29 citations · 46 across the 10 of their papers we have counts for
11 papers
Domain Agnostic Few-Shot Learning For Document Intelligence
Jaya Krishna Mandivarapu, Eric bunch, Glenn fung
Few-shot learning aims to generalize to novel classes with only a few samples with class labels. Research in few-shot learning has borrowed techniques from transfer learning, metri…
Efficient Document Image Classification Using Region-Based Graph Neural Network
Jaya Krishna Mandivarapu, Eric Bunch, Qian You +1
Document image classification remains a popular research area because it can be commercialized in many enterprise applications across different industries. Recent advancements in l…
Weighting vectors for machine learning: numerical harmonic analysis applied to boundary detection
Eric Bunch, Jeffery Kline, Daniel Dickinson +2
Metric space magnitude, an active field of research in algebraic topology, is a scalar quantity that summarizes the effective number of distinct points that live in a general metri…
Nyströmformer: A Nyström-Based Algorithm for Approximating Self-Attention
Yunyang Xiong, Zhanpeng Zeng, Rudrasis Chakraborty +4
Transformers have emerged as a powerful tool for a broad range of natural language processing tasks. A key component that drives the impressive performance of Transformers is the s…
A Simple yet Brisk and Efficient Active Learning Platform for Text Classification
Teja Kanchinadam, Qian You, Keith Westpfahl +4
In this work, we propose the use of a fully managed machine learning service, which utilizes active learning to directly build models from unstructured data. With this tool, busine…
Graph Neural Networks to Predict Customer Satisfaction Following Interactions with a Corporate Call Center
Teja Kanchinadam, Zihang Meng, Joseph Bockhorst +2
Customer satisfaction is an important factor in creating and maintaining long-term relationships with customers. Near real-time identification of potentially dissatisfied customers…