惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

Y
Y Combinator Blog
博
博客园 - 司徒正美
TaoSecurity Blog
TaoSecurity Blog
Martin Fowler
Martin Fowler
T
Threat Research - Cisco Blogs
Blog — PlanetScale
Blog — PlanetScale
S
Secure Thoughts
博
博客园 - 三生石上(FineUI控件)
K
KPMG report finds enterprise disconnect between AI and its ROI | CIO
K
Kaspersky official blog
cs.CL updates on arXiv.org
cs.CL updates on arXiv.org
Cisco Talos Blog
Cisco Talos Blog
H
Help Net Security
博
博客园 - 叶小钗
爱范儿
爱范儿
GbyAI
GbyAI
I
Intezer
M
MIT News - Artificial intelligence
Latest news
Latest news
Schneier on Security
Schneier on Security
T
Tor Project blog
Simon Willison's Weblog
Simon Willison's Weblog
I
InfoQ
Threat Intelligence Blog | Flashpoint
Threat Intelligence Blog | Flashpoint
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
C
CXSECURITY Database RSS Feed - CXSecurity.com
罗
罗磊的独立博客
N
News and Events Feed by Topic
T
The Blog of Author Tim Ferriss
V2EX - 技术
V2EX - 技术
B
Blog
T
Tailwind CSS Blog
N
Netflix TechBlog - Medium
Security Latest
Security Latest
V
V2EX
F
Fortinet All Blogs
Forbes - Security
Forbes - Security
Application and Cybersecurity Blog
Application and Cybersecurity Blog
The Hacker News
The Hacker News
Scott Helme
Scott Helme
P
Privacy International News Feed
P
Palo Alto Networks Blog
H
Heimdal Security Blog
C
Cisco Blogs
T
The Exploit Database - CXSecurity.com
博
博客园 - Franky
酷 壳 – CoolShell
酷 壳 – CoolShell
G
Google Developers Blog
W
WeLiveSecurity
L
LINUX DO - 最新话题

cs.NE updates on arXiv.org

MPCS: Neuroplastic Continual Learning via Multi-Component Plasticity and Topology-Aware EWC Combining Trained Models in Reinforcement Learning Training Non-Differentiable Networks via Optimal Transport ShiftLIF: Efficient Multi-Level Spiking Neurons with Power-of-Two Quantization Probe-Geometry Alignment: Erasing the Cross-Sequence Memorization Signature Below Chance Benchmarking local Hebbian learning rules for memory storage and prototype extraction Robust volatility updates for Hierarchical Gaussian Filtering Spiking Sequence Machines and Transformers Affinity Is Not Enough: Recovering the Free Energy Principle in Mixture-of-Experts Scalable Learning in Structured Recurrent Spiking Neural Networks without Backpropagation Geometric and dynamical analysis of attractor boundaries and storage limits in kernel Hopfield networks Attractor FCM Physical Foundation Models: Fixed hardware implementations of large-scale neural networks When Does Structure Matter in Continual Learning? Dimensionality Controls When Modularity Shapes Representational Geometry Learning to Forget: Continual Learning with Adaptive Weight Decay Causal Learning with Neural Assemblies NORACL: Neurogenesis for Oracle-free Resource-Adaptive Continual Learning Text-Utilization for Encoder-dominated Speech Recognition Models EdgeSpike: Spiking Neural Networks for Low-Power Autonomous Sensing in Edge IoT Architectures EvoTSC: Evolving Feature Learning Models for Time Series Classification via Genetic Programming Analysis and Explainability of LLMs Via Evolutionary Methods Deployment-Aligned Low-Precision Neural Architecture Search for Spaceborne Edge AI SeaEvo: Advancing Algorithm Discovery with Strategy Space Evolution Primitive Recursion without Composition: Dynamical Characterizations, from Neural Networks to Polynomial ODEs MAEO: Multiobjective Animorphic Ensemble Optimization for Scalable Large-scale Engineering Applications Necessary and sufficient conditions for universality of Kolmogorov-Arnold networks Learn&Drop: Fast Learning of CNNs based on Layer Dropping Architecture-Induced Recoverability Bias in Differentiable Symbolic Regression Collocation-based Robust Physics Informed Neural Networks for time-dependent simulations of pollution propagation under thermal inversion conditions on Spitsbergen Structure-Guided Diffusion Model for EEG-Based Visual Cognition Reconstruction HubRouter: A Pluggable Sub-Quadratic Routing Primitive for Hybrid Sequence Models A Co-Evolutionary Theory of Human-AI Coexistence: Mutualism, Governance, and Dynamics in Complex Societies LTBs-KAN: Linear-Time B-splines Kolmogorov-Arnold Networks Multi-Task Optimization over Networks of Tasks Geometric Monomial (GEM): a family of rational 2N-differentiable activation functions On the Role of Preprocessing and Memristor Dynamics in Reservoir Computing for Image Classification Trust-SSL: Additive-Residual Selective Invariance for Robust Aerial Self-Supervised Learning Focus Session: Hardware and Software Techniques for Accelerating Multimodal Foundation Models An explicit operator explains end-to-end computation in the modern neural networks used for sequence and language modeling Distributional Value Estimation Without Target Networks for Robust Quality-Diversity EvoJail: Evolutionary Diverse Jailbreak Prompt Generation for Large Language Models Where to Bind Matters: Hebbian Fast Weights in Vision Transformers for Few-Shot Character Recognition What Makes an LLM a Good Optimizer? A Trajectory Analysis of LLM-Guided Evolutionary Search Scalable Memristive-Friendly Reservoir Computing for Time Series Classification Large Language Models Exhibit Normative Conformity Prototype-Grounded Concept Models for Verifiable Concept Alignment ECG-Lens: Benchmarking ML & DL Models on PTB-XL Dataset What Makes a Bacterial Model a Good Reservoir Computer? Predicting Performance from Separability and Similarity Neuromorphic Parameter Estimation for Power Converter Health Monitoring Using Spiking Neural Networks Why Fine-Tuning Encourages Hallucinations and How to Fix It Beyond Single-Model Optimization: Preserving Plasticity in Continual Reinforcement Learning Structure as Computation: Developmental Generation of Minimal Neural Circuits NEAT-NC: NEAT guided Navigation Cells for Robot Path Planning Neural architectures for resolving references in program code Diffusion Language Models for Speech Recognition A Dynamic-Growing Fuzzy-Neuro Controller, Application to a 3PSP Parallel Robot On the Use of Evolutionary Optimization for the Dynamic Chance Constrained Open-Pit Mine Scheduling Problem Analog Optical Inference on Million-Record Mortgage Data Shapley Value-Guided Adaptive Ensemble Learning for Explainable Financial Fraud Detection with U.S. Regulatory Compliance Validation Does Dimensionality Reduction via Random Projections Preserve Landscape Features? Agent-GWO: Collaborative Agents for Dynamic Prompt Optimization in Large Language Models Neuromorphic Continual Learning for Sequential Deployment of Nuclear Plant Monitoring Systems Beyond LLMs, Sparse Distributed Memory, and Neuromorphics <A Hyper-Dimensional SRAM-CAM "VaCoAl" for Ultra-High Speed, Ultra-Low Power, and Low Cost> SpikeMLLM: Spike-based Multimodal Large Language Models via Modality-Specific Temporal Scales and Temporal Compression Evolving Many Worlds: Towards Open-Ended Discovery in Petri Dish NCA via Population-Based Training Frugal Knowledge Graph Construction with Local LLMs: A Zero-Shot Pipeline, Self-Consistency and Wisdom of Artificial Crowds Retinal Cyst Detection from Optical Coherence Tomography Images TurboEvolve: Towards Fast and Robust LLM-Driven Program Evolution Universal statistical signatures of evolution in artificial intelligence architectures Wolkowicz-Styan Upper Bound on the Hessian Eigenspectrum for Cross-Entropy Loss in Nonlinear Smooth Neural Networks Sequential KV Cache Compression via Probabilistic Language Tries: Beyond the Per-Vector Shannon Limit Evolutionary Token-Level Prompt Optimization for Diffusion Models Hierarchical Kernel Transformer: Multi-Scale Attention with an Information-Theoretic Approximation Analysis A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need Multi-Modal Learning meets Genetic Programming: Analyzing Alignment in Latent Space Optimization OpenCLAW-P2P v7.0-P2PCLAW: Resilient Multi-Layer Persistence, Live Reference Verification, and Production-Scale Evaluation of Decentralized AI Peer Review v7.0 -- Mathematical Corrections & Ecosystem Developments Edition An Imbalanced Dataset with Multiple Feature Representations for Studying Quality Control of Next-Generation Sequencing Selectivity and Shape in the Design of Forward-Forward Goodness Functions Efficient Disruption of Criminal Networks through Multi-Objective Genetic Algorithms DarwinNet: An Evolutionary Network Architecture for Agent-Driven Protocol Synthesis EvoForest: A Novel Machine-Learning Paradigm via Open-Ended Evolution of Computational Graphs Evolving Multi-Channel Confidence-Aware Activation Functions for Missing Data with Channel Propagation Rethinking LLM-Driven Heuristic Design: Generating Efficient and Specialized Solvers via Dynamics-Aware Optimization Discount Model Search for Quality Diversity Optimization in High-Dimensional Measure Spaces QSLM: A Performance- and Memory-aware Quantization Framework with Tiered Search Strategy for Spike-driven Language Models Optimized Architectures for Kolmogorov-Arnold Networks AP-BMM: Approximating Capability-Cost Pareto Sets of LLMs via Asynchronous Prior-Guided Bayesian Model Merging Transformer Semantic Genetic Programming for d-dimensional Symbolic Regression Problems Efficient Vector Symbolic Architectures from Histogram Recovery Language Models Learn Universal Representations of Numbers and Here's Why You Should Care A Practitioner's Guide to Kolmogorov-Arnold Networks Symbolic Quantile Regression for the Interpretable Prediction of Conditional Quantiles PBiLoss: Popularity-Aware Regularization to Improve Fairness in Graph-Based Recommender Systems HiPreNets: High-Precision Neural Networks through Progressive Training Machine Learning as Iterated Belief Change a la Darwiche and Pearl Transformer-Empowered Actor-Critic Reinforcement Learning for Sequence-Aware Service Function Chain Partitioning Scalable Multi-Task Learning through Spiking Neural Networks with Adaptive Task-Switching Policy for Intelligent Autonomous Agents Learning Evolution via Optimization Knowledge Adaptation Frame forecasting in cine MRI using the PCA respiratory motion model: comparing recurrent neural networks trained online and transformers P1-KAN: an effective Kolmogorov-Arnold network with application to hydraulic valley optimization
Who is the best connected EC researcher? Centrality analysis of the complex network of authors in evolutionary computation
Juan J. Merelo, Carlos Cotta · 2007-08-15 · via cs.NE updates on arXiv.org

Co-authorship graphs (that is, the graph of authors linked by co-authorship of papers) are complex networks, which expresses the dynamics of a complex system. Only recently its study has started to draw interest from the EC community, the first paper dealing with it having been published two years ago. In this paper we will study the co-authorship network of EC at a microscopic level. Our objective is ascertaining which are the most relevant nodes (i.e. authors) in it. For this purpose, we examine several metrics defined in the complex-network literature, and analyze them both in isolation and combined within a Pareto-dominance approach. The result of our analysis indicates that there are some well-known researchers that appear systematically in top rankings. This also provides some hints on the social behavior of our community.

此内容由惯性聚合(RSS阅读器)自动聚合整理，仅供阅读参考。 原文来自 — 版权归原作者所有。