Decorrelation, Diversity, and Emergent Intelligence: The Isomorphism Between Social Insect Colonies and Ensemble Machine Learning

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Fokoué, Ernest, Babbitt, Gregory, Levental, Yuval
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Machine Learning 68T05, 62G08, 62C10, 92B05, 68W15
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Isomorphic Functionalities between Ant Colony and Ensemble Learning: Part III -- Gradient Descent, Neural Plasticity, and the Emergence of Deep Intelligence
di: Fokoué, Ernest, et al.
Pubblicazione: (2026)

Isomorphic Functionalities between Ant Colony and Ensemble Learning: Part II-On the Strength of Weak Learnability and the Boosting Paradigm
di: Fokoué, Ernest, et al.
Pubblicazione: (2026)

Multi-Head Attention as Ensemble Nadaraya-Watson Estimation: Variance Reduction, Decorrelation, and Optimal Head Diversity
di: Fokoué, Ernest
Pubblicazione: (2026)

Fibonacci-Driven Recursive Ensembles: Algorithms, Convergence, and Learning Dynamics
di: Fokoué, Ernest
Pubblicazione: (2026)

Causality as the Statistical Conscience of Artificial Intelligence: From Pearl's Ladder to Trustworthy Machines
di: Fokoué, Ernest
Pubblicazione: (2026)

A General Weighting Theory for Ensemble Learning: Beyond Variance Reduction via Spectral and Geometric Structure
di: Fokoué, Ernest
Pubblicazione: (2025)

On Fibonacci Ensembles: An Alternative Approach to Ensemble Learning Inspired by the Timeless Architecture of the Golden Ratio
di: Fokoué, Ernest
Pubblicazione: (2025)

Extensions of the regret-minimization algorithm for optimal design
di: Chen, Youguang, et al.
Pubblicazione: (2025)

A PAC-Bayes oracle inequality for sparse neural networks
di: Steffen, Maximilian F., et al.
Pubblicazione: (2022)

Estimating Unbounded Density Ratios: Applications in Error Control under Covariate Shift
di: Xu, Shuntuo, et al.
Pubblicazione: (2025)

Wasserstein Distributionally Robust Nonparametric Regression
di: Liu, Changyu, et al.
Pubblicazione: (2025)

Computing conservative probabilities of rare events with surrogates
di: Bousquet, Nicolas
Pubblicazione: (2024)

From Conditional to Unconditional Independence: Testing Conditional Independence via Transport Maps
di: He, Chenxuan, et al.
Pubblicazione: (2025)

Semiparametric Spatiotemporal Model with Mixed Frequencies
di: Malabanan, Vladimir A., et al.
Pubblicazione: (2021)

Weak Signals and Heavy Tails: Learning Theory meets Extreme Value Analysis
di: Clémençon, Stephan, et al.
Pubblicazione: (2025)

Data-driven Error Estimation: Excess Risk Bounds without Class Complexity as Input
di: Krishnamurthy, Sanath Kumar, et al.
Pubblicazione: (2024)

Machine Collaboration
di: Liu, Qingfeng, et al.
Pubblicazione: (2021)

Distributed Sparse Linear Regression under Communication Constraints
di: Fonseca, Rodney, et al.
Pubblicazione: (2023)

Computing k-means in mixed precision
di: Carson, Erin, et al.
Pubblicazione: (2024)

The Impact of Formations on Football Matches Using Double Machine Learning. Is it worth parking the bus?
di: Ruiz-Menárguez, Genís, et al.
Pubblicazione: (2026)

Structure and Sensitivity in Differential Privacy: Comparing K-Norm Mechanisms
di: Awan, Jordan, et al.
Pubblicazione: (2018)

CRPS-Optimal Binning for Univariate Conformal Regression
di: Toccaceli, Paolo
Pubblicazione: (2026)

Quantile Additive Trend Filtering
di: Zhang, Zhi, et al.
Pubblicazione: (2023)

Transcendental Regularization of Finite Mixtures:Theoretical Guarantees and Practical Limitations
di: Fokoué, Ernest
Pubblicazione: (2026)

Reinforcement Learning with Action-Triggered Observations
di: Ryabchenko, Alexander, et al.
Pubblicazione: (2025)

Batched Nonparametric Bandits via k-Nearest Neighbor UCB
di: Arya, Sakshi
Pubblicazione: (2025)

Gaussian Ensemble Belief Propagation for Efficient Inference in High-Dimensional Systems
di: MacKinlay, Dan, et al.
Pubblicazione: (2024)

Conformal e-prediction
di: Vovk, Vladimir
Pubblicazione: (2020)

RotorMap and Quantum Fingerprints of DNA Sequences via Rotary Position Embeddings
di: Yakymenko, Danylo, et al.
Pubblicazione: (2026)

Dynamic Regret for Online Regression in RKHS via Discounted VAW and Subspace Approximation
di: Rokhlin, Dmitry B., et al.
Pubblicazione: (2026)

Ultrafast topological data analysis reveals pandemic-scale dynamics of convergent evolution
di: Bleher, Michael, et al.
Pubblicazione: (2021)

Ranking Perspective for Tree-based Methods with Applications to Symbolic Feature Selection
di: Luo, Hengrui, et al.
Pubblicazione: (2024)

Anchored Likelihood-Ratio Geometry of Anonymous Shuffle Experiments: Exact Privacy Envelopes and Universal Low-Budget Design
di: Shvets, Alex
Pubblicazione: (2026)

Bayesian D-Optimal Experimental Designs via Column Subset Selection
di: Eswar, Srinivas, et al.
Pubblicazione: (2024)

Analyzing directional errors in spatial orientation using nonparametric circular regression with mixed covariates
di: Francisco-Fernández, Mario, et al.
Pubblicazione: (2026)

Inductive Venn-Abers and related regressors
di: Petej, Ivan, et al.
Pubblicazione: (2026)

Constructive interpolation and generalization rates for neural ODEs: a control perspective
di: Álvarez-López, Antonio, et al.
Pubblicazione: (2026)

Kernel $ε$-Greedy for Multi-Armed Bandits with Covariates
di: Arya, Sakshi, et al.
Pubblicazione: (2023)

On the Convergence of the ELBO to Entropy Sums
di: Lücke, Jörg, et al.
Pubblicazione: (2022)

Generative Models with ELBOs Converging to Entropy Sums
di: Warnken, Jan, et al.
Pubblicazione: (2024)