Connor Mclaughlin

According to our database, Connor Mclaughlin authored at least 10 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Fast and Robust State Estimation and Tracking via Hierarchical Learning.

Connor Mclaughlin, Matthew Ding, Deniz Erdogmus, Lili Su

IEEE Trans. Autom. Control., March, 2026

Similarity-Aware Mixture-of-Experts for Data-Efficient Continual Learning.

Connor Mclaughlin, Nigel Lee, Lili Su

CoRR, March, 2026

On the Power of Source Screening for Learning Shared Feature Extractors.

Leo Wang, Connor Mclaughlin, Lili Su

CoRR, February, 2026

2024

Personalized Federated Learning via Feature Distribution Adaptation.

Connor Mclaughlin, Lili Su

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Byzantine-Resilient Collaborative Hierarchical Non-Bayesian Learning.

Connor Mclaughlin, Matthew Ding, Deniz Erdogmus, Lili Su

Proceedings of the 58th Asilomar Conference on Signals, 2024

2023

Mahalanobis-Aware Training for Out-of-Distribution Detection.

Connor Mclaughlin, Jason Matterer, Michael Yee

CoRR, 2023

Network Fault-tolerant and Byzantine-resilient Social Learning via Collaborative Hierarchical Non-Bayesian Learning.

Connor Mclaughlin, Matthew Ding, Deniz Edogmus, Lili Su

CoRR, 2023

Fast and Robust State Estimation and Tracking via Hierarchical Learning.

Connor Mclaughlin, Matthew Ding, Deniz Edogmus, Lili Su

CoRR, 2023

2021

Latent Factor Decomposition Model: Applications for Questionnaire Data.

Connor J. McLaughlin, Efi G. Kokkotou, Jean A. King, Lisa A. Conboy, Ali Yousefi

CoRR, 2021

Latent Factor Decomposition Model: Applications for Questionnaire Data ^*.

Connor J. McLaughlin, Efi G. Kokkotou, Jean A. King, Lisa A. Conboy, Ali Yousefi

Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021