conftrace_

feature importance

139 papers

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FI

Co-occurring keywords

model interpretability (519) model explanation (155) explainable ai (480) shapley value (206) neural network (6616) feature attribution (280) text classification (6793) model interpretation (93) explainable artificial intelligence (130) random forest (326)

Papers

Marginal Contribution Feature Importance - an Axiomatic Approach for Explaining Data ICML 2021
A Unified Taylor Framework for Revisiting Attribution Methods AAAI 2021
Explaining Time Series Predictions with Dynamic Masks ICML 2021
Explainable Automated Graph Representation Learning with Hyperparameter Importance ICML 2021
Shapley Flow: A Graph-based Approach to Interpreting Model Predictions AISTATS 2021
An Importance Weighted Feature Selection Stability Measure JMLR 2021
Explaining Deep Neural Network Models with Adversarial Gradient Integration IJCAI 2021
Feature Importance-Aware Transferable Adversarial Attacks ICCV 2021
Context-Sensitive Temporal Feature Learning for Gait Recognition ICCV 2021
Invertible Concept-based Explanations for CNN Models with Non-negative Concept Activation Vectors AAAI 2021
Building Reliable Explanations of Unreliable Neural Networks: Locally Smoothing Perspective of Model Interpretation CVPR 2021
Widening the Pipeline in Human-Guided Reinforcement Learning with Explanation and Context-Aware Data Augmentation NIPS 2021
The Out-of-Distribution Problem in Explainability and Search Methods for Feature Importance Explanations NIPS 2021
FIMAP: Feature Importance by Minimal Adversarial Perturbation AAAI 2021
Accurate and Robust Feature Importance Estimation under Distribution Shifts AAAI 2021
Does BERT Learn as Humans Perceive? Understanding Linguistic Styles through Lexica EMNLP 2021
Reliable Post hoc Explanations: Modeling Uncertainty in Explainability NIPS 2021
Shapley Residuals: Quantifying the limits of the Shapley value for explanations NIPS 2021
Auditing Black-Box Prediction Models for Data Minimization Compliance NIPS 2021
Evaluating Explainable AI: Which Algorithmic Explanations Help Users Predict Model Behavior? ACL 2020
Channel Pruning Guided by Classification Loss and Feature Importance AAAI 2020
FIND: Human-in-the-Loop Debugging Deep Text Classifiers EMNLP 2020
Automated Dependence Plots UAI 2020
Learning outside the Black-Box: The pursuit of interpretable models NIPS 2020
Learning to Faithfully Rationalize by Construction ACL 2020