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en:publi:belief_art [2020/06/18 03:55] tdenoeuxen:publi:belief_art [2021/05/25 07:42] tdenoeux
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-====== Belief Functions and Pattern recognition ====== +====== Belief Functions and Machine Learning ====== 
-  - T. Denoeux and P. P. Shenoy. An Interval-Valued Utility Theory for Decision Making with Dempster-Shafer Belief Function. International Journal of Approximate Reasoning (to appear), 2020. {{ :en:publi:utilitytheoryfdstheory_final.pdf |pdf}}+  - T. Denoeux. NN-EVCLUS: Neural Network-based Evidential Clustering. Information Sciences, Vol. 572, Pages 297-330, 2021. {{ :en:publi:nn_evclus_insv2.pdf |pdf}} 
 +  - Z. Tong, Ph. Xu and T. Denoeux. An evidential classifier based on Dempster-Shafer theory and deep learning. Neurocomputing, Vol. 450, pages 275-293, 2021. {{ :en:publi:r1_clean_evidential_dl_classifier_0206_td_phx.pdf |pdf}} 
 +  - Z.-G. Liu, L.-Q. Huang, K. Zhou, and T. Denoeux. Combination of Transferable Classification with Multisource Domain Adaptation Based on Evidential Reasoning. IEEE Transactions on Neural Networks and Learning Systems, Vol. 32, Issue 5, pages 2015-2029, 2021. {{ :en:publi:tnnls-2013-p-0123.pdf |pdf}} 
 +  - Z. Tong, Ph. Xu and T. Denoeux. Evidential fully convolutional network for semantic segmentation. Applied Intelligence (to appear), 2021. {{ :en:publi:efcn_final.pdf |pdf}} 
 +  - L. Ma and T. Denoeux. Partial Classification in the Belief Function Framework. Knowledge-Based Systems, Vol. 214, 106742, 2021.  {{ :en:publi:revision-v3-final.pdf |pdf}} 
 +  - T. Denoeux. Belief functions induced by random fuzzy sets: A general framework for representing uncertain and fuzzy evidence. Fuzzy Sets and Systems (to appear), 2020. {{ :en:publi:fuzzybs_fss_v2_clean.pdf |pdf}} 
 +  - T. Denoeux. Distributed combination of belief functions. Information Fusion, Vol. 65, pages 179-191, 2021. {{ :en:publi:distcomb_v2clean.pdf |pdf}} 
 +  - T. Denoeux and P. P. Shenoy. An Interval-Valued Utility Theory for Decision Making with Dempster-Shafer Belief Functions. International Journal of Approximate Reasoning, Vol. 124, pages 194-216, 2020. {{ :en:publi:utilitytheoryfdstheory_final.pdf |pdf}}
   - Z.-G. Su, Q. Hu, and T. Denoeux. A Distributed Rough Evidential K-NN Classifier: Integrating Feature Reduction and Classification. IEEE Transactions on Fuzzy Systems (to appear), 2020.{{ :en:publi:tfs_2019_final_version.pdf |pdf}}   - Z.-G. Su, Q. Hu, and T. Denoeux. A Distributed Rough Evidential K-NN Classifier: Integrating Feature Reduction and Classification. IEEE Transactions on Fuzzy Systems (to appear), 2020.{{ :en:publi:tfs_2019_final_version.pdf |pdf}}
-  - Z.-G. Liu, L.-Q. Huang, K. Zhou, and T. Denoeux. Combination of Transferable Classification with Multi-source Domain Adaptation Based on Evidential Reasoning. IEEE Transactions on Neural Networks and Learning Systems (to appear), 2020. {{ :en:publi:tnnls-2013-p-0123.pdf |pdf}} 
   - T. Denoeux. Calibrated model-based evidential clustering using bootstrapping. Information Sciences, Vol. 528, pages 17-45, 2020. {{ :en:publi:bootclus_v2_clean.pdf |pdf}}   - T. Denoeux. Calibrated model-based evidential clustering using bootstrapping. Information Sciences, Vol. 528, pages 17-45, 2020. {{ :en:publi:bootclus_v2_clean.pdf |pdf}}
   - Feng Li, Shoumei Li and Thierry Denoeux. Combining clusterings in the belief function framework. Array, Vol. 6, 100018, 2020. {{ :en:publi:evidential_clustering_submitted_v2.pdf |pdf}}   - Feng Li, Shoumei Li and Thierry Denoeux. Combining clusterings in the belief function framework. Array, Vol. 6, 100018, 2020. {{ :en:publi:evidential_clustering_submitted_v2.pdf |pdf}}
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   - M.-H. Masson and T. Denoeux. Clustering Interval-valued Data using Belief Functions. Pattern Recognition Letters, Vol. 25, Issue 2, 2004, Pages 163-171. {{:en:publi:evclusint.pdf|pdf}}   - M.-H. Masson and T. Denoeux. Clustering Interval-valued Data using Belief Functions. Pattern Recognition Letters, Vol. 25, Issue 2, 2004, Pages 163-171. {{:en:publi:evclusint.pdf|pdf}}
   - T. Denoeux and M.-H. Masson. EVCLUS: Evidential Clustering of Proximity Data. IEEE Transactions on Systems, Man and Cybernetics B, Vol. 34, Issue 1, 95-109, 2004. {{en:revues:evclus.pdf|pdf}}   - T. Denoeux and M.-H. Masson. EVCLUS: Evidential Clustering of Proximity Data. IEEE Transactions on Systems, Man and Cybernetics B, Vol. 34, Issue 1, 95-109, 2004. {{en:revues:evclus.pdf|pdf}}
-  - S. Petit-Renaud and T. Denoeux. Nonparametric regression analysis of uncertain and imprecise data using belief Functions. International Journal of Approximate Reasoning, Vol. 35, No. 1, 1-28, 2004. {{en:revues:petitrenaud.ps|postscript}}+  - S. Petit-Renaud and T. Denoeux. Nonparametric regression analysis of uncertain and imprecise data using belief Functions. International Journal of Approximate Reasoning, Vol. 35, No. 1, 1-28, 2004. {{ :en:publi:petitrenaud.pdf |pdf}}
   - J. François, Y. Grandvalet, T. Denoeux and  J.-M. Roger. Resample and Combine: An Approach to Improving Uncertainty Representation in Evidential Pattern Classification. Information Fusion, (4):75-85, 2003. {{en:revues: info_fusion03.ps|postscript}}   - J. François, Y. Grandvalet, T. Denoeux and  J.-M. Roger. Resample and Combine: An Approach to Improving Uncertainty Representation in Evidential Pattern Classification. Information Fusion, (4):75-85, 2003. {{en:revues: info_fusion03.ps|postscript}}
   - T. Denoeux and A. Ben Yaghlane. Approximating the Combination of Belief Functions using the Fast Moebius Transform in a coarsened frame. International Journal of Approximate Reasoning, Vol. 31, No. 1-2, 77-101, 2002. {{en:revues:ijar02.pdf|pdf}}   - T. Denoeux and A. Ben Yaghlane. Approximating the Combination of Belief Functions using the Fast Moebius Transform in a coarsened frame. International Journal of Approximate Reasoning, Vol. 31, No. 1-2, 77-101, 2002. {{en:revues:ijar02.pdf|pdf}}

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