Cover Image

Exhaustive Exploitation of Nature-inspired Computation for Cancer Screening in an Ensemble Manner

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wang, Xubin, Wang, Yunhe, Ma, Zhiqing, Wong, Ka-Chun, Li, Xiangtao
Format:	Preprint
Published:	2024
Subjects:	Neural and Evolutionary Computing Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Brain-inspired Computational Intelligence via Predictive Coding
by: Salvatori, Tommaso, et al.
Published: (2023)

MEL: Efficient Multi-Task Evolutionary Learning for High-Dimensional Feature Selection
by: Wang, Xubin, et al.
Published: (2024)

Rare Events, Real Signals: Functional Ensembles as Units of Computation in Deep Spiking Networks
by: Aravind, Aditi, et al.
Published: (2026)

Applications of Nature-Inspired Metaheuristic Algorithms for Tackling Optimization Problems Across Disciplines
by: Cui, Elvis Han, et al.
Published: (2023)

Evolutionary Ensemble of Agents
by: Yu, Zongmin, et al.
Published: (2026)

Brain-inspired Chaotic Graph Backpropagation for Large-scale Combinatorial Optimization
by: Tao, Peng, et al.
Published: (2024)

An Experimental Study on Decomposition-Based Deep Ensemble Learning for Traffic Flow Forecasting
by: Zhu, Qiyuan, et al.
Published: (2024)

Auto-configuring Exploration-Exploitation Tradeoff in Evolutionary Computation via Deep Reinforcement Learning
by: Ma, Zeyuan, et al.
Published: (2024)

Reconsidering the energy efficiency of spiking neural networks
by: Yan, Zhanglu, et al.
Published: (2024)

Instance Generation for Meta-Black-Box Optimization through Latent Space Reverse Engineering
by: Wang, Chen, et al.
Published: (2025)

A Learning-Based Cooperative Coevolution Framework for Heterogeneous Large-Scale Global Optimization
by: Qiu, Wenjie, et al.
Published: (2026)

Structure as Computation: Developmental Generation of Minimal Neural Circuits
by: Zhou, Duan
Published: (2026)

No One-Size-Fits-All Neurons: Task-based Neurons for Artificial Neural Networks
by: Fan, Feng-Lei, et al.
Published: (2024)

BiSpikCLM: A Spiking Language Model integrating Softmax-Free Spiking Attention and Spike-Aware Alignment Distillation
by: Guo, Sihang, et al.
Published: (2026)

Continual Learning with Neuromorphic Computing: Foundations, Methods, and Emerging Applications
by: Minhas, Mishal Fatima, et al.
Published: (2024)

Modality-Dependent Memory Mechanisms in Cross-Modal Neuromorphic Computing
by: Blessing, Effiong, et al.
Published: (2025)

Brain-Inspired Spiking Neural Networks for Industrial Fault Diagnosis: A Survey, Challenges, and Opportunities
by: Wang, Huan, et al.
Published: (2023)

Evolutionary Computation and Explainable AI: A Roadmap to Understandable Intelligent Systems
by: Zhou, Ryan, et al.
Published: (2024)

VS-Graph: Scalable and Efficient Graph Classification Using Hyperdimensional Computing
by: Poursiami, Hamed, et al.
Published: (2025)

Task-free Adaptive Meta Black-box Optimization
by: Wang, Chao, et al.
Published: (2026)

Destroy and Repair Using Hyper Graphs for Routing
by: Li, Ke, et al.
Published: (2025)

MetaBox-v2: A Unified Benchmark Platform for Meta-Black-Box Optimization
by: Ma, Zeyuan, et al.
Published: (2025)

HyperGraphX: Graph Transductive Learning with Hyperdimensional Computing and Message Passing
by: Cong, Guojing, et al.
Published: (2025)

Sparsity Moves Computation: How FFN Architecture Reshapes Attention in Small Transformers
by: Smithline, Gabriel, et al.
Published: (2026)

CDRL: A Reinforcement Learning Framework Inspired by Cerebellar Circuits and Dendritic Computational Strategies
by: Zhang, Sibo, et al.
Published: (2026)

SpikySpace: A Spiking State Space Model for Energy-Efficient Time Series Forecasting
by: Tang, Kaiwen, et al.
Published: (2026)

ShiftLIF: Efficient Multi-Level Spiking Neurons with Power-of-Two Quantization
by: Tang, Kaiwen, et al.
Published: (2026)

EvoForest: A Novel Machine-Learning Paradigm via Open-Ended Evolution of Computational Graphs
by: Yuksel, Kamer Ali, et al.
Published: (2026)

Comply: Learning Sentences with Complex Weights inspired by Fruit Fly Olfaction
by: Figueroa, Alexei, et al.
Published: (2025)

Bridging Models to Defend: A Population-Based Strategy for Robust Adversarial Defense
by: Wang, Ren, et al.
Published: (2023)

Learning from Emergence: A Study on Proactively Inhibiting the Monosemantic Neurons of Artificial Neural Networks
by: Wang, Jiachuan, et al.
Published: (2023)

Fuzzy Recurrent Stochastic Configuration Networks for Industrial Data Analytics
by: Wang, Dianhui, et al.
Published: (2024)

Evolved Sample Weights for Bias Mitigation: Effectiveness Depends on the Fairness Objective
by: Saini, Anil K., et al.
Published: (2025)

A Novel Reservoir Computing Framework for Chaotic Time Series Prediction Using Time Delay Embedding and Random Fourier Features
by: Laha, S. K.
Published: (2025)

Benchmarking Fairness in Spiking Neural Networks: Data Bias, Spurious Features, and Hardware Effects
by: He, Hudi, et al.
Published: (2026)

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models
by: Wang, Ren-Jian, et al.
Published: (2025)

Rethinking LLM-Driven Heuristic Design: Generating Efficient and Specialized Solvers via Dynamics-Aware Optimization
by: Wang, Rongzheng, et al.
Published: (2026)

Knowledge-aware Evolutionary Graph Neural Architecture Search
by: Wang, Chao, et al.
Published: (2024)

Experience Replay Addresses Loss of Plasticity in Continual Learning
by: Wang, Jiuqi, et al.
Published: (2025)

Towards Universal Offline Black-Box Optimization via Learning Language Model Embeddings
by: Tan, Rong-Xi, et al.
Published: (2025)