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cs.LG2021
Pattern Sampling for Shapelet-based Time Series Classification
Atif Raza, Stefan Kramer
Subsequence-based time series classification algorithms provide accurate and interpretable models, but training these models is extremely computation intensive. The asymptotic time…
cs.LG2020
Rule Extraction from Binary Neural Networks with Convolutional Rules for Model Validation
Sophie Burkhardt, Jannis Brugger, Nicolas Wagner +3
Most deep neural networks are considered to be black boxes, meaning their output is hard to interpret. In contrast, logical expressions are considered to be more comprehensible sin…