• The single depot multiple set orienteering problem 

  Mishra, Abhishek (Scitepress, 2023)

  In this article, we present the single Depot multiple Set Orienteering Problem (sDmSOP), a new variant of the classical Set Orienteering Problem (SOP). A significant feature of sDmSOP is the presence of many travelers who ...
• A compact formulation for the mdmsop: theoretical and computational time analysis 

  Mishra, Abhishek (Springer, 2023-11)

  The multi-Depot multiple Set Orienteering Problem (mDmSOP) is one of the recently proposed variants of the Set Orienteering Problem (SOP), which has applicability in different real-life applications such as delivering ...
• The multi-depot multiple set orienteering problem: an integer linear programming formulation 

  Mishra, Abhishek (Scitepress, 2024)

  In this article, we introduce a novel variant of the single Depot multiple Set Orienteering Problem (sDmSOP), which we refer to as the multi-Depot multiple Set Orienteering Problem (mDmSOP). We suggest the integer linear ...
• Variable neighborhood search for the multi-depot multiple set orienteering problem 

  Mishra, Abhishek (2024)

  This paper introduces a variant of the Set Orienteering Problem (SOP), the multi-Depot multiple Set Orienteering Problem (mDmSOP). It generalizes the SOP by grouping nodes into mutually exclusive sets (clusters) with ...
• New techniques for constructing rare-case hard functions 

  Mishra, Abhishek (2025-02)

  We say that a function is rare-case hard against a given class of algorithms (the adversary) if all algorithms in the class can compute the function only on an o(1)-fraction of instances of size n for large enough n. ...
• Hardness amplification via group theory 

  Mishra, Abhishek (2024-11)

  We employ techniques from group theory to show that, in many cases, counting problems on graphs are almost as hard to solve in a small number of instances as they are in all instances. Specifically, we show the following ...
• Exploring the performance of genetic algorithm and variable neighborhood search for solving the single depot multiple set orienteering problem: a comparative study 

  Mishra, Abhishek (2024-11)

  This article discusses the single Depot multiple Set Orienteering Problem (sDmSOP), a recently suggested generalization of the Set Orienteering Problem (SOP). This problem aims to discover a path for each traveler over a ...
• Composite Sequential Modeling for Identifying Fake Reviews 

  Sharma, Yashvardhan (De Gruyter, 2018-04)

  This paper presents a comprehensive analysis and comparison of various proposed sequential models based on different deep networks such as the convolutional neural network, long short-term memory, and recurrent neural ...
• Neural Network-Based Architecture for Sentiment Analysis in Indian Languages 

  Sharma, Yashvardhan (De Gruyter, 2018-06)

  Sentiment analysis refers to determining the polarity of the opinions represented by text. The paper proposes an approach to determine the sentiments of tweets in one of the Indian languages (Hindi, Bengali, and Tamil). ...
• Language Identification and Context-based Analysis of Code-switching Behaviors in Social Media Discussions 

  Sharma, Yashvardhan (IEEE, 2019)

  Social media discussions see the participation of multilingual individuals: who tend to utilize alternate languages in a single post (code-switching) for effective communication in a discussion. This paper attempts to ...
• Deep Extractive Text Summarization 

  Sharma, Yashvardhan (Elsevier, 2020)

  With introduction of deep learning techniques their has been an increase in intelligent classification of text in many applications. Advances in automatic text summarization using deep learning technique is prime focus of ...
• Deep Text Summarization using Generative Adversarial Networks in Indian Languagess 

  Sharma, Yashvardhan (Elsevier, 2020)

  Abstractive Text Summarization (ATS) is a task of capturing information from different sources and condense it such that, content is represented well and there is no loss of information. It has been an active area of ...
• Bits2020@ Dravidian-CodeMix-FIRE2020: Sub-Word Level Sentiment Analysis of Dravidian Code Mixed Data 

  Sharma, Yashvardhan (CEUR-WS, 2020)

  This paper presents the methodologies implemented while classifying Dravidian code-mixed comments according to their polarity in the evaluation of the track ‘Sentiment Analysis for Davidian Languages in Code-Mixed Text’ ...
• Character aware models with similarity learning for metaphor detection 

  Sharma, Yashvardhan (Association for Computational Linguistics (ACL), 2020)

  Recent work on automatic sequential metaphor detection has involved recurrent neural networks initialized with different pre-trained word embeddings and which are sometimes combined with hand engineered features. To capture ...
• Siva@ HASOC-Dravidian-CodeMix-FIRE-2020: Multilingual Offensive Speech Detection in Code-mixed and Romanized Text 

  Sharma, Yashvardhan (CEUR-WS, 2020)

  Detecting and eliminating offensive and hate speech in social media content is an important concern as hate and offensive speech can have serious consequences in society ranging from ill-education among youth to hate crimes. ...
• Combating Online Hate: A Comparative Study on Identification of Hate Speech and Offensive Content in Social Media Text 

  Sharma, Yashvardhan (IEEE, 2020)

  This paper addresses the important issue of rising hate and offensive comments against individuals or communities on social media. Such behaviour has become pervasive in social media where people are easily able to vent ...
• Text-Convolutional Neural Networks for Fake News Detection in Tweets 

  Sharma, Yashvardhan (Springer, 2020-09)

  With the widespread use of online social networking websites, user-generated stories and social network platform have become critical in news propagation. The Web portals are being used to mislead users for political gains. ...
• Open machine translation for low resource South American languages (AmericasNLP 2021 shared task contribution) 

  Sharma, Yashvardhan (Association for Computational Linguistics (ACL), 2021)

  This paper describes the team ("Tamalli")’s submission to AmericasNLP2021 shared task on Open Machine Translation for low resource South American languages. Our goal was to evaluate different Machine Translation ...
• Stacked Embeddings and Multiple Fine-Tuned XLM-RoBERTa Models for Enhanced Hostility Identification 

  Sharma, Yashvardhan (Springer, 2021-04)

  Designing effective automated techniques for proper identification and categorisation of hostile speech is essential, especially for low resource Indian languages without established datasets. A majority of Indians use ...
• A Three-Fold Machine Learning Approach for Detection of COVID-19 from Audio Data 

  Sharma, Yashvardhan (Springer, 2021-09)

  Most work on leveraging machine learning techniques has been focused on using chest CT scans or X-ray images. However, this approach requires special machinery, and is not very scalable. Using audio data to perform this ...

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