Export Citations
Save this search
Please login to be able to save your searches and receive alerts for new content matching your search criteria.
- research-articleFebruary 2024
Semi-supervised cross-lingual speech emotion recognition
- Mirko Agarla,
- Simone Bianco,
- Luigi Celona,
- Paolo Napoletano,
- Alexey Petrovsky,
- Flavio Piccoli,
- Raimondo Schettini,
- Ivan Shanin
Expert Systems with Applications: An International Journal (EXWA), Volume 237, Issue PAMar 2024https://doi.org/10.1016/j.eswa.2023.121368AbstractPerformance in Speech Emotion Recognition (SER) on a single language has increased greatly in the last few years thanks to the use of deep learning techniques. However, cross-lingual SER remains a challenge in real-world applications due to two ...
Highlights- A cross-lingual Speech Emotion Recognition (SER) framework spanning five languages.
- A semi-supervised learning based cross-lingual SER method for emotion categorization.
- Two different approaches for generating pseudo-labels are ...
- review-articleFebruary 2024
Deep learning-based multimodal emotion recognition from audio, visual, and text modalities: A systematic review of recent advancements and future prospects
Expert Systems with Applications: An International Journal (EXWA), Volume 237, Issue PCMar 2024https://doi.org/10.1016/j.eswa.2023.121692AbstractEmotion recognition has recently attracted extensive interest due to its significant applications to human–computer interaction. The expression of human emotion depends on various verbal and non-verbal languages like audio, visual, text, etc. ...
- research-articleFebruary 2024
Robust and sparse canonical correlation analysis for fault detection and diagnosis using training data with outliers
Expert Systems with Applications: An International Journal (EXWA), Volume 236, Issue CFeb 2024https://doi.org/10.1016/j.eswa.2023.121434AbstractA well-known shortcoming of the traditional canonical correlation analysis (CCA) is the lack of robustness against outliers. This shortcoming hinders the application of CCA in the case where the training data contain outliers. To overcome this ...
- research-articleMarch 2023
Theory of reduced biquaternion sparse representation and its applications
Expert Systems with Applications: An International Journal (EXWA), Volume 213, Issue PChttps://doi.org/10.1016/j.eswa.2022.119245Highlights- We proposed new singular value decomposition in the reduced biquaternion domain.
Traditional sparse representation models treat color image either represent color channels independently using the monochromatic model or concatenate color channels using the concatenation model. However, these two strategies cannot ...
- research-articleJanuary 2023
Kernel robust singular value decomposition
Expert Systems with Applications: An International Journal (EXWA), Volume 211, Issue CJan 2023https://doi.org/10.1016/j.eswa.2022.118555AbstractSingular value decomposition (SVD) is one of the most widely used algorithms for dimensionality reduction and performing principal component analysis, which represents an important tool used in many pattern recognition problems. However, in the ...
Highlights- Four kernel robust singular value decomposition (KR-SVD) algorithms are proposed.
- The KR-SVD allows to obtain robust estimates for the singular values and vectors.
- The KR-SVD outperforms the standard SVD and other robust SVD ...
-
- research-articleDecember 2022
A novel initialization method of fixed point continuation for recommendation systems
Expert Systems with Applications: An International Journal (EXWA), Volume 210, Issue CDec 2022https://doi.org/10.1016/j.eswa.2022.118346Highlights- A property in the iterative process of FPC is discovered.
- A novel ...
In recent years, the problem of matrix completion based on rank minimization has received widespread attention in machine learning. The tightest convex relaxation of this problem is the linearly constrained nuclear norm minimization. ...
- research-articleDecember 2022
Nonnegative matrix factorization with combined kernels for small data representation
Expert Systems with Applications: An International Journal (EXWA), Volume 208, Issue CDec 2022https://doi.org/10.1016/j.eswa.2022.118155AbstractKernel nonnegative matrix factorization (KNMF) has emerged as a promising nonlinear data representation method, especially for applications with small sample sizes. Existing methods are usually based on a single kernel function, ...
Highlights- Formulating a combined kernel with the newly defined fractional-power Gaussian kernel.
- research-articleSeptember 2022
Riemannian submanifold framework for log-Euclidean metric learning on symmetric positive definite manifolds
Expert Systems with Applications: An International Journal (EXWA), Volume 202, Issue CSep 2022https://doi.org/10.1016/j.eswa.2022.117270AbstractThis study presents a novel Riemannian submanifold (RS) framework for log-Euclidean metric learning on symmetric positive definite manifolds. Our method identifies the optimal RS without changing the original tangent space. The RS is ...
Highlights- We propose a Riemannian submanifold for log-Euclidean metric learning.
- We ...
- research-articleJune 2022
A novel constrained non-negative matrix factorization method based on users and items pairwise relationship for recommender systems
Expert Systems with Applications: An International Journal (EXWA), Volume 195, Issue Chttps://doi.org/10.1016/j.eswa.2022.116593AbstractNon-negative matrix factorization (NMF) is a famous method to learn parts-based representations of non-negative data. It has been used successfully in various applications such as information retrieval and recommender systems. Most of ...
Highlights- NMF generates low-rank data while keeping the non-negativity of matrices elements.
- research-articleDecember 2021
An efficient Nyström spectral clustering algorithm using incomplete Cholesky decomposition
Expert Systems with Applications: An International Journal (EXWA), Volume 186, Issue CDec 2021https://doi.org/10.1016/j.eswa.2021.115813Highlights- A new matrix factorization strategy is designed for Nyström spectral clustering.
- Incomplete Cholesky decomposition is introduced to accelerate Nyström approximation.
- An efficient Nyström spectral clustering algorithm called ICD-NSC ...
Nyström method can estimate the eigenvectors of a large kernel matrix with the eigenvectors of a small sampled sub-matrix. However, we may encounter two problems when using Nyström method to speed up spectral clustering: one problem is the ...
- research-articleNovember 2021
On clustering categories of categorical predictors in generalized linear models
Expert Systems with Applications: An International Journal (EXWA), Volume 182, Issue CNov 2021https://doi.org/10.1016/j.eswa.2021.115245Highlights- The paper proposes a method to cluster categorical features in Generalized Linear Models.
We propose a method to reduce the complexity of Generalized Linear Models in the presence of categorical predictors. The traditional one-hot encoding, where each category is represented by a dummy variable, can be wasteful, difficult ...
- research-articleMarch 2020
Robust weighted SVD-type latent factor models for rating prediction
Expert Systems with Applications: An International Journal (EXWA), Volume 141, Issue CMar 2020https://doi.org/10.1016/j.eswa.2019.112885AbstractRecommending system is a popular tool in many commercial or social platforms which finds interesting products for users based on their preference history. Predicting the ratings of items, such as movies, plays an essential role in the ...
- research-articleAugust 2019
A novel approach for classification of epileptic seizures using matrix determinant
Expert Systems with Applications: An International Journal (EXWA), Volume 127, Issue CPages 323–341https://doi.org/10.1016/j.eswa.2019.03.021Highlights- Matrix determinant was shown as a novel feature for seizure detection.
- In total,...
Objective: An epileptic seizure is recognized as a neurological disorder caused by transient and unexpected disturbance resulting from the excessive synchronous activity of the neurons in the brain. Analysis of epileptic ...
- research-articleAugust 2019
A Feature Selection based on perturbation theory
Expert Systems with Applications: An International Journal (EXWA), Volume 127, Issue CAug 2019, Pages 1–8https://doi.org/10.1016/j.eswa.2019.02.028Highlights- We have proved that perturbation theory can detect correlations between features.
Consider a supervised dataset D = [ A ∣ b ] , where b is the outcome column, rows of D correspond to observations, and columns of A are the features of the dataset. A central problem in machine learning and pattern recognition is to ...
- articleApril 2009
An iterative semi-explicit rating method for building collaborative recommender systems
Expert Systems with Applications: An International Journal (EXWA), Volume 36, Issue 3Pages 6181–6186https://doi.org/10.1016/j.eswa.2008.07.085Collaborative filtering plays the key role in recent recommender systems. It uses a user-item preference matrix rated either explicitly (i.e., explicit rating) or implicitly (i.e., implicit feedback). Despite the explicit rating captures the preferences ...
- articleApril 2009
Two-way cooperative prediction for collaborative filtering recommendations
Expert Systems with Applications: An International Journal (EXWA), Volume 36, Issue 3April, 2009, Pages 5353–5361https://doi.org/10.1016/j.eswa.2008.06.106The two of the most famous techniques in collaborative filtering (CF) are the so-called User-Based CF and Item-Based CF. In this paper, we claim that each of them takes only one-directional information from the user-item ratings matrix to generate ...
- articleMarch 2009
An efficient document classification model using an improved back propagation neural network and singular value decomposition
Expert Systems with Applications: An International Journal (EXWA), Volume 36, Issue 2Pages 3208–3215https://doi.org/10.1016/j.eswa.2008.01.014This paper proposed a new improved method for back propagation neural network, and used an efficient method to reduce the dimension and improve the performance. The traditional back propagation neural network (BPNN) has the drawbacks of slow learning and ...
- articleOctober 2008
Short Communication: Design of variable structure control for fuzzy nonlinear systems
Expert Systems with Applications: An International Journal (EXWA), Volume 35, Issue 3Pages 1496–1503https://doi.org/10.1016/j.eswa.2007.08.034In this paper, the variable structure control problem is presented for Takagi-Sugeno fuzzy systems with uncertainties and external disturbances. The sliding surfaces for the T-S fuzzy system are proposed by using a Lyapunov function and a fuzzy Lyapunov ...
- articleFebruary 2008
Value-added treatment inference model for rule-based certainty knowledge
Expert Systems with Applications: An International Journal (EXWA), Volume 34, Issue 2Pages 1250–1265https://doi.org/10.1016/j.eswa.2006.12.026During various knowledge sources and expert comments in the knowledge base may lead to knowledge overlaps, conflicts or data size variations in the knowledge base, with wrong knowledge leads to wrong decisions. This study proposes using an O-A-RV ...
- articleFebruary 2008
Classification method using fuzzy level set subgrouping
Expert Systems with Applications: An International Journal (EXWA), Volume 34, Issue 2Pages 859–865https://doi.org/10.1016/j.eswa.2006.10.023We present a new classification system which is based on fuzzy level sets subgrouping. This new classification system allows a fast classification method with quite accurate results. Classification runs were carried out with four different data sets. ...