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- short-paperJune 2022
A Hybrid Transformer Network for Detection of Risk Situations on Multimodal Life-Log Health Data
- Rupayan Mallick,
- Jenny Benois-Pineau,
- Akka Zemmari,
- Marion Pech,
- Thinhinane Yebda,
- Hélène Amieva,
- Laura Middleton
ICDAR '22: Proceedings of the 3rd ACM Workshop on Intelligent Cross-Data Analysis and RetrievalPages 22–26https://doi.org/10.1145/3512731.3534212The paper is focused on the development of hybrid transformer architectures for the detection of risk events on multimodal data recorded on a person with visual and signal sensors. The proposed two-stream architecture consists of a visual transformer ...
- research-articleMarch 2017
An Algorithm for Constructing Feature Relations between the Classes in the Trading Set
Procedia Computer Science (PROCS), Volume 103, Issue CPages 244–247https://doi.org/10.1016/j.procs.2017.01.094In this paper, we propose a new approach for determining the feature relations between classes to solving a problem of classification on based (precedents of) training set. The main Idea of this approach is the selection of best features for object ...
- research-articleJune 2015
Computer Algebra Applied to a Solitary Waves Study
ISSAC '15: Proceedings of the 2015 ACM International Symposium on Symbolic and Algebraic ComputationPages 125–132https://doi.org/10.1145/2755996.2756659We apply Computer algebra techniques, such as algebraic computations of resultants and discriminants, certified drawing (with a guaranteed topology) of plane curves, to a problem in Fluid dynamics: We investigate ``capillary-gravity'' solitary waves in ...
- research-articleJanuary 2015
An Efficient CRM-Data Mining Framework for the Prediction of Customer Behaviour
Procedia Computer Science (PROCS), Volume 46, Issue CPages 725–731https://doi.org/10.1016/j.procs.2015.02.136AbstractCRM-data mining framework establishes close customer relationships and manages relationship between organizations and customers in today's advanced world of businesses. Data mining has gained popularity in various CRM applications in recent years ...
- ArticleMarch 2014
A Method of Pixel Unmixing by Classes based on the Possibilistic Similarity
ICPRAM 2014: Proceedings of the 3rd International Conference on Pattern Recognition Applications and MethodsPages 220–226https://doi.org/10.5220/0004826202200226In this paper, an approach for pixel unmixing based on possibilistic similarity is proposed. This approach uses possibility distributions to express both the expertâ s semantic knowledge (a priori knowledge) and the contextual information. Dubois-Pradeâ ...
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- articleJuly 2012
Free Energy Score Spaces: Using Generative Information in Discriminative Classifiers
IEEE Transactions on Pattern Analysis and Machine Intelligence (ITPM), Volume 34, Issue 7Pages 1249–1262https://doi.org/10.1109/TPAMI.2011.241A score function induced by a generative model of the data can provide a feature vector of a fixed dimension for each data sample. Data samples themselves may be of differing lengths (e.g., speech segments or other sequential data), but as a score ...
- extended-abstractMay 2012
Watching you moving the mouse, i know who you are
CHI EA '12: CHI '12 Extended Abstracts on Human Factors in Computing SystemsPages 2661–2666https://doi.org/10.1145/2212776.2223853Previous research on modeling human's pointing behavior focuses on user-independent variables such as target width and distance. In this work-in-progress, we investigate a set of user-dependent variables, which are drawn from cursor trajectory data and ...
- articleMay 2012
Empirical Evidence of the Applicability of Functional Clustering through Gene Expression Classification
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), Volume 9, Issue 3Pages 788–798https://doi.org/10.1109/TCBB.2012.23The availability of a great range of prior biological knowledge about the roles and functions of genes and gene-gene interactions allows us to simplify the analysis of gene expression data to make it more robust, compact, and interpretable. Here, we ...
- research-articleMarch 2012
Prototype Selection for Nearest Neighbor Classification: Taxonomy and Empirical Study
IEEE Transactions on Pattern Analysis and Machine Intelligence (ITPM), Volume 34, Issue 3Pages 417–435https://doi.org/10.1109/TPAMI.2011.142The nearest neighbor classifier is one of the most used and well-known techniques for performing recognition tasks. It has also demonstrated itself to be one of the most useful algorithms in data mining in spite of its simplicity. However, the nearest ...
- research-articleMarch 2012
Feature Selection Based on Class-Dependent Densities for High-Dimensional Binary Data
IEEE Transactions on Knowledge and Data Engineering (IEEECS_TKDE), Volume 24, Issue 3Pages 465–477https://doi.org/10.1109/TKDE.2010.263Data and knowledge management systems employ feature selection algorithms for removing irrelevant, redundant, and noisy information from the data. There are two well-known approaches to feature selection, feature ranking (FR) and feature subset ...
- research-articleFebruary 2012
Adaptive Manifold Learning
IEEE Transactions on Pattern Analysis and Machine Intelligence (ITPM), Volume 34, Issue 2Pages 253–265https://doi.org/10.1109/TPAMI.2011.115Manifold learning algorithms seek to find a low-dimensional parameterization of high-dimensional data. They heavily rely on the notion of what can be considered as local, how accurately the manifold can be approximated locally, and, last but not least, ...
- research-articleJanuary 2012
Mutual Information-Based Supervised Attribute Clustering for Microarray Sample Classification
IEEE Transactions on Knowledge and Data Engineering (IEEECS_TKDE), Volume 24, Issue 1Pages 127–140https://doi.org/10.1109/TKDE.2010.210Microarray technology is one of the important biotechnological means that allows to record the expression levels of thousands of genes simultaneously within a number of different samples. An important application of microarray gene expression data in ...
- articleJuly 2011
Random k-Labelsets for Multilabel Classification
IEEE Transactions on Knowledge and Data Engineering (IEEECS_TKDE), Volume 23, Issue 7Pages 1079–1089https://doi.org/10.1109/TKDE.2010.164A simple yet effective multilabel learning method, called label powerset (LP), considers each distinct combination of labels that exist in the training set as a different class value of a single-label classification task. The computational efficiency ...
- articleJuly 2011
Robust Feature Selection for Microarray Data Based on Multicriterion Fusion
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), Volume 8, Issue 4Pages 1080–1092https://doi.org/10.1109/TCBB.2010.103Feature selection often aims to select a compact feature subset to build a pattern classifier with reduced complexity, so as to achieve improved classification performance. From the perspective of pattern analysis, producing stable or robust solution is ...
- research-articleMarch 2010
A Distance Measure Approach to Exploring the Rough Set Boundary Region for Attribute Reduction
IEEE Transactions on Knowledge and Data Engineering (IEEECS_TKDE), Volume 22, Issue 3Pages 305–317https://doi.org/10.1109/TKDE.2009.119Feature Selection (FS) or Attribute Reduction techniques are employed for dimensionality reduction and aim to select a subset of the original features of a data set which are rich in the most useful information. The benefits of employing FS techniques ...
- research-articleNovember 2009
A Dynamic Discretization Approach for Constructing Decision Trees with a Continuous Label
IEEE Transactions on Knowledge and Data Engineering (IEEECS_TKDE), Volume 21, Issue 11Pages 1505–1514https://doi.org/10.1109/TKDE.2009.24In traditional decision (classification) tree algorithms, the label is assumed to be a categorical (class) variable. When the label is a continuous variable in the data, two possible approaches based on existing decision tree algorithms can be used to ...
- research-articleJuly 2009
Predictive Ensemble Pruning by Expectation Propagation
IEEE Transactions on Knowledge and Data Engineering (IEEECS_TKDE), Volume 21, Issue 7Pages 999–1013https://doi.org/10.1109/TKDE.2009.62An ensemble is a group of learners that work together as a committee to solve a problem. The existing ensemble learning algorithms often generate unnecessarily large ensembles, which consume extra computational resource and may degrade the ...
- research-articleJune 2007
Iterative RELIEF for Feature Weighting: Algorithms, Theories, and Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence (ITPM), Volume 29, Issue 6Pages 1035–1051https://doi.org/10.1109/TPAMI.2007.1093RELIEF is considered one of the most successful algorithms for assessing the quality of features. In this paper, we propose a set of new feature weighting algorithms that perform significantly better than RELIEF, without introducing a large increase in ...
- ArticleNovember 2006
Reduct Generation and Classification of Gene Expression Data
ICHIT '06: Proceedings of the 2006 International Conference on Hybrid Information Technology - Volume 01Pages 699–708Identification of gene subsets responsible for discerning between available samples of gene microarray data is an important task in Bioinformatics. Due to the large number of genes in samples, there is an exponentially large search space of solutions. ...
- research-articleAugust 2006
Test Strategies for Cost-Sensitive Decision Trees
IEEE Transactions on Knowledge and Data Engineering (IEEECS_TKDE), Volume 18, Issue 8Pages 1055–1067https://doi.org/10.1109/TKDE.2006.131In medical diagnosis, doctors must often determine what medical tests (e.g., X-ray and blood tests) should be ordered for a patient to minimize the total cost of medical tests and misdiagnosis. In this paper, we design cost-sensitive machine learning ...