Browsing Computer Science and Automation (CSA) by Advisor "Shevade, Shirish"
Now showing items 1-14 of 14
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Algorithms for Multilingual IR in Low Resource Languages using Weakly Aligned Corpora
Multilingual information retrieval (MLIR) methods generally rely on linguistic resources such as dictionaries, parallel corpora, etc., to overcome the language barrier. For low resource languages without these resources, ... -
CodeQueries: Benchmarking Query Answering over Source Code
Software developers often make queries about the security, performance effectiveness, and maintainability of their code. Through an iterative debugging process, developers analyze the code to find answers to these ... -
A Context-Aware Neural Approach for Explainable Citation Link Prediction
Citations have become an integral part of scientific publications. They play a crucial role in supporting authors’ claims throughout a scientific paper. However, citing related work is a challenging and laborious task, ... -
Explainable and Efficient Neural Models for Natural Language to Bash Command Translation
One of the key goals of Natural Language Processing is to make computers understand natural language. Semantic Parsing has been one of the driving tasks for Natural Language Understanding. It is formally defined as the ... -
An Explainable Hierarchical Class Attention Model for Legal Appeal Automation
Judicial systems worldwide are overburdened due to the limited number of legal professionals. The digitization of legal processes has resulted in abundant legal data, paving the way for the development of legal automation ... -
Model Extraction Defense using Modified Variational Autoencoder
Machine Learning as a Service (MLaaS) exposes machine learning (ML) models that are trained on confidential datasets to users in the form of an Application Programming Interface (API). Since the MLaaS models are deployed ... -
Multi-label Classification with Multiple Label Correlation Orders And Structures
(2018-06-18)Multilabel classification has attracted much interest in recent times due to the wide applicability of the problem and the challenges involved in learning a classifier for multilabeled data. A crucial aspect of multilabel ... -
Neural Approaches for Natural Language Query Answering over Source Code
During software development, developers need to ensure that the developed code is bug-free and the best coding practices are followed during the code development process. To guarantee this, the developers require answers ... -
Neural Models for Personalized Recommendation Systems with External Information
Personalized recommendation systems use the data generated by user-item interactions (for example, in the form of ratings) to predict different users interests in available items and recommend a set of items or products ... -
New Methods for Learning from Heterogeneous and Strategic Agents
(2018-05-21)1 Introduction In this doctoral thesis, we address several representative problems that arise in the context of learning from multiple heterogeneous agents. These problems are relevant to many modern applications such as ... -
Novel Neural Architecture for Multi-Hop Question Answering
Natural language understanding has been one of the key drivers responsible for advancing the eld of AI. To this end, automated Question Answering (QA) has served as an effective way of measuring the language understanding ... -
A Novel Neural Network Architecture for Sentiment-oriented Aspect-Opinion Pair Extraction
Over the years, fine-grained opinion mining in online reviews has received great attention from the NLP research community. It involves different tasks such as Aspect Term Extraction (ATE), Opinion Term Extraction (OTE), ... -
Sparse Multiclass And Multi-Label Classifier Design For Faster Inference
(2013-06-20)Many real-world problems like hand-written digit recognition or semantic scene classification are treated as multiclass or multi-label classification prob-lems. Solutions to these problems using support vector machines (SVMs) ... -
A Syntactic Neural Model For Question Decomposition
Question decomposition along with single-hop Question Answering (QA) system serve as useful modules in developing multi-hop Question Answering systems, mainly because the resulting QA system is interpretable and has been ...