15 citations · 28 across the 4 of their papers we have counts for
6 papers
The Blame Problem in Evaluating Local Explanations, and How to Tackle it
Amir Hossein Akhavan Rahnama
The number of local model-agnostic explanation techniques proposed has grown rapidly recently. One main reason is that the bar for developing new explainability techniques is low d…
Evaluating Local Model-Agnostic Explanations of Learning to Rank Models with Decision Paths
Amir Hossein Akhavan Rahnama, Judith Butepage
Local explanations of learning-to-rank (LTR) models are thought to extract the most important features that contribute to the ranking predicted by the LTR model for a single data p…
Evaluating Local Explanations using White-box Models
Amir Hossein Akhavan Rahnama, Judith Butepage, Pierre Geurts +1
Evaluating explanation techniques using human subjects is costly, time-consuming and can lead to subjectivity in the assessments. To evaluate the accuracy of local explanations, we…
A study of data and label shift in the LIME framework
Amir Hossein Akhavan Rahnama, Henrik Boström
LIME is a popular approach for explaining a black-box prediction through an interpretable model that is trained on instances in the vicinity of the predicted instance. To generate…
An LP-based hyperparameter optimization model for language modeling
Amir Hossein Akhavan Rahnama, Mehdi Toloo, Nezer Jacob Zaidenberg
In order to find hyperparameters for a machine learning model, algorithms such as grid search or random search are used over the space of possible values of the models hyperparamet…
Distributed Real-Time Sentiment Analysis for Big Data Social Streams
Amir Hossein Akhavan Rahnama
Big data trend has enforced the data-centric systems to have continuous fast data streams. In recent years, real-time analytics on stream data has formed into a new research field,…