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Explaining AI Decisions: Towards Achieving Human-Centered Explainability in Smart Home Environments
Smart home systems are gaining popularity as homeowners strive to enhance their living and working environments while minimizing energy consumption.
Explainable artificial intelligence
Explainable Artificial Intelligence (XAI)
+1
Unveiling Black-boxes: Explainable Deep Learning Models for Patent Classification
Considering the relevance score, we then generate explanations by visualizing relevant words for the predicted patent class.
Arabic Sentiment Analysis with Noisy Deep Explainable Model
This paper proposes an explainable sentiment classification framework for the Arabic language by introducing a noise layer on Bi-Directional Long Short-Term Memory (BiLSTM) and Convolutional Neural Networks (CNN)-BiLSTM models that overcome over-fitting problem.
Textual Entailment Recognition with Semantic Features from Empirical Text Representation
In this paper, we propose a novel approach to identifying the textual entailment relationship between text and hypothesis, thereby introducing a new semantic feature focusing on empirical threshold-based semantic text representation.
Natural Language Inference
Natural Language Understanding
+2
Interpreting Black-box Machine Learning Models for High Dimensional Datasets
Many real-life datasets, however, are of increasingly high dimensionality, where a large number of features may be irrelevant for both supervised and unsupervised learning tasks.
