10 citations · 18 across the 6 of their papers we have counts for
6 papers
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…
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…
Generating an Overview Report over Many Documents
Jingwen Wang, Hao Zhang, Cheng Zhang +3
How to efficiently generate an accurate, well-structured overview report (ORPT) over thousands of related documents is challenging. A well-structured ORPT consists of sections of m…
DTATG: An Automatic Title Generator based on Dependency Trees
Liqun Shao, Jie Wang
We study automatic title generation for a given block of text and present a method called DTATG to generate titles. DTATG first extracts a small number of central sentences that co…
Efficient and Effective Single-Document Summarizations and A Word-Embedding Measurement of Quality
Liqun Shao, Hao Zhang, Ming Jia +1
Our task is to generate an effective summary for a given document with specific realtime requirements. We use the softplus function to enhance keyword rankings to favor important s…