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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,657 papers · 148 categories

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0111 · Jun 202019922001200920172026
3 results for “meta-variables”
A distance for mixed-variable and hierarchical domains with meta variablesstat.ML

A new distance for mixed-variable, hierarchical datasets with meta variables.

problem Heterogeneous datasets limit generalizability and performance in machine learning and optimization.
method Developed a modeling framework for mixed-variable and hierarchical domains with meta variables, and a novel distance function.
result The novel distance function allows comparison of heterogeneous datasets, improving model performance.
distance functionmixed-variablehierarchical domainsmeta variablesmachine learning
2024-05-20abs ↗pdf ↗
Automatically Learning Compact Quality-aware Surrogates for Optimization Problemscs.LG

We learn a compact surrogate model for optimization problems to reduce training and inference time.

problem Solving optimization problems with unknown parameters is computationally expensive and may lead to suboptimal solutions.
method We represent the optimization problem in terms of meta-variables and learn a low-dimensional surrogate model end-to-end with the predictive model.
result We achieve a large reduction in training and inference time, and improved performance.
optimizationsurrogate modelingmeta-variablesmeta-compositionmeta-optimization
2020-06-18abs ↗pdf ↗
Modeling Hierarchical Spaces: A Review and Unified Framework for Surrogate-Based Architecture Designcs.LG

Unified framework for modeling hierarchical spaces in design problems.

problem Challenges in modeling hierarchical, conditional, heterogeneous, or tree-structured domains.
method Unified framework combining feature modeling and graph theory, introducing meta and partially-decreed variables.
result Demonstrated effectiveness on complex system design problems, including neural networks and green-aircraft.
hierarchical spacesmeta variablespartially-decreed variablesdesign space graphssurrogate modeling
2025-06-27abs ↗pdf ↗