New Metrics to Evaluate the Performance and Fairness of Personalized Federated Learning

no code implementations • 28 Jul 2021 • Siddharth Divi, Yi-Shan Lin, Habiba Farrukh, Z. Berkay Celik

In this setting, the non-IID distribution of the data across clients restricts the global FL model from delivering good performance on the local data of each client.

Fairness Personalized Federated Learning

What Do You See? Evaluation of Explainable Artificial Intelligence (XAI) Interpretability through Neural Backdoors

no code implementations • 22 Sep 2020 • Yi-Shan Lin, Wen-Chuan Lee, Z. Berkay Celik

EXplainable AI (XAI) methods have been proposed to interpret how a deep neural network predicts inputs through model saliency explanations that highlight the parts of the inputs deemed important to arrive a decision at a specific target.

Explainable artificial intelligence Explainable Artificial Intelligence (XAI)

Interactive Learning for Identifying Relevant Tweets to Support Real-time Situational Awareness

no code implementations • 1 Aug 2019 • Luke S. Snyder, Yi-Shan Lin, Morteza Karimzadeh, Dan Goldwasser, David S. Ebert

We present a novel interactive learning framework to improve the classification process in which the user iteratively corrects the relevancy of tweets in real-time to train the classification model on-the-fly for immediate predictive improvements.

Classification General Classification