Search Results for author: Dinesh Garg

Found 13 papers, 5 papers with code

Knowledge Graph Question Answering via SPARQL Silhouette Generation

no code implementations6 Sep 2021 Sukannya Purkayastha, Saswati Dana, Dinesh Garg, Dinesh Khandelwal, G P Shrivatsa Bhargav

Experimental results show that the quality of generated SPARQL silhouette in the first stage is outstanding for the ideal scenarios but for realistic scenarios (i. e. noisy linker), the quality of the resulting SPARQL silhouette drops drastically.

Graph Question Answering Knowledge Graphs +2

Explanations for CommonsenseQA: New Dataset and Models

no code implementations AKBC Workshop CSKB 2021 Shourya Aggarwal, Divyanshu Mandowara, Vishwajeet Agrawal, Dinesh Khandelwal, Parag Singla, Dinesh Garg

We human-annotate a first-of-its-kind dataset (called ECQA) of positive and negative properties, as well as free-flow explanations, for $11K$ QA pairs taken from the CQA dataset.

Common Sense Reasoning Fine-tuning +3

Quantum Embedding of Knowledge for Reasoning

1 code implementation NeurIPS 2019 Dinesh Garg, Shajith Ikbal Mohamed, Santosh K. Srivastava, Harit Vishwakarma, Hima Karanam, L. Venkata Subramaniam

Statistical Relational Learning (SRL) methods are the most widely used techniques to generate distributional representations of the symbolic Knowledge Bases (KBs).

Relational Reasoning

Span Selection Pre-training for Question Answering

1 code implementation ACL 2020 Michael Glass, Alfio Gliozzo, Rishav Chakravarti, Anthony Ferritto, Lin Pan, G P Shrivatsa Bhargav, Dinesh Garg, Avirup Sil

BERT (Bidirectional Encoder Representations from Transformers) and related pre-trained Transformers have provided large gains across many language understanding tasks, achieving a new state-of-the-art (SOTA).

Language Modelling Language understanding +2

Deep Domain Adaptation under Deep Label Scarcity

no code implementations20 Sep 2018 Amar Prakash Azad, Dinesh Garg, Priyanka Agrawal, Arun Kumar

The goal behind Domain Adaptation (DA) is to leverage the labeled examples from a source domain so as to infer an accurate model in a target domain where labels are not available or in scarce at the best.

Domain Adaptation

Improved Linear Embeddings via Lagrange Duality

no code implementations30 Nov 2017 Kshiteej Sheth, Dinesh Garg, Anirban Dasgupta

Near isometric orthogonal embeddings to lower dimensions are a fundamental tool in data science and machine learning.

Latent Space Embedding for Retrieval in Question-Answer Archives

no code implementations EMNLP 2017 Deepak P, Dinesh Garg, Shirish Shevade

The idea is that such a space mirrors semantic similarity among questions as well as answers, thereby enabling high quality retrieval.

Question Answering Semantic Similarity +3

A Sparse Nonlinear Classifier Design Using AUC Optimization

no code implementations27 Dec 2016 Vishal Kakkar, Shirish K. Shevade, S. Sundararajan, Dinesh Garg

Batch learning methods for solving the kernelized version of this problem suffer from scalability and may not result in sparse classifiers.

A Robust UCB Scheme for Active Learning in Regression from Strategic Crowds

no code implementations25 Jan 2016 Divya Padmanabhan, Satyanath Bhat, Dinesh Garg, Shirish Shevade, Y. Narahari

We study the problem of training an accurate linear regression model by procuring labels from multiple noisy crowd annotators, under a budget constraint.

Active Learning Variational Inference

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