Search Results for author: Keegan E. Hines

Found 7 papers, 0 papers with code

Equalizing Credit Opportunity in Algorithms: Aligning Algorithmic Fairness Research with U.S. Fair Lending Regulation

no code implementations5 Oct 2022 I. Elizabeth Kumar, Keegan E. Hines, John P. Dickerson

Credit is an essential component of financial wellbeing in America, and unequal access to it is a large factor in the economic disparities between demographic groups that exist today.

Fairness

Counterfactual Explanations and Algorithmic Recourses for Machine Learning: A Review

no code implementations20 Oct 2020 Sahil Verma, Varich Boonsanong, Minh Hoang, Keegan E. Hines, John P. Dickerson, Chirag Shah

Machine learning plays a role in many deployed decision systems, often in ways that are difficult or impossible to understand by human stakeholders.

BIG-bench Machine Learning counterfactual +1

Quantifying Challenges in the Application of Graph Representation Learning

no code implementations18 Jun 2020 Antonia Gogoglou, C. Bayan Bruss, Brian Nguyen, Reza Sarshogh, Keegan E. Hines

Graph Representation Learning (GRL) has experienced significant progress as a means to extract structural information in a meaningful way for subsequent learning tasks.

Graph Representation Learning Link Prediction +1

On the Interpretability and Evaluation of Graph Representation Learning

no code implementations7 Oct 2019 Antonia Gogoglou, C. Bayan Bruss, Keegan E. Hines

With the rising interest in graph representation learning, a variety of approaches have been proposed to effectively capture a graph's properties.

Graph Representation Learning

DeepTrax: Embedding Graphs of Financial Transactions

no code implementations16 Jul 2019 C. Bayan Bruss, Anish Khazane, Jonathan Rider, Richard Serpe, Antonia Gogoglou, Keegan E. Hines

In this paper, we present a novel application of representation learning to bipartite graphs of credit card transactions in order to learn embeddings of account and merchant entities.

BIG-bench Machine Learning Fraud Detection +4

Graph Embeddings at Scale

no code implementations3 Jul 2019 C. Bayan Bruss, Anish Khazane, Jonathan Rider, Richard Serpe, Saurabh Nagrecha, Keegan E. Hines

Graph embedding is a popular algorithmic approach for creating vector representations for individual vertices in networks.

Graph Embedding graph partitioning +1

A Multitask Network for Localization and Recognition of Text in Images

no code implementations21 Jun 2019 Mohammad Reza Sarshogh, Keegan E. Hines

We present an end-to-end trainable multi-task network that addresses the problem of lexicon-free text extraction from complex documents.

Optical Character Recognition (OCR)

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