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20222026
most citedParallel Approaches to Accelerate Bayesian Decision Trees

1 citations · 1 across the 5 of their papers we have counts for

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5 papers

cs.GT2026

Game-Theoretic Foundations of Competition for Conscious Access

Efthyvoulos Drousiotis, Paul Spirakis, Sotiris Nikoletseas

Conscious access in the human brain is often described as the outcome of a competition among candidate representations, but this competition is usually left at the level of mechani…

cs.GT2026

A Tractability Boundary for Exclusion Zones in Instant-Runoff Voting: Planar Versus One-Apex Graphs

Georgios Birmpas, Georgios Chionas, Efthyvoulos Drousiotis +3

We study exclusion zones for instant-runoff voting (IRV) on connected, unweighted graphs. Each vertex hosts one voter and may host a candidate. Voters rank candidates by shortest-p…

cs.LG2023

Bayesian Decision Trees Inspired from Evolutionary Algorithms

Efthyvoulos Drousiotis, Alexander M. Phillips, Paul G. Spirakis +1

Bayesian Decision Trees (DTs) are generally considered a more advanced and accurate model than a regular Decision Tree (DT) because they can handle complex and uncertain data. Exis…

stat.CO2023★ 1 cited

Parallel Approaches to Accelerate Bayesian Decision Trees

Efthyvoulos Drousiotis, Paul G. Spirakis, Simon Maskell

Markov Chain Monte Carlo (MCMC) is a well-established family of algorithms primarily used in Bayesian statistics to sample from a target distribution when direct sampling is challe…

cs.AI2022

Single MCMC Chain Parallelisation on Decision Trees

Efthyvoulos Drousiotis, Paul G. Spirakis

Decision trees are highly famous in machine learning and usually acquire state-of-the-art performance. Despite that, well-known variants like CART, ID3, random forest, and boosted…