47 citations · 80 across the 6 of their papers we have counts for
6 papers
Lessons from Deep Learning applied to Scholarly Information Extraction: What Works, What Doesn't, and Future Directions
Raquib Bin Yousuf, Subhodip Biswas, Kulendra Kumar Kaushal +6
Understanding key insights from full-text scholarly articles is essential as it enables us to determine interesting trends, give insight into the research and development, and buil…
Using AntiPatterns to avoid MLOps Mistakes
Nikhil Muralidhar, Sathappah Muthiah, Patrick Butler +8
We describe lessons learned from developing and deploying machine learning models at scale across the enterprise in a range of financial analytics applications. These lessons are p…
Can Self-Censorship in News Media be Detected Algorithmically? A Case Study in Latin America
Rongrong Tao, Baojian Zhou, Feng Chen +4
Censorship in social media has been well studied and provides insight into how governments stifle freedom of expression online. Comparatively less (or no) attention has been paid t…
EMBERS at 4 years: Experiences operating an Open Source Indicators Forecasting System
Sathappan Muthiah, Patrick Butler, Rupinder Paul Khandpur +15
EMBERS is an anticipatory intelligence system forecasting population-level events in multiple countries of Latin America. A deployed system from 2012, EMBERS has been generating al…
'Beating the news' with EMBERS: Forecasting Civil Unrest using Open Source Indicators
Naren Ramakrishnan, Patrick Butler, Sathappan Muthiah +27
We describe the design, implementation, and evaluation of EMBERS, an automated, 24x7 continuous system for forecasting civil unrest across 10 countries of Latin America using open…
Towards Chip-on-Chip Neuroscience: Fast Mining of Frequent Episodes Using Graphics Processors
Yong Cao, Debprakash Patnaik, Sean Ponce +4
Computational neuroscience is being revolutionized with the advent of multi-electrode arrays that provide real-time, dynamic, perspectives into brain function. Mining event streams…