Despite widespread industry recommendations, a new ETH Zurich paper concludes that AGENTS.md files may often hinder AI coding agents. The researchers recommend omitting LLM-generated context files ...
The training error decreases with increasing neuron count and plateaus beyond 28 neurons per hidden layer. For the two-hidden-layer network, error stabilization is ...
Abstract: This article proposes a novel constrained multiobjective evolutionary Bayesian optimization algorithm based on decomposition (named CMOEBO/D) for expensive constrained multiobjective ...
Machine learning models are increasingly applied across scientific disciplines, yet their effectiveness often hinges on heuristic decisions such as data transformations, training strategies, and model ...
Despite the vast diversity of human languages, specific grammatical patterns appear again and again. A new study reveals that around a third of the long-proposed "linguistic universals"—patterns ...
ABSTRACT: Mathematical optimization is a fundamental aspect of machine learning (ML). An ML task can be conceptualized as optimizing a specific objective using the training dataset to discern patterns ...
This repository contains experiment that implements Bayesian Optimization (BO) techniques for Conditional Value-at-Risk (CVaR)-based portfolio optimization, inspired by the research paper "Bayesian ...
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