Search Results for author: Sameep Mehta

Found 16 papers, 2 papers with code

Data Quality Toolkit: Automatic assessment of data quality and remediation for machine learning datasets

no code implementations12 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.

Explainable Link Prediction for Privacy-Preserving Contact Tracing

no code implementations10 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.

Link Prediction Privacy Preserving

Data Readiness Report

no code implementations14 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.

AutoML

Fair Transfer of Multiple Style Attributes in Text

no code implementations18 Jan 2020 Karan Dabas, Nishtha Madan, Vijay Arya, Sameep Mehta, Gautam Singh, Tanmoy Chakraborty

To preserve anonymity and obfuscate their identity on online platforms users may morph their text and portray themselves as a different gender or demographic.

Chatbot Style Transfer

Extracting Fairness Policies from Legal Documents

no code implementations12 Sep 2018 Rashmi Nagpal, Chetna Wadhwa, Mallika Gupta, Samiulla Shaikh, Sameep Mehta, Vikram Goyal

Automatic extraction of fairness policies, or in general, any specific kind of policies from large legal corpus can be very useful for the study of bias and fairness in the context of AI applications.

Fairness

Generating Clues for Gender based Occupation De-biasing in Text

no code implementations11 Apr 2018 Nishtha Madaan, Gautam Singh, Sameep Mehta, Aditya Chetan, Brihi Joshi

Vast availability of text data has enabled widespread training and use of AI systems that not only learn and predict attributes from the text but also generate text automatically.

Hardening Deep Neural Networks via Adversarial Model Cascades

1 code implementation2 Feb 2018 Deepak Vijaykeerthy, Anshuman Suri, Sameep Mehta, Ponnurangam Kumaraguru

Deep neural networks (DNNs) are vulnerable to malicious inputs crafted by an adversary to produce erroneous outputs.

Model Extraction Warning in MLaaS Paradigm

no code implementations20 Nov 2017 Manish Kesarwani, Bhaskar Mukhoty, Vijay Arya, Sameep Mehta

In this work, we present a cloud-based extraction monitor that can quantify the extraction status of models by observing the query and response streams of both individual and colluding adversarial users.

Adversarial Attack Model extraction

Bollywood Movie Corpus for Text, Images and Videos

no code implementations11 Oct 2017 Nishtha Madaan, Sameep Mehta, Mayank Saxena, Aditi Aggarwal, Taneea S Agrawaal, Vrinda Malhotra

In this work, we have worked with movie data from Wikipedia plots and movie trailers from YouTube.

A Survey on Resilient Machine Learning

no code implementations11 Jul 2017 Atul Kumar, Sameep Mehta

Machine learning based system are increasingly being used for sensitive tasks such as security surveillance, guiding autonomous vehicle, taking investment decisions, detecting and blocking network intrusion and malware etc.

Towards Crafting Text Adversarial Samples

no code implementations10 Jul 2017 Suranjana Samanta, Sameep Mehta

Our algorithm works best for the datasets which have sub-categories within each of the classes of examples.

Adversarial Text Sentiment Analysis

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