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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... -
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... -
Multimodal Information Retrieval
In today’s rapidly evolving digital landscape, the wealth of available information has expanded beyond the boundaries of traditional text-based... -
Outlook
While multimodal information retrieval has several exciting applications and a high potential for impact on important problems, there are several... -
Multimodal Content Generation
In this chapter, we will review the advances that are being made in this new field of multimodal content generation and also discuss several... -
Retrieval Augmented Modeling
Till this point in our book, we have discussed the fundamental principles of information retrieval, exploring its key elements, and various... -
Transformer-Driven Models for Language, Vision, and Multimodality
In this chapter, we will learn about the modeling and learning techniques that drive multimodal applications. We will focus specifically on the... -
Introduction
In this book, our emphasis is on multimodal information retrieval, specifically concentrating on text and image data. The traditional unimodal... -
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... -
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... -
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... -
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... -
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... -
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,... -
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... -
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... -
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... -
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... -
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... -
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...