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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.

168,695 papers · 148 categories

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4 results for “order-reducibility”

The fundamental Lepage form in two independent variables: a generalization using order-reducibilitymath.DG

A generalized Lepage form for second-order Lagrangians is described.

problem Finding a Lepage equivalent for second-order Lagrangians.

method Using equivalence relation and preserving the order of Lagrangians.

result Completes attempts to find a Lepage equivalent for second-order Lagrangians.

Lepage form geometric calculus fibered manifolds order-reducibility Lagrangian

2022-04-04abs ↗pdf ↗

Higher Order Reduced Rank Regressionstat.ML

Extends RRR to capture nonlinear interactions in multi-response regression.

problem Complex relationships in real-world data cannot be adequately modeled by linear interactions.

method Introduces Higher Order Reduced Rank Regression (HORRR) using tensor representations and Tucker decomposition.

result HORRR can capture nonlinear interactions in multi-response regression.

Reduced Rank Regression Higher Order Nonlinear Interactions Tensor Representations Tucker Decomposition

2025-03-09abs ↗pdf ↗

A Multivariate Bernoulli-Based Sampling Method for Multi-Label Data with Application to Meta-Researchcs.LG

A new sampling method balances multi-label datasets by preserving category frequency order.

problem Sampling challenges in multi-label datasets with varying label frequencies.

method Uses multivariate Bernoulli distribution and label dependencies to estimate and weight label combinations.

result Produces a more balanced sub-sample with enhanced representation of minority categories.

sampling multi-label Bernoulli distribution label dependencies category frequency

2025-12-09abs ↗pdf ↗

A Quadratic Order Reduction -- Gaussian Process Ordinary Differential Equation framework for the inference of Large Continuous Dynamical Systemsmath.NA

A Gaussian Process Ordinary Differential Equation framework for large continuous dynamical systems

problem Forecasting complex dynamical systems

method Kernel autonomous ODE approach based on Gaussian Processes and Quadratic Order Model Reduction

result Full model outperforms ROM methods in terms of accuracy or computational costs

Gaussian Process Ordinary Differential Equation ROM Uncertainty Quantification

2026-06-11abs ↗pdf ↗