5 citations · 11 across the 4 of their papers we have counts for
6 papers
Lights, Camera, Action! A Framework to Improve NLP Accuracy over OCR documents
Amit Gupte, Alexey Romanov, Sahitya Mantravadi +6
Document digitization is essential for the digital transformation of our societies, yet a crucial step in the process, Optical Character Recognition (OCR), is still not perfect. Ev…
Evaluating Tree Explanation Methods for Anomaly Reasoning: A Case Study of SHAP TreeExplainer and TreeInterpreter
Pulkit Sharma, Shezan Rohinton Mirzan, Apurva Bhandari +4
Understanding predictions made by Machine Learning models is critical in many applications. In this work, we investigate the performance of two methods for explaining tree-based mo…
Examination and Extension of Strategies for Improving Personalized Language Modeling via Interpolation
Liqun Shao, Sahitya Mantravadi, Tom Manzini +4
In this paper, we detail novel strategies for interpolating personalized language models and methods to handle out-of-vocabulary (OOV) tokens to improve personalized language model…
Model adaptation and unsupervised learning with non-stationary batch data under smooth concept drift
Subhro Das, Prasanth Lade, Soundar Srinivasan
Most predictive models assume that training and test data are generated from a stationary process. However, this assumption does not hold true in practice. In this paper, we consid…
Griffon: Reasoning about Job Anomalies with Unlabeled Data in Cloud-based Platforms
Liqun Shao, Yiwen Zhu, Abhiram Eswaran +9
Microsoft's internal big data analytics platform is comprised of hundreds of thousands of machines, serving over half a million jobs daily, from thousands of users. The majority of…
Dealing with Class Imbalance using Thresholding
Charmgil Hong, Rumi Ghosh, Soundar Srinivasan
We propose thresholding as an approach to deal with class imbalance. We define the concept of thresholding as a process of determining a decision boundary in the presence of a tuna…