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Saturated Controller Design of an ABR Explicit Rate Algorithm for ATM Switches
The transmission of multimedia traffic on the broadband integrated service digital networks (B-ISDN) has created the need for new transport...
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Models and Methods for Analyzing Internet Congestion Control Algorithms
Congestion control in the Internet was introduced in the late 1980s by Van Jacobson [9]. Jacobson’s algorithm which is implemented in the transport...
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kNN Join for Dynamic High-Dimensional Data: A Parallel Approach
The k nearest neighbor (kNN) join operation is a fundamental task that combines two high-dimensional databases, enabling data points in the User...
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Multi-level Storage Optimization for Intermediate Data in AI Model Training
As Transformer-based large models become the mainstream of AI training, the development of hardware devices (e.g., GPUs) cannot keep up with the...
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Take a Close Look at the Optimization of Deep Kernels for Non-parametric Two-Sample Tests
The maximum mean discrepancy (MMD) test with deep kernel is a powerful method to distinguish whether two samples are drawn from the same...
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Balanced Hop-Constrained Path Enumeration in Signed Directed Graphs
Hop-constrained path enumeration, which aims to output all the paths from two distinct vertices within the given hops, is one of the fundamental...
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Probabilistic Reverse Top-k Query on Probabilistic Data
Reverse top-k queries have received much attention from research communities. The result of reverse top-k queries is a set of objects, which had the...
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Bayesian Network-Based Multi-objective Estimation of Distribution Algorithm for Feature Selection Tailored to Regression Problems
Feature selection is an essential pre-processing step in Machine Learning for improving the performance of models, reducing the time of predictions,...
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Applying Genetic Algorithms to Validate a Conjecture in Graph Theory: The Minimum Dominating Set Problem
This paper presents a case study where the interdisciplinary approach between artificial intelligence, specifically genetic algorithms, and discrete...
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Multiresolution Controller Based on Window Function Networks for a Quanser Helicopter
To improve neural network (NN) performance, new activation functions, such as ReLU, GELU, and SELU, to name a few, have been proposed. Windows-based...
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Smart Noise Detection for Statistical Disclosure Attacks
While anonymization systems like mix networks can provide privacy to their users by, e.g., hiding their communication relationships, several traffic...
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Load Demand Forecasting Using a Long-Short Term Memory Neural Network
Electric power load forecasting is very important for the operation and the planning of a utility company. Decisions of the electric market, electric...
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To Possess or Not to Possess - WhatsApp for Android Revisited with a Focus on Stickers
WhatsApp stickers are a popular hybrid of images and emoticons that can contain user-created content. Stickers are mostly sent for legitimate...
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Nonlinear DIP-DiracVTV Model for Color Image Restoration
Variational models for inverse problems are mainly based on the choice of the regularizer, whose goal is to give the solutions some desirable...
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Reasoning in DL- \(Lite_R\) Based Knowledge Base Under Category Semantics
We propose in this paper a rewriting of the usual set-theoretical semantics of the Description Logic DL-...
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IFGNN: An Individual Fairness Awareness Model for Missing Sensitive Information Graphs
Graph neural networks (GNNs) provide an approach for analyzing complicated graph data for node, edge, and graph-level prediction tasks. However, due...
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Discovering Densest Subgraph over Heterogeneous Information Networks
Densest Subgraph Discovery (DSD) is a fundamental and challenging problem in the field of graph mining in recent years. The DSD aims to determine,...
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Influence Maximization Revisited
Influence Maximization (IM) has been extensively studied, which is to select a set of k seed users from a social network to maximize the expected...
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Maximum Fairness-Aware (k, r)-Core Identification in Large Graphs
Cohesive subgraph mining is a fundamental problem in attributed graph analysis. The k-core model has been widely used in many studies to measure the...