Search Results for author: Vijjini Anvesh Rao

Found 12 papers, 2 papers with code

Sequential Domain Adaptation through Elastic Weight Consolidation for Sentiment Analysis

no code implementations2 Jul 2020 Avinash Madasu, Vijjini Anvesh Rao

SDA draws on EWC for training on successive source domains to move towards a general domain solution, thereby solving the problem of domain adaptation.

Domain Adaptation Sentiment Analysis

A SentiWordNet Strategy for Curriculum Learning in Sentiment Analysis

1 code implementation10 May 2020 Vijjini Anvesh Rao, Kaveri Anuranjana, Radhika Mamidi

In this paper, we apply the ideas of curriculum learning, driven by SentiWordNet in a sentiment analysis setting.

Sentiment Analysis

Hindi Question Generation Using Dependency Structures

no code implementations20 Jun 2019 Kaveri Anuranjana, Vijjini Anvesh Rao, Radhika Mamidi

We present a rule-based system for question generation in Hindi by formalizing question transformation methods based on karaka-dependency theory.

Question Answering Question Generation +2

Gated Convolutional Neural Networks for Domain Adaptation

no code implementations16 May 2019 Avinash Madasu, Vijjini Anvesh Rao

In this paper, we show that Gated Convolutional Neural Networks (GCN) perform effectively at learning sentiment analysis in a manner where domain dependant knowledge is filtered out using its gates.

Domain Adaptation Sentiment Analysis

Effectiveness of Self Normalizing Neural Networks for Text Classification

no code implementations3 May 2019 Avinash Madasu, Vijjini Anvesh Rao

In this paper we aim to show the effectiveness of proposed, Self Normalizing Convolutional Neural Networks(SCNN) on text classification.

General Classification text-classification +1

BCSAT : A Benchmark Corpus for Sentiment Analysis in Telugu Using Word-level Annotations

no code implementations ACL 2018 Sreekavitha Parupalli, Vijjini Anvesh Rao, Radhika Mamidi

The presented work aims at generating a systematically annotated corpus that can support the enhancement of sentiment analysis tasks in Telugu using word-level sentiment annotations.

Sentiment Analysis

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