the proceedings contain 122 papers. the topics discussed include: equity research chatbot using LLM: a responsive agent for investment research;bird species classification and prediction using machine learning algorit...
ISBN:
(纸本)9798331527822
the proceedings contain 122 papers. the topics discussed include: equity research chatbot using LLM: a responsive agent for investment research;bird species classification and prediction using machine learning algorithms;early identification of nutritional gaps in pregnant women using nail images for healthcare analysis;detection of malignant cancerous nuclei using quantum Hadamard edge detection algorithm;transforming insurance processes with ICP blockchain integration;extracting valuable insights from the handwritten feedback;real-time gesture-to-speech conversion system for mute person;blockchain-based universal basic income system;and crowd density estimation and real-time monitoring using digital twins in transportation hubs.
Since the meta-learning recommendation's quality depends on the meta-features decision quality, a common problem in meta-learning is establishing a (good) collection of meta-features that best represent the datase...
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ISBN:
(纸本)9798400707339
Since the meta-learning recommendation's quality depends on the meta-features decision quality, a common problem in meta-learning is establishing a (good) collection of meta-features that best represent the dataset properties. therefore, many meta-feature measures/methods have been proposed during the last decade to describe the characteristics of the data. However, little attention has been paid to validating the meta-feature decisions in reflecting the actual data properties. In particular, if the meta-feature analysis is negatively affected by complex data characteristics, such as class overlap due to the distortion imposed by the noisy features at the decision boundary of the classes and thereby produces biased meta-learning recommendations that do not match the actual data characteristics (either by overestimating or underestimating the complexity). Hence, this issue is crucial to ensure the success of the meta-learning model since the learning algorithm selection decision is based on meta-feature analysis. Based on that, in this work, we aim to investigate this by assessing the performance of complexity Measures (global/data-level measures) & Instance Hardness Measures (local/instance-level measures) as a meta-feature in reflecting the actual data complexity associated withthe high-class overlapping problem. the reason for focusing on the overlapping classes problem is that several studies have proven that this data issue significantly contributes to degrading prediction accuracy, with which most real-world datasets are associated. On the other hand, the motivation for using the above measures among different meta-feature methods proposed in the literature is that since this study aims to focus on the overlapping classes problem, the above measures are mainly proposed to estimate the data complexity according to the geometrical descriptions focusing on the class overlap imposed by feature values, in which match the data problem that the study interested to in
Approximate multipliers reduce energy consumption in image processing by simplifying circuits, thereby introducing output errors. In this paper, three approximate Booth multipliers, including CABM1(Configurable Approx...
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Protein sequence classification is vital for understanding protein functionalities, aiding in the inference of novel protein functions. Machine learning and deep learning algorithms have revolutionized this field, off...
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作者：
Tausiesakul, BamrungSrinakharinwirot University
Faculty of Engineering Department of Electrical Engineering 63 Mu 7 Rangsit-Nakhonnayok Road Canal 16 Ongkharak Nakhonnayok26120 Thailand
the acquisition of a discrete-time signal is an im-portant part of a compressive sensing problem. A fine algorithm that could bring better signal recovery performance is often called for. In this work, two homotopy al...
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the proceedings contain 22 papers. the topics discussed include: machine learning for socially responsible portfolio optimization;leveraging deep learning approaches for deepfake detection: a review;predicting open pa...
ISBN:
(纸本)9781450399920
the proceedings contain 22 papers. the topics discussed include: machine learning for socially responsible portfolio optimization;leveraging deep learning approaches for deepfake detection: a review;predicting open parking space using deep learning and support vector regression;habitat prediction and knowledge extraction for marine bivalves using machine learning techniques;optimized computational diabetes prediction with feature selection algorithms;chaos gray wolf global optimization algorithm based on opposition-based learning;a learnheuristic approach to a constrained multi-objective portfolio optimization problem;analyzing the computing time to solve single row facility layout problems by simulated annealing in a Python framework;feature selection using gravitational search algorithm in customer churn prediction;and set-based particle swarm optimization for data clustering: comparison and analysis of control parameters.
Surface unmanned platforms can realize the purpose of attacking the enemy boats by loading counterload. In order to solve the problem of maximally traumatizing the enemy boats under the premise of limited damage capab...
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the proceedings contain 12 papers. the topics discussed include: SU-Next: an image segmentation model of breast tumors based on U-next and attention mechanisms;a fast image matching method based on improved SURF;surve...
the proceedings contain 12 papers. the topics discussed include: SU-Next: an image segmentation model of breast tumors based on U-next and attention mechanisms;a fast image matching method based on improved SURF;survey of noise-against techniques for extracting stable skeleton;SDenseNet-an improved DenseNet model for spiking neural networks;a method for generating error-caused scenarios;graph transformation based on heterogeneous information network for graph algorithms;dynamic probabilistic broadcast based on neighbor discovery;FG-PFC: a fine-grained PFC mechanism for lossless RDMA;system health assessment model based on anomaly detection;and the optimization of multi-objective FJSP based on the hybrid algorithm.
the RoboCup, an international competition, necessitated an innovative approach in 2022 due to its transition to an online format in China, prompted by an epidemic. this shift demanded the development of more specializ...
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the proceedings contain 17 papers. the topics discussed include: portable implementations of work stealing;sKokkos: enabling Kokkos with transparent device selection on heterogeneous systems using OpenACC;parallelized...
ISBN:
(纸本)9798400708893
the proceedings contain 17 papers. the topics discussed include: portable implementations of work stealing;sKokkos: enabling Kokkos with transparent device selection on heterogeneous systems using OpenACC;parallelized remapping algorithms for km-scale global weather and climate simulations with icosahedral grid system;approximate block diagonalization of symmetric matrices using quantum annealing;QUBO formulation using inequalities for problems with complex constraints;low-latency communication in RISC-V clusters;flexible systolic array platform on virtual 2-D multi-FPGA plane;an efficient task-parallel pipeline programming framework;and task-based low-rank hybrid parallel Cholesky factorization for distributed memory environment.
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