Weighted Automata Extraction from Recurrent Neural Networks via Regression on State Spaces

We present a method to extract a weighted finite automaton (WFA) from a recurrent neural network (RNN). Our algorithm is based on the WFA learning algorithm by Balle and Mohri, which is in turn an extension of Angluin's classic \lstar algorithm. Our technical novelty is in the use of \emph{regression} methods for the so-called equivalence queries, thus exploiting the internal state space of an RNN to prioritize counterexample candidates. This way we achieve a quantitative/weighted extension of the recent work by Weiss, Goldberg and Yahav that extracts DFAs. We experimentally evaluate the accuracy, expressivity and efficiency of the extracted WFAs.Comment: AAAI 2020. We are preparing to distribute the implementatio

Lung Nodule Classification by the Combination of Fusion Classifier and Cascaded Convolutional Neural Networks

Lung nodule classification is a class imbalanced problem, as nodules are found with much lower frequency than non-nodules. In the class imbalanced problem, conventional classifiers tend to be overwhelmed by the majority class and ignore the minority class. We showed that cascaded convolutional neural networks can classify the nodule candidates precisely for a class imbalanced nodule candidate data set in our previous study. In this paper, we propose Fusion classifier in conjunction with the cascaded convolutional neural network models. To fuse the models, nodule probabilities are calculated by using the convolutional neural network models at first. Then, Fusion classifier is trained and tested by the nodule probabilities. The proposed method achieved the sensitivity of 94.4% and 95.9% at 4 and 8 false positives per scan in Free Receiver Operating Characteristics (FROC) curve analysis, respectively.Comment: Draft of ISBI2018. arXiv admin note: text overlap with arXiv:1703.0031

Electronic structures of CeRu2X2_2X_2 (XX = Si, Ge) in the paramagnetic phase studied by soft X-ray ARPES and hard X-ray photoelectron spectroscopy

Soft and hard X-ray photoelectron spectroscopy (PES) has been performed for one of the heavy fermion system CeRu$_2$Si$_2$ and a $4f$-localized ferromagnet CeRu$_2$Ge$_2$ in the paramagnetic phase. The three-dimensional band structures and Fermi surface (FS) shapes of CeRu$_2$Si$_2$ have been determined by soft X-ray $h\nu$-dependent angle resolved photoelectron spectroscopy (ARPES). The differences in the Fermi surface topology and the non-$4f$ electronic structures between CeRu$_2$Si$_2$ and CeRu$_2$Ge$_2$ are qualitatively explained by the band-structure calculation for both $4f$ itinerant and localized models, respectively. The Ce valences in CeRu$_2X_2$ ($X$ = Si, Ge) at 20 K are quantitatively estimated by the single impurity Anderson model calculation, where the Ce 3d hard X-ray core-level PES and Ce 3d X-ray absorption spectra have shown stronger hybridization and signature for the partial $4f$ contribution to the conduction electrons in CeRu$_2$Si$_2$.Comment: 8figure

Modelling the Localized to Itinerant Electronic Transition in the Heavy Fermion System CeIrIn5

We address the fundamental question of crossover from localized to itinerant state of a paradigmatic heavy fermionmaterial CeIrIn5. The temperature evolution of the one electron spectra and the optical conductivity is predicted from first principles calculation. The buildup of coherence in the form of a dispersive many body feature is followed in detail and its effects on the conduction electrons and optical conductivity of the material is revealed. We find multiple hybridization gaps and link them to the crystal structure of the material. Our theoretical approach explains the multiple peak structures observed in optical experiments and the sensitivity of CeIrIn5 to substitutions of the transition metal element and may provide a microscopic basis for the more phenomenological descriptions currently used to interpret experiments in heavy fermion systems.Comment: 12 pages, 3 figure