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Improving hyper-parameter self-tuning for data streams by adapting an evolutionary approach
Hyper-parameter tuning of machine learning models has become a crucial task in achieving optimal results in terms of performance. Several researchers...
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A new hyper-parameter optimization method for machine learning in fault classification
Accurate bearing fault classification is essential for the safe and stable operation of rotating machinery. The success of Machine Learning (ML) in...
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Dynamic Parameter Estimation for Mixtures of Plackett-Luce Models
Traditional parameter estimation algorithms rely on static datasets whose data remain constant during program execution. However, in the real-world...
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Parameter-efficient tuning of cross-modal retrieval for a specific database via trainable textual and visual prompts
A novel cross-modal image retrieval method realized by parameter efficiently tuning a pre-trained cross-modal model is proposed in this study....
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AndroEvolve: automated Android API update with data flow analysis and variable denormalization
The Android operating system is frequently updated, with each version bringing a new set of APIs. New versions may involve API deprecation; Android...
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Application of AI-Based Algorithms for Industrial Photovoltaic Module Parameter Extraction
Solar energy is the best choice in non-renewable energy sources for generating electricity since it is a widely accessible and sustainable source....
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Towards Automatic Synthesis of View Update Programs on Relations
Automatic synthesis of bidirectional programs on relations has not been well studied yet. As an attempt to solve the problem, we propose an approach...
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Robust gain-combined proportionate normalized subband adaptive filter algorithm with a variable control parameter step-size scaler
IN order to improve performance of the original normalized subband adaptive filter algorithm with the step-size scaler (SSS-NSAF) when identifying...
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Big topic modeling based on a two-level hierarchical latent Beta-Liouville allocation for large-scale data and parameter streaming
As an extension to the standard symmetric latent Dirichlet allocation topic model, we implement asymmetric Beta-Liouville as a conjugate prior to the...
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Converting hyperparameter gamma in distance-based loss functions to normal parameter for knowledge graph completion
The parameter gamma, which is used in distance-based knowledge graph embedding to distinguish positive and negative samples, plays an important role...
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Multi-granularity competition-cooperation optimization algorithm with adaptive parameter configuration
The intelligent optimization algorithm has the advantage of giving feasible solutions in polynomial time when solving complex problems in reality....
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Accelerating Massively Distributed Deep Learning Through Efficient Pseudo-Synchronous Update Method
In recent years, deep learning models have been successfully applied to large-scale data analysis, including image classification, video caption,...
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Parameterized complexity of multiwinner determination: more effort towards fixed-parameter tractability
We study the parameterized complexity of winner determination problems for three prevalent k -committee selection rules, namely the minimax approval...
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Adaptive Parameter Tuning for Constructing Storage Tiers in an Autonomous Distributed Storage System
We are develo** an autonomous distributed storage system to make effective use of networked heterogeneous storage devices. It dynamically...
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Error-Aware Conversion from ANN to SNN via Post-training Parameter Calibration
Spiking Neural Network (SNN), originating from the neural behavior in biology, has been recognized as one of the next-generation neural networks....
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Enhanced whale optimization algorithm-based modeling and simulation analysis for industrial system parameter identification
Parameter identification for complex systems of nonlinear nature is challenging due to the complicated process structure and large number of...
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Retrospective Cost Parameter Estimation with Application to Space Weather Modeling
This chapter reviews standard parameter estimation techniques and presents a novel gradient-, ensemble-, adjoint-free data-driven parameter...
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A conjugate gradient algorithm based on double parameter scaled Broyden–Fletcher–Goldfarb–Shanno update for optimization problems and image restoration
In this paper, we present a three-term conjugate gradient algorithm and three approaches are used in the designed algorithm: (i) A modified weak...
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Dynamic Universal Accumulator with Batch Update over Bilinear Groups
We propose a Dynamic Universal Accumulator in the Accumulator Manager setting for bilinear groups which extends Nguyen’s positive accumulator and Au...