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Cause Effect Pairs in Machine Learning / / edited by Isabelle Guyon, Alexander Statnikov, Berna Bakir Batu
| Cause Effect Pairs in Machine Learning / / edited by Isabelle Guyon, Alexander Statnikov, Berna Bakir Batu |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (378 pages) |
| Disciplina | 006.31 |
| Collana | The Springer Series on Challenges in Machine Learning |
| Soggetto topico |
Artificial intelligence
Optical data processing Pattern recognition Artificial Intelligence Image Processing and Computer Vision Pattern Recognition |
| ISBN | 3-030-21810-4 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1. The cause-effect problem: motivation, ideas, and popular misconceptions -- 2. Evaluation methods of cause-effect pairs -- 3. Learning Bivariate Functional Causal Models -- 4. Discriminant Learning Machines -- 5. Cause-Effect Pairs in Time Series with a Focus on Econometrics -- 6. Beyond cause-effect pairs -- 7. Results of the Cause-Effect Pair Challenge -- 8. Non-linear Causal Inference using Gaussianity Measures -- 9. From Dependency to Causality: A Machine Learning Approach -- 10. Pattern-based Causal Feature Extraction -- 11. Training Gradient Boosting Machines using Curve-fitting and Information-theoretic Features for Causal Direction Detection -- 12. Conditional distribution variability measures for causality detection -- 13. Feature importance in causal inference for numerical and categorical variables -- 14. Markov Blanket Ranking using Kernel-based Conditional Dependence Measures. |
| Record Nr. | UNINA-9910349271903321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Explainable and Interpretable Models in Computer Vision and Machine Learning / / edited by Hugo Jair Escalante, Sergio Escalera, Isabelle Guyon, Xavier Baró, Yağmur Güçlütürk, Umut Güçlü, Marcel van Gerven
| Explainable and Interpretable Models in Computer Vision and Machine Learning / / edited by Hugo Jair Escalante, Sergio Escalera, Isabelle Guyon, Xavier Baró, Yağmur Güçlütürk, Umut Güçlü, Marcel van Gerven |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (305 pages) |
| Disciplina | 006.31 |
| Collana | The Springer Series on Challenges in Machine Learning |
| Soggetto topico |
Artificial intelligence
Optical data processing Pattern recognition Artificial Intelligence Image Processing and Computer Vision Pattern Recognition |
| ISBN | 3-319-98131-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1 Considerations for Evaluation and Generalization in Interpretable Machine Learning -- 2 Explanation Methods in Deep Learning: Users, Values, Concerns and Challenges -- 3 Learning Functional Causal Models with Generative Neural Networks -- 4 Learning Interpretable Rules for Multi-label Classification -- 5 Structuring Neural Networks for More Explainable Predictions -- 6 Generating Post-Hoc Rationales of Deep Visual Classification Decisions -- 7 Ensembling Visual Explanations -- 8 Explainable Deep Driving by Visualizing Causal Action -- 9 Psychology Meets Machine Learning: Interdisciplinary Perspectives on Algorithmic Job Candidate Screening -- 10 Multimodal Personality Trait Analysis for Explainable Modeling of Job Interview Decisions -- 11 On the Inherent Explainability of Pattern Theory-based Video Event Interpretations. . |
| Record Nr. | UNINA-9910299353403321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Gesture Recognition / / edited by Sergio Escalera, Isabelle Guyon, Vassilis Athitsos
| Gesture Recognition / / edited by Sergio Escalera, Isabelle Guyon, Vassilis Athitsos |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (XII, 578 p. 214 illus., 170 illus. in color.) |
| Disciplina | 006.4 |
| Collana | The Springer Series on Challenges in Machine Learning |
| Soggetto topico |
Artificial intelligence
Optical data processing Pattern recognition Artificial Intelligence Image Processing and Computer Vision Pattern Recognition |
| ISBN | 3-319-57021-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Preface -- Chapter 1 -- Chapter 2 -- Chapter 3 -- Chapter 4 -- Chapter 5. |
| Record Nr. | UNINA-9910254813803321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Neural Connectomics Challenge / / edited by Demian Battaglia, Isabelle Guyon, Vincent Lemaire, Javier Orlandi, Bisakha Ray, Jordi Soriano
| Neural Connectomics Challenge / / edited by Demian Battaglia, Isabelle Guyon, Vincent Lemaire, Javier Orlandi, Bisakha Ray, Jordi Soriano |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (X, 117 p. 28 illus.) |
| Disciplina | 006.3 |
| Collana | The Springer Series on Challenges in Machine Learning |
| Soggetto topico |
Artificial intelligence
Optical data processing Artificial Intelligence Image Processing and Computer Vision |
| ISBN | 3-319-53070-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | First Connectomics Challenge: From Imaging to Connectivity -- Simple Connectome Inference from Partial Correlation Statistics in Calcium Imaging -- Supervised Neural Network Structure Recovery -- Signal Correlation Prediction Using Convolutional Neural Networks -- Reconstruction of Excitatory Neuronal Connectivity via Metric Score Pooling and Regularization -- Neural Connectivity Reconstruction from Calcium Imaging Signal using Random Forest with Topological Features -- Efficient Combination of Pairwise Feature Networks -- Predicting Spiking Activities in DLS Neurons with Linear-Nonlinear-Poisson Model -- SuperSlicing Frame Restoration for Anisotropic ssTEM and Video Data -- Supplemental Information. |
| Record Nr. | UNINA-9910254814603321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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