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Blaise Hanczar
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2020 – today
- 2024
- [i2]Alex Lence, Ahmad Fall, Federica Granese, Blaise Hanczar, Joe-Elie Salem, Jean-Daniel Zucker, Edi Prifti:
ECGrecover: a Deep Learning Approach for Electrocardiogram Signal Completion. CoRR abs/2406.16901 (2024) - 2023
- [j19]Aurélien Beaude
, Milad Rafiee Vahid
, Franck Augé
, Farida Zehraoui, Blaise Hanczar:
AttOmics: attention-based architecture for diagnosis and prognosis from omics data. Bioinform. 39(Supplement-1): 94-102 (2023) - [j18]Alice Lacan, Michèle Sebag, Blaise Hanczar:
GAN-based data augmentation for transcriptomics: survey and comparative assessment. Bioinform. 39(Supplement-1): 111-120 (2023) - 2022
- [j17]Blaise Hanczar, Victoria Bourgeais
, Farida Zehraoui:
Assessment of deep learning and transfer learning for cancer prediction based on gene expression data. BMC Bioinform. 23(1): 262 (2022) - [i1]Ayoub Abraich
, Agathe Guilloux, Blaise Hanczar:
SurvCaus : Representation Balancing for Survival Causal Inference. CoRR abs/2203.15672 (2022) - 2021
- [j16]Victoria Bourgeais
, Farida Zehraoui, Mohamed Ben Hamdoune, Blaise Hanczar:
Deep GONet: self-explainable deep neural network based on Gene Ontology for phenotype prediction from gene expression data. BMC Bioinform. 22-S(10): 455 (2021) - [j15]Blaise Hanczar, Avner Bar-Hen:
CASCARO: Cascade of classifiers for minimizing the cost of prediction. Pattern Recognit. Lett. 149: 37-43 (2021) - 2020
- [j14]Blaise Hanczar
, Farida Zehraoui, Tina Issa, Mathieu Arles:
Biological interpretation of deep neural network for phenotype prediction based on gene expression. BMC Bioinform. 21(1): 501 (2020) - [c18]Elies Gherbi, Blaise Hanczar, Jean-Christophe Janodet, Witold Klaudel:
Deep Learning for In-Vehicle Intrusion Detection System. ICONIP (4) 2020: 50-58
2010 – 2019
- 2019
- [j13]Blaise Hanczar:
Performance visualization spaces for classification with rejection option. Pattern Recognit. 96 (2019) - [c17]Elies Gherbi, Blaise Hanczar, Jean-Christophe Janodet, Witold Klaudel:
An Encoding Adversarial Network for Anomaly Detection. ACML 2019: 188-203 - [c16]Matthieu Clertant, Nataliya Sokolovska, Yann Chevaleyre, Blaise Hanczar:
Interpretable Cascade Classifiers with Abstention. AISTATS 2019: 2312-2320 - 2018
- [j12]Blaise Hanczar, Jean-Daniel Zucker
:
An approach to optimizing abstaining area for small sample data classification. Expert Syst. Appl. 95: 153-161 (2018) - [c15]Blaise Hanczar, Mohamed Nadif:
Controlling and Visualizing the Precision-Recall Tradeoff for External Performance Indices. ECML/PKDD (1) 2018: 687-702 - 2016
- [c14]Blaise Hanczar, Avner Bar-Hen:
Controlling the Cost of Prediction in using a Cascade of Reject Classifiers for Personalized Medicine. BIOINFORMATICS 2016: 42-50 - 2015
- [c13]Blaise Hanczar, Mohamed Nadif:
Compromis précision-rappel dans l'évaluation des performances. EGC 2015: 113-124 - 2014
- [j11]David Dernoncourt, Blaise Hanczar, Jean-Daniel Zucker
:
Analysis of feature selection stability on high dimension and small sample data. Comput. Stat. Data Anal. 71: 681-693 (2014) - [c12]Blaise Hanczar, Mohamed Nadif:
Aggregation of Biclustering Solutions for Ensemble Approach. ICPRAM (Selected Papers) 2014: 19-34 - [c11]Blaise Hanczar, Mohamed Nadif:
Unsupervised Consensus Functions Applied to Ensemble Biclustering. ICPRAM 2014: 30-39 - [c10]David Dernoncourt, Blaise Hanczar, Jean-Daniel Zucker:
Stability of Ensemble Feature Selection on High-Dimension and Low-Sample Size Data - Influence of the Aggregation Method. ICPRAM 2014: 325-330 - [c9]Blaise Hanczar, Michèle Sebag:
Combination of One-Class Support Vector Machines for Classification with Reject Option. ECML/PKDD (1) 2014: 547-562 - 2013
- [j10]Blaise Hanczar, Edward R. Dougherty:
The reliability of estimated confidence intervals for classification error rates when only a single sample is available. Pattern Recognit. 46(3): 1067-1077 (2013) - [c8]Blaise Hanczar, Mohamed Nadif:
Precision-recall space to correct external indices for biclustering. ICML (2) 2013: 136-144 - 2012
- [j9]Blaise Hanczar, Mohamed Nadif
:
Ensemble methods for biclustering tasks. Pattern Recognit. 45(11): 3938-3949 (2012) - [j8]Blaise Hanczar, Avner Bar-Hen:
A New Measure of Classifier Performance for Gene Expression Data. IEEE ACM Trans. Comput. Biol. Bioinform. 9(5): 1379-1386 (2012) - [c7]David Dernoncourt, Blaise Hanczar, Jean-Daniel Zucker
:
Experimental analysis of feature selection stability for high-dimension and low-sample size gene expression classification task. BIBE 2012: 350-355 - 2011
- [j7]Blaise Hanczar, Mohamed Nadif
:
Using the bagging approach for biclustering of gene expression data. Neurocomputing 74(10): 1595-1605 (2011) - [c6]Blaise Hanczar, Mohamed Nadif:
Improving the Biological Relevance of Biclustering for Microarray Data in Using Ensemble Methods. DEXA Workshops 2011: 413-417 - 2010
- [j6]Blaise Hanczar, Jianping Hua, Chao Sima, John N. Weinstein
, Michael L. Bittner, Edward R. Dougherty:
Small-sample precision of ROC-related estimates. Bioinform. 26(6): 822-830 (2010) - [j5]Blaise Hanczar, Corneliu Henegar
, Jean-Daniel Zucker
:
Exploring interaction measures to identify informative pairs of genes. Int. J. Bioinform. Res. Appl. 6(6): 628-642 (2010) - [c5]Blaise Hanczar, Mohamed Nadif:
Bagged Biclustering for Microarray Data. ECAI 2010: 1131-1132 - [c4]Blaise Hanczar, Mohamed Nadif:
Bagging for Biclustering: Application to Microarray Data. ECML/PKDD (1) 2010: 490-505 - [c3]Malik Sajjad Ahmed Nadeem, Jean-Daniel Zucker, Blaise Hanczar:
Accuracy-Rejection Curves (ARCs) for Comparing Classification Methods with a Reject Option. MLSB 2010: 65-81
2000 – 2009
- 2008
- [j4]Blaise Hanczar, Edward R. Dougherty:
Classification with reject option in gene expression data. Bioinform. 24(17): 1889-1895 (2008) - 2007
- [j3]Blaise Hanczar, Jean-Daniel Zucker
, Corneliu Henegar
, Lorenza Saitta:
Feature construction from synergic pairs to improve microarray-based classification. Bioinform. 23(21): 2866-2872 (2007) - [j2]Blaise Hanczar, Jianping Hua, Edward R. Dougherty:
Decorrelation of the True and Estimated Classifier Errors in High-Dimensional Settings. EURASIP J. Bioinform. Syst. Biol. 2007 (2007) - 2005
- [c2]Blaise Hanczar, Jean-Daniel Zucker:
Exploiter l'information mutuelle inter-gènes pour réduire la dimension des données biopuces: une approche basée sur la construction automatique d'attributs. CAP 2005: 247-262 - [c1]Blaise Hanczar:
Combining Feature Selection and Feature Construction to Improve Concept Learning for High Dimensional Data. SARA 2005: 261-273 - 2003
- [j1]Blaise Hanczar, Mélanie Courtine
, Arriel Benis
, Corneliu Henegar, Karine Clément, Jean-Daniel Zucker:
Improving classification of microarray data using prototype-based feature selection. SIGKDD Explor. 5(2): 23-30 (2003)
Coauthor Index
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last updated on 2024-07-25 20:21 CEST by the dblp team
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