activity
20172022
most citedPreprocessor Selection for Machine Learning Pipelines

8 citations · 13 across the 7 of their papers we have counts for

collaborators

8 papers

cs.CL2022

When to Use Multi-Task Learning vs Intermediate Fine-Tuning for Pre-Trained Encoder Transfer Learning

Orion Weller, Kevin Seppi, Matt Gardner

Transfer learning (TL) in natural language processing (NLP) has seen a surge of interest in recent years, as pre-trained models have shown an impressive ability to transfer to nove…

cs.CL2021

Exploring the Relationship Between Algorithm Performance, Vocabulary, and Run-Time in Text Classification

Wilson Fearn, Orion Weller, Kevin Seppi

Text classification is a significant branch of natural language processing, and has many applications including document classification and sentiment analysis. Unsurprisingly, thos…

cs.CL2019★ 4 cited

Humor Detection: A Transformer Gets the Last Laugh

Orion Weller, Kevin Seppi

Much previous work has been done in attempting to identify humor in text. In this paper we extend that capability by proposing a new task: assessing whether or not a joke is humoro…

cs.CL2019★ 1 cited

Why Didn't You Listen to Me? Comparing User Control of Human-in-the-Loop Topic Models

Varun Kumar, Alison Smith-Renner, Leah Findlater +2

To address the lack of comparative evaluation of Human-in-the-Loop Topic Modeling (HLTM) systems, we implement and evaluate three contrasting HLTM modeling approaches using simulat…

cs.IR2019

Automatic Evaluation of Local Topic Quality

Jeffrey Lund, Piper Armstrong, Wilson Fearn +4

Topic models are typically evaluated with respect to the global topic distributions that they generate, using metrics such as coherence, but without regard to local (token-level) t…

cs.CL2019

Cross-referencing using Fine-grained Topic Modeling

Jeffrey Lund, Piper Armstrong, Wilson Fearn +3

Cross-referencing, which links passages of text to other related passages, can be a valuable study aid for facilitating comprehension of a text. However, cross-referencing requires…

cs.LG2018★ 8 cited

Preprocessor Selection for Machine Learning Pipelines

Brandon Schoenfeld, Christophe Giraud-Carrier, Mason Poggemann +2

Much of the work in metalearning has focused on classifier selection, combined more recently with hyperparameter optimization, with little concern for data preprocessing. Yet, it i…

cs.HC2017

Sculpt, Deploy, Repeat: Fast Prototyping of Interactive Physical Objects

Michael Jones, Kevin Seppi

Building a deployable PhysiComp that merges form and function typically involves a significant investment of time and skill in digital electronics, 3D modeling and mechanical desig…