6 citations · 6 across the 1 of their papers we have counts for
6 papers
Driving with Data in the Motor City: Mining and Modeling Vehicle Fleet Maintenance Data
Josh Gardner, Jawad Mroueh, Natalia Jenuwine +4
The City of Detroit maintains an active fleet of over 2500 vehicles, spending an annual average of over $5 million on purchases and over $7.7 million on maintenance. Modeling pat…
Advances and Open Problems in Federated Learning
Peter Kairouz, H. Brendan McMahan, Brendan Avent +56
Federated learning (FL) is a machine learning setting where many clients (e.g. mobile devices or whole organizations) collaboratively train a model under the orchestration of a cen…
Beyond A/B Testing: Sequential Randomization for Developing Interventions in Scaled Digital Learning Environments
Timothy NeCamp, Josh Gardner, Christopher Brooks
Randomized experiments ensure robust causal inference that are critical to effective learning analytics research and practice. However, traditional randomized experiments, like A/B…
Enabling End-To-End Machine Learning Replicability: A Case Study in Educational Data Mining
Josh Gardner, Yuming Yang, Ryan Baker +1
The use of machine learning techniques has expanded in education research, driven by the rich data from digital learning environments and institutional data warehouses. However, re…
Dropout Model Evaluation in MOOCs
Josh Gardner, Christopher Brooks
The field of learning analytics needs to adopt a more rigorous approach for predictive model evaluation that matches the complex practice of model-building. In this work, we presen…
Driving with Data: Modeling and Forecasting Vehicle Fleet Maintenance in Detroit
Josh Gardner, Danai Koutra, Jawad Mroueh +4
The City of Detroit maintains an active fleet of over 2500 vehicles, spending an annual average of over $5 million on new vehicle purchases and over $7.7 million on maintaining t…