On-device research index

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.

169,291 papers · 148 categories

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5 results for “GSLS”

Robust Graph Structure Learning with the Alignment of Features and Adjacency Matrixcs.LG

This paper improves GNN robustness by aligning feature and adjacency matrix learning.

problem Improving robustness of graph neural networks (GNN) in noisy graph data.

method Proposes a novel regularized GSL approach that aligns feature information and graph information, incorporating sparse dimensional reduction.

result Demonstrates superior performance in noisy graph structures compared to competitive baselines.

Graph Neural Networks Graph Structure Learning Feature Alignment Sparse Dimensional Reduction Noisy Graphs

2023-07-05abs ↗pdf ↗

A Generalized Framework for Simultaneous Long-Short Feedback Tradingq-fin.TR

A new trading strategy improves stock performance.

problem Improving stock trading performance using a generalized SLS framework.

method Developed a Generalized SLS (GSLS) trading strategy, tested on historical data, and optimized control parameters.

result Optimized GSLS strategy outperforms simpler SLS strategy and historical trading.

trading strategy GSLS stock performance control parameters historical data

2018-06-14abs ↗pdf ↗

Graph Structure Learning with Interpretable Bayesian Neural Networkscs.LG

Bayesian neural networks learn graph structure with interpretable parameters.

problem Learning graph structure from nodal observations in data with uncertainty.

method Introduces novel iterations with independently interpretable parameters and Bayesian neural networks.

result Bayesian neural networks provide well-calibrated uncertainty quantification on graph structure.

Bayesian neural networks graph structure learning interpretable parameters uncertainty quantification Markov Chain Monte Carlo

2024-06-20abs ↗pdf ↗

Hyperbolic Continuous Structural Entropy for Hierarchical Clusteringcs.LG

Proposes HypCSE for enhanced hierarchical clustering.

problem Challenges in existing hierarchical clustering methods.

method Hyperbolic Continuous Structural Entropy (HypCSE) neural networks.

result Superior performance on seven datasets.

Hierarchical Clustering Hyperbolic Space Graph Neural Networks Continuous Structural Entropy Lowest Common Ancestor

2025-11-29abs ↗pdf ↗

RKHSMetaMod: An R package to estimate the Hoeffding decomposition of a complex model by solving RKHS ridge group sparse optimization problemstat.ML

RKHSMetaMod estimates complex models' Hoeffding decomposition for sensitivity analysis.

problem Estimating the Hoeffding decomposition of complex models for sensitivity analysis.

method Penalized empirical least-squares minimization with RKHS ridge group sparse optimization.

result Estimates non-zero Sobol indices for sensitivity analysis.

Hoeffding decomposition meta-model sensitivity analysis RKHS ridge group sparse Sobol indices

2019-05-31abs ↗pdf ↗