research
∙
08/25/2023
Reinforcement Learning-assisted Evolutionary Algorithm: A Survey and Research Opportunities
Evolutionary algorithms (EA), a class of stochastic search methods based...
share
research
∙
05/08/2022
Hamiltonian Monte Carlo Particle Swarm Optimizer
We introduce the Hamiltonian Monte Carlo Particle Swarm Optimizer (HMC-P...
research
∙
04/07/2022
Interval Bound Propagationx2013aided Fewx002dshot Learning
Few-shot learning aims to transfer the knowledge acquired from training ...
research
∙
01/06/2022
Robust Linear Predictions: Analyses of Uniform Concentration, Fast Rates and Model Misspecification
The problem of linear predictions has been extensively studied for the p...
research
∙
10/27/2021
Uniform Concentration Bounds toward a Unified Framework for Robust Clustering
Recent advances in center-based clustering continue to improve upon the ...
research
∙
10/08/2021
Statistical Regeneration Guarantees of the Wasserstein Autoencoder with Latent Space Consistency
The introduction of Variational Autoencoders (VAE) has been marked as a ...
research
∙
05/01/2021
t-Entropy: A New Measure of Uncertainty with Some Applications
The concept of Entropy plays a key role in Information Theory, Statistic...
research
∙
04/25/2021
An Adaptive Learning based Generative Adversarial Network for One-To-One Voice Conversion
Voice Conversion (VC) emerged as a significant domain of research in the...
research
∙
02/05/2021
Robust Principal Component Analysis: A Median of Means Approach
Principal Component Analysis (PCA) is a fundamental tool for data visual...
research
∙
12/20/2020
Automated Clustering of High-dimensional Data with a Feature Weighted Mean Shift Algorithm
Mean shift is a simple interactive procedure that gradually shifts data ...
research
∙
11/12/2020
Kernel k-Means, By All Means: Algorithms and Strong Consistency
Kernel k-means clustering is a powerful tool for unsupervised learning o...
research
∙
08/26/2020
Appropriateness of Performance Indices for Imbalanced Data Classification: An Analysis
Indices quantifying the performance of classifiers under class-imbalance...
research
∙
04/24/2020
One Sparse Perturbation to Fool them All, almost Always!
Constructing adversarial perturbations for deep neural networks is an im...
research
∙
01/10/2020
Entropy Regularized Power k-Means Clustering
Despite its well-known shortcomings, k-means remains one of the most wid...
research
∙
09/19/2019
A Compressed Coding Scheme for Evolutionary Algorithms in Mixed-Integer Programming: A Case Study on Multi-Objective Constrained Portfolio Optimization
A lot of real-world applications could be modeled as the Mixed-Integer N...
research
∙
03/24/2019
A Strongly Consistent Sparse k-means Clustering with Direct l_1 Penalization on Variable Weights
We propose the Lasso Weighted k-means (LW-k-means) algorithm as a simple...
research
∙
03/22/2019
Generative Adversarial Minority Oversampling
Class imbalance is a long-standing problem relevant to a number of real-...
research
∙
08/09/2018
Fuzzy Clustering to Identify Clusters at Different Levels of Fuzziness: An Evolutionary Multi-Objective Optimization Approach
Fuzzy clustering methods identify naturally occurring clusters in a data...
research
∙
12/22/2017
Diversifying Support Vector Machines for Boosting using Kernel Perturbation: Applications to Class Imbalance and Small Disjuncts
The diversification (generating slightly varying separating discriminato...
research
∙
03/28/2016
