no code implementations • 14 Mar 2024 • Balaji Ganesan, Matheen Ahmed Pasha, Srinivasa Parkala, Neeraj R Singh, Gayatri Mishra, Sumit Bhatia, Hima Patel, Somashekar Naganna, Sameep Mehta
Explaining neural model predictions to users requires creativity.
no code implementations • 8 Jul 2023 • Nischal Ashok Kumar, Nitin Gupta, Shanmukha Guttula, Hima Patel
This can lead to multiple intents or ambiguity in the input and output samples.
no code implementations • 13 Feb 2023 • Shashank Mujumdar, Stuti Mehta, Hima Patel, Suman Mitra
In this paper, we investigate the effect of addressing difficult samples from a given text dataset on the downstream text classification task.
no code implementations • 12 Aug 2021 • Nitin Gupta, Hima Patel, Shazia Afzal, Naveen Panwar, Ruhi Sharma Mittal, Shanmukha Guttula, Abhinav Jain, Lokesh Nagalapatti, Sameep Mehta, Sandeep Hans, Pranay Lohia, Aniya Aggarwal, Diptikalyan Saha
We attempt to re-look at the data quality issues in the context of building a machine learning pipeline and build a tool that can detect, explain and remediate issues in the data, and systematically and automatically capture all the changes applied to the data.
no code implementations • 10 Dec 2020 • Balaji Ganesan, Hima Patel, Sameep Mehta
Contact Tracing has been used to identify people who were in close proximity to those infected with SARS-Cov2 coronavirus.
no code implementations • 14 Oct 2020 • Shazia Afzal, Rajmohan C, Manish Kesarwani, Sameep Mehta, Hima Patel
Data exploration and quality analysis is an important yet tedious process in the AI pipeline.
no code implementations • 30 Sep 2020 • Subhojeet Pramanik, Shashank Mujumdar, Hima Patel
Recent approaches in literature have exploited the multi-modal information in documents (text, layout, image) to serve specific downstream document tasks.
no code implementations • 7 Mar 2020 • Balaji Ganesan, Srinivas Parkala, Neeraj R Singh, Sumit Bhatia, Gayatri Mishra, Matheen Ahmed Pasha, Hima Patel, Somashekar Naganna
Learning graph representations of n-ary relational data has a number of real world applications like anti-money laundering, fraud detection, and customer due diligence.
no code implementations • 23 Feb 2020 • Lingraj S Vannur, Balaji Ganesan, Lokesh Nagalapatti, Hima Patel, MN Thippeswamy
Cold start knowledge base population (KBP) is the problem of populating a knowledge base from unstructured documents.
no code implementations • 22 Jan 2020 • Balaji Ganesan, Riddhiman Dasgupta, Akshay Parekh, Hima Patel, Berthold Reinwald
A person ontology comprising concepts, attributes and relationships of people has a number of applications in data protection, didentification, population of knowledge graphs for business intelligence and fraud prevention.
no code implementations • 11 Jul 2014 • Ramasubramanian Sundararajan, Hima Patel, Dattesh Shanbhag, Vivek Vaidya
We consider the problem of automatically prescribing oblique planes (short axis, 4 chamber and 2 chamber views) in Cardiac Magnetic Resonance Imaging (MRI).
no code implementations • 10 Jul 2014 • Ramasubramanian Sundararajan, Hima Patel, Manisha Srivastava
This document describes a novel learning algorithm that classifies "bags" of instances rather than individual instances.