• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 87 matches

• 2024
• 
  Guillaume Lefebvre, Haytham Elghazel, Théodore Guillet, Alexandre Aussem, Matthieu Sonnati:
  A new sentence embedding framework for the education and professional training domain with application to hierarchical multi-label text classification. Data Knowl. Eng. 150: 102281 (2024)
• 2023
• 
  Florian Baud, Alexandre Aussem:
  Répondre aux requêtes des étudiants avec un agent conversationnel à mémoire supervisée. EGC 2023: 631-632
• 
  Guillaume Lefebvre, Haytham Elghazel, Théodore Guillet, Alexandre Aussem, Matthieu Sonnati:
  BERTEPro : Une nouvelle approche de représentation sémantique dans le domaine de l'éducation et de la formation professionnelle. EGC 2023: 211-222
• 
  Miguel Palencia-Olivar, Stéphane Bonnevay, Alexandre Aussem, Bruno Canitia:
  Topic modeling neuronal non-paramétrique pour l'extraction d'insight client : une application à l'industrie du pneumatique. EGC 2023: 499-506
• 
  Florian Baud, Alex Aussem:
  Answering Student Queries with a Supervised Memory Conversational Agent. FLAIRS 2023
• 
  Florian Baud, Alex Aussem:
  Non-Parametric Memory Guidance for Multi-Document Summarization. RANLP 2023: 153-158
• 
  Guillaume Lefebvre, Haytham Elghazel, Théodore Guillet, Alexandre Aussem, Matthieu Sonnati:
  BERTEPro : A new Sentence Embedding Framework for the Education and Professional Training domain. SAC 2023: 929-935
• 
  Florian Baud, Alexandre Aussem:
  Résumé automatique multi-documents guidé par une base de résumés similaires. CORIA-TALN (4) 2023: 19-27
• 
  Florian Baud, Alex Aussem:
  Non-Parametric Memory Guidance for Multi-Document Summarization. CoRR abs/2311.10760 (2023)
• 2022
• 
  Miguel Palencia-Olivar, Stéphane Bonnevay, Alexandre Aussem, Bruno Canitia:
  Processus de Dirichlet profonds pour le topic modeling. EGC 2022: 355-362
• 
  Miguel Palencia-Olivar, Stéphane Bonnevay, Alexandre Aussem, Bruno Canitia:
  Nonparametric neural topic modeling for customer insight extraction about the tire industry. IJCNN 2022: 1-9
• 2021
• 
  Clément Sage, Thibault Douzon, Alex Aussem, Véronique Eglin, Haytham Elghazel, Stefan Duffner, Christophe Garcia, Jérémy Espinas:
  Data-Efficient Information Extraction from Documents with Pre-trained Language Models. ICDAR Workshops (2) 2021: 455-469
• 
  Miguel Palencia-Olivar, Stéphane Bonnevay, Alexandre Aussem, Bruno Canitia:
  Neural Embedded Dirichlet Processes for Topic Modeling. MDAI 2021: 299-310
• 2020
• 
  Li Guo, Samia Boukir, Alexandre Aussem:
  Building bagging on critical instances. Expert Syst. J. Knowl. Eng. 37(2) (2020)
• 
  Clément Sage, Alex Aussem, Véronique Eglin, Haytham Elghazel, Jérémy Espinas:
  End-to-End Extraction of Structured Information from Business Documents with Pointer-Generator Networks. SPNLP@EMNLP 2020: 43-52
• 2019
• 
  Clément Sage, Alexandre Aussem, Haytham Elghazel, Véronique Eglin, Jérémy Espinas:
  Recurrent Neural Network Approach for Table Field Extraction in Business Documents. ICDAR 2019: 1308-1313
• 
  Jean-Baptiste Aujogue, Alex Aussem:
  Hierarchical Recurrent Attention Networks for Context-Aware Education Chatbots. IJCNN 2019: 1-8
• 2018
• 
  Denis Lecoeuche, Alex Aussem, Maxime Gasse:
  On the use of binary stochastic autoencoders for multi-label classification under the zero-one loss. INNS Conference on Big Data 2018: 71-80
• 2017
• 
  Van-Tinh Tran, Alex Aussem:
  Reducing variance due to importance weighting in covariate shift bias correction. ESANN 2017
• 
  Anil Narassiguin, Haytham Elghazel, Alex Aussem:
  Dynamic Ensemble Selection with Probabilistic Classifier Chains. ECML/PKDD (1) 2017: 169-186
• 2016
• 
  Haytham Elghazel, Alex Aussem, Ouadie Gharroudi, Wafa Saadaoui:
  Ensemble multi-label text categorization based on rotation forest and latent semantic indexing. Expert Syst. Appl. 57: 1-11 (2016)
• 
  Anil Narassiguin, Mohamed Bibimoune, Haytham Elghazel, Alex Aussem:
  An extensive empirical comparison of ensemble learning methods for binary classification. Pattern Anal. Appl. 19(4): 1093-1128 (2016)
• 
  Ouadie Gharroudi, Haytham Elghazel, Alexandre Aussem:
  A Semi-Supervised Ensemble Approach for Multi-label Learning. ICDM Workshops 2016: 1197-1204
• 
  Anil Narassiguin, Haytham Elghazel, Alex Aussem:
  Similarity Tree Pruning: A Novel Dynamic Ensemble Selection Approach. ICDM Workshops 2016: 1243-1250
• 
  Maxime Gasse, Alex Aussem:
  Identifying the irreducible disjoint factors of a multivariate probability distribution. Probabilistic Graphical Models 2016: 183-194
• 
  Maxime Gasse, Alex Aussem:
  F-Measure Maximization in Multi-Label Classification with Conditionally Independent Label Subsets. ECML/PKDD (1) 2016: 619-631
• 
  Maxime Gasse, Alex Aussem:
  F-measure Maximization in Multi-Label Classification with Conditionally Independent Label Subsets. CoRR abs/1604.07759 (2016)
• 2015
• 
  Haytham Elghazel, Alex Aussem:
  Unsupervised feature selection with ensemble learning. Mach. Learn. 98(1-2): 157-180 (2015)
• 
  Maxime Gasse, Alexandre Aussem, Haytham Elghazel:
  On the Optimality of Multi-Label Classification under Subset Zero-One Loss for Distributions Satisfying the Composition Property. ICML 2015: 2531-2539
• 
  Ouadie Gharroudi, Haytham Elghazel, Alex Aussem:
  Calibrated k-labelsets for Ensemble Multi-label Classification. ICONIP (1) 2015: 573-582

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