20 citations · 59 across the 22 of their papers we have counts for
23 papers
Neural Feature Governance: Extending Atom Prevalence
Idris Karel Seunda Ekwe, Patrick Tenga Shako, Ernest Parfait Fokoué
Neural network compression and interpretability remain open challenges in modern deep learn- ing, where billion-parameter architectures deliver impressive accuracy at the cost of t…
Improving the Predictive Performances of Nearest Neighbors Learning by Efficient Variable Selection
Eddie Pei, Ernest Fokoue
This paper computationally demonstrates a sharp improvement in predictive performance for nearest neighbors thanks to an efficient forward selection of the predictor variables.…
Efficient Novelty Detection Methods for Early Warning of Potential Fatal Diseases
Sèdjro Salomon Hotegni, Ernest Fokoué
Fatal diseases, as Critical Health Episodes (CHEs), represent real dangers for patients hospitalized in Intensive Care Units. These episodes can lead to irreversible organ damage a…
A Computational Exploration of Emerging Methods of Variable Importance Estimation
Louis Mozart Kamdem, Ernest Fokoue
Estimating the importance of variables is an essential task in modern machine learning. This help to evaluate the goodness of a feature in a given model. Several techniques for est…
A Text Mining Discovery of Similarities and Dissimilarities Among Sacred Scriptures
Younous Mofenjou Peuriekeu, Victoire Djimna Noyum, Cyrille Feudjio +2
The careful examination of sacred texts gives valuable insights into human psychology, different ideas regarding the organization of societies as well as into terms like truth and…
Boosting the Predictive Accurary of Singer Identification Using Discrete Wavelet Transform For Feature Extraction
Victoire Djimna Noyum, Younous Perieukeu Mofenjou, Cyrille Feudjio +2
Facing the diversity and growth of the musical field nowadays, the search for precise songs becomes more and more complex. The identity of the singer facilitates this search. In th…
Nonnegative Matrix Factorization with Zellner Penalty
Matthew Corsetti, Ernest Fokoué
Nonnegative matrix factorization (NMF) is a relatively new unsupervised learning algorithm that decomposes a nonnegative data matrix into a parts-based, lower dimensional, linear r…
Nonnegative Matrix Factorization with Toeplitz Penalty
Matthew Corsetti, Ernest Fokoué
Nonnegative Matrix Factorization (NMF) is an unsupervised learning algorithm that produces a linear, parts-based approximation of a data matrix. NMF constructs a nonnegative low ra…
Graph Enhanced High Dimensional Kernel Regression
E. Pei, E. Fokoué
In this paper, the flexibility, versatility and predictive power of kernel regression are combined with now lavishly available network data to create regression models with even gr…
Multi-Stage Fault Warning for Large Electric Grids Using Anomaly Detection and Machine Learning
Sanjeev Raja, Ernest Fokoué
In the monitoring of a complex electric grid, it is of paramount importance to provide operators with early warnings of anomalies detected on the network, along with a precise clas…
Naive Dictionary On Musical Corpora: From Knowledge Representation To Pattern Recognition
Qiuyi Wu, Ernest Fokoue
In this paper, we propose and develop the novel idea of treating musical sheets as literary documents in the traditional text analytics parlance, to fully benefit from the vast amo…
To Bayes or Not To Bayes? That's no longer the question!
Ernest Fokoue
This paper seeks to provide a thorough account of the ubiquitous nature of the Bayesian paradigm in modern statistics, data science and artificial intelligence. Once maligned, on t…
On the Statistical Challenges of Echo State Networks and Some Potential Remedies
Qiuyi Wu, Ernest Fokoue, Dhireesha Kudithipudi
Echo state networks are powerful recurrent neural networks. However, they are often unstable and shaky, making the process of finding an good ESN for a specific dataset quite hard.…
A Mathematical Formalization of Hierarchical Temporal Memory's Spatial Pooler
James Mnatzaganian, Ernest Fokoué, Dhireesha Kudithipudi
Hierarchical temporal memory (HTM) is an emerging machine learning algorithm, with the potential to provide a means to perform predictions on spatiotemporal data. The algorithm, in…
On the Predictive Properties of Binary Link Functions
Necla Gunduz, Ernest Fokoue
This paper provides a theoretical and computational justification of the long held claim that of the similarity of the probit and logit link functions often used in binary classifi…
Adaptive Random SubSpace Learning (RSSL) Algorithm for Prediction
Mohamed Elshrif, Ernest Fokoue
We present a novel adaptive random subspace learning algorithm (RSSL) for prediction purpose. This new framework is flexible where it can be adapted with any learning technique. In…
Random Subspace Learning Approach to High-Dimensional Outliers Detection
Bohan Liu, Ernest Fokoue
We introduce and develop a novel approach to outlier detection based on adaptation of random subspace learning. Our proposed method handles both high-dimension low-sample size and…
A Comparison of Classifiers in Performing Speaker Accent Recognition Using MFCCs
Zichen Ma, Ernest Fokoue
An algorithm involving Mel-Frequency Cepstral Coefficients (MFCCs) is provided to perform signal feature extraction for the task of speaker accent recognition. Then different class…
An Information-Theoretic Alternative to the Cronbach's Alpha Coefficient of Item Reliability
Ernest Fokoue, Necla Gunduz
We propose an information-theoretic alternative to the popular Cronbach alpha coefficient of reliability. Particularly suitable for contexts in which instruments are scored on a st…
Pattern Discovery in Students' Evaluations of Professors: A Statistical Data Mining Approach
Necla Gunduz, Ernest Fokoue
The evaluation of instructors by their students has been practiced at most universities for many decades, and there has always been a great interest in a variety of aspects of the…
A Taxonomy of Big Data for Optimal Predictive Machine Learning and Data Mining
Ernest Fokoue
Big data comes in various ways, types, shapes, forms and sizes. Indeed, almost all areas of science, technology, medicine, public health, economics, business, linguistics and socia…
Robust Classification of High Dimension Low Sample Size Data
Necla Gunduz, Ernest Fokoue
The robustification of pattern recognition techniques has been the subject of intense research in recent years. Despite the multiplicity of papers on the subject, very few articles…
Probit Normal Correlated Topic Models
Xingchen Yu, Ernest Fokoue
The logistic normal distribution has recently been adapted via the transformation of multivariate Gaus- sian variables to model the topical distribution of documents in the presenc…