72 citations · 203 across the 13 of their papers we have counts for
15 papers
TAR on Social Media: A Framework for Online Content Moderation
Eugene Yang, David D. Lewis, Ophir Frieder
Content moderation (removing or limiting the distribution of posts based on their contents) is one tool social networks use to fight problems such as harassment and disinformation.…
Certifying One-Phase Technology-Assisted Reviews
David D. Lewis, Eugene Yang, Ophir Frieder
Technology-assisted review (TAR) workflows based on iterative active learning are widely used in document review applications. Most stopping rules for one-phase TAR workflows lack…
Heuristic Stopping Rules For Technology-Assisted Review
Eugene Yang, David D. Lewis, Ophir Frieder
Technology-assisted review (TAR) refers to human-in-the-loop active learning workflows for finding relevant documents in large collections. These workflows often must meet a target…
On Minimizing Cost in Legal Document Review Workflows
Eugene Yang, David D. Lewis, Ophir Frieder
Technology-assisted review (TAR) refers to human-in-the-loop machine learning workflows for document review in legal discovery and other high recall review tasks. Attorneys and leg…
The Analysis from Nonlinear Distance Metric to Kernel-based Drug Prescription Prediction System
Der-Chen Chang, Ophir Frieder, Chi-Feng Hung +1
Distance metrics and their nonlinear variant play a crucial role in machine learning based real-world problem solving. We demonstrated how Euclidean and cosine distance measures di…
Cross-Global Attention Graph Kernel Network Prediction of Drug Prescription
Hao-Ren Yao, Der-Chen Chang, Ophir Frieder +3
We present an end-to-end, interpretable, deep-learning architecture to learn a graph kernel that predicts the outcome of chronic disease drug prescription. This is achieved through…