Submissions
Sandya Mannarswamy

Sandya Mannarswamy

@sandyasm

  • Joined Sep 2019

Sandya Mannarswamy is an NLP researcher and is currently serving as Principal Engineer at Intel India. She was previously a senior research scientist at Conduent Labs India in the Natural Language Processing research group. She holds a Ph.D. in computer science from Indian Institute of Science, Bangalore. Her research interests span natural language processing, machine learning and compilers. Her research career spans over 16 years, at various R&D labs, including Hewlett Packard Ltd, IBM Research etc. Her current research is focused on natural language processing applications and AI compilers. She is the author of the column ‘CodeSport’ in ‘Open Source For You’ magazine.

Submissions for MLOps November edition

Opening the NLP Blackbox - Analysis, Evaluation and Testing of NLP Models

Rapid progress in NLP Research has seen a swift translation to real world commercial deployment. While a number of success stories of NLP applications have emerged, failures of translating scientific progress in NLP to real-world software have also been considerable. Evaluation of NLP models is often limited to held out test set accuracy on a handful of datasets, and analysis of NLP models is oft… more
  • 1 comments
  • Submitted
  • 13 Jun 2021

The Fifth Elephant 2020 edition

Is Your NLP Model Solving the Dataset Or the Actual Task? - Identifying, Analyzing and Mitigating Spurious Dataset Cues in NLP Applications

Natural Language Processing models are susceptible to learning spurious and shallow patterns in the dataset which does not generalize well to real world data. Given that dataset serves as the proxy for the actual task on hand, often deep learning NLP models learn from the spurious shallow patterns in the dataset instead of solving the actual task on hand. The presence of such non-robust brittle f… more
  • 0 comments
  • Submitted
  • 24 Mar 2020

Anthill Inside 2019

Rigorous Evaluation of NLP Models for Real World Deployment

Rapid progress in NLP Research has seen a swift translation to real world commercial deployment. While a number of success stories of NLP applications have emerged, failures of translating scientific progress in NLP to real-world software have also been considerable (some of these issues are covered in my IJCAI paper https://www.ijcai.org/proceedings/2018/717). Specifically, the challenges and ga… more
  • 1 comments
  • Confirmed & scheduled
  • 03 Sep 2019
Full talk Intermediate Discussion

Anthill Inside 2019

Tutorial on Testing of Machine Learning Applications

URL for workshop date, time, venue, schedule and tickets: https://hasgeek.com/anthillinside/testing-machine-learning-applications-workshop/ more
  • 0 comments
  • Confirmed
  • 03 Sep 2019
Tutorials Intermediate Tutorial