industrial and domestic domain. There are various approaches that employ ...

    • An Interpretable Knowledge Representation Framework for Natural Language Processing with Cross-Domain Application 

      Bhattarai, Bimal; Granmo, Ole-Christoffer; Lei, Jiao (Lecture Notes in Computer Science;13980, Chapter; Peer reviewed, 2023)
      Data representation plays a crucial role in natural language processing (NLP), forming the foundation for most NLP tasks. Indeed, NLP performance highly depends upon the effectiveness of the preprocessing pipeline that ...

    • Massively Parallel and Asynchronous Tsetlin Machine Architecture Supporting Almost Constant-Time Scaling 

      Abeyrathna, Kuruge Darshana; Bhattarai, Bimal; Goodwin, Morten; Gorji, Saeed Rahimi; Granmo, Ole-Christoffer; Lei, Jiao; Saha, Rupsa; Yadav, Rohan Kumar (Peer reviewed; Journal article, 2021)
      Using logical clauses to represent patterns, Tsetlin Machine (TM) have recently obtained competitive performance in terms of accuracy, memory footprint, energy, and learning speed on several benchmarks. Each TM clause votes ...

    • Tsetlin Machine for Fake News Detection: Enhancing Accuracy and Reliability 

      Ledaal, Bjørn Vetle (Master thesis, 2023)
      This thesis aims to improve the accuracy of fake news detection by using Tsetlin Machines (TM). TMs are well suited for noisy and complex relations within the provided data, which on initial analysis, overlaps nicely with ...

    • Word-level human interpretable scoring mechanism for novel text detection using Tsetlin Machines 

      Bhattarai, Bimal; Granmo, Ole-Christoffer; Lei, Jiao (Peer reviewed; Journal article, 2022)
      Recent research in novelty detection focuses mainly on document-level classification, employing deep neural networks (DNN). However, the black-box nature of DNNs makes it difficult to extract an exact explanation of why a ...