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.

168,878 papers · 148 categories

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7 results for “RBFNN”

Spatio-Temporal RBF Neural Networksstat.ML

Improved RBFNN for nonlinear system identification.

problem Nonlinear system identification problem.

method Spatio-temporal extension of RBFNN with time-space orthogonality.

result Spatio-temporal RBFNN outperforms standard RBFNN in convergence and error reduction.

RBFNN nonlinear system spatio-temporal orthogonality system identification

2019-08-04abs ↗pdf ↗

Canonical dual solutions to nonconvex radial basis neural network optimization problemcs.NE

Radial Basis Functions Neural Networks (RBFNNs) are tools widely used in regression problems. One of their principal drawbacks is that the formulation corresponding to the training with the supervision of both the centers and the weights is a highly non-convex optimization problem, which leads to some fundamentally dif…

2013-02-18abs ↗pdf ↗

Multi-Kernel Fusion for RBF Neural Networkscs.LG

A new multi-kernel RBFNN design improves performance and speed.

problem Improving the performance and speed of RBFNNs.

method Proposes a novel multi-kernel RBFNN where each base kernel has its own weight.

result Better performance gains including faster convergence, better local minima, and resilience against poor local minima.

RBF neural networks multi-kernel performance improvement convex combination local minima

2020-07-06abs ↗pdf ↗

Online High-Frequency Trading Stock Forecasting with Automated Feature Clustering and Radial Basis Function Neural Networksq-fin.ST

Study automates feature selection and clustering for HFT stock price forecasting.

problem Manual feature selection and clustering for high-frequency trading (HFT) stock price forecasting.

method Dual competitive feature importance mechanism and clustering via shallow neural network topology.

result Enhanced forecasting ability of the RBFNN regressor through automated feature selection and clustering.

high-frequency trading stock forecasting feature selection neural networks radial basis function

2024-11-23abs ↗pdf ↗

Chaotic Time Series Prediction using Spatio-Temporal RBF Neural Networksstat.ML

Spatio-temporal RBF neural networks improve chaotic time series prediction.

problem Predicting chaotic time series due to their dynamic nature.

method Proposes an spatio-temporal extension of RBF neural networks.

result Spatio-temporal RBF outperforms standard RBF in chaotic time series prediction.

chaotic time series RBF neural networks spatio-temporal Mackey-Glass prediction

2019-08-17abs ↗pdf ↗

Minimal Batch Adaptive Learning Policy Engine for Real-Time Mid-Price Forecasting in High-Frequency Tradingq-fin.ST

ALPE improves mid-price forecasting in HFT with real-time data.

problem Real-time mid-price forecasting in high-frequency trading.

method Adaptive Learning Policy Engine (ALPE) using RL and adaptive epsilon decay.

result ALPE outperforms other models in mid-price forecasting.

High-frequency trading Mid-price forecasting Reinforcement learning Real-time data Adaptive epsilon decay

2024-12-26abs ↗pdf ↗

Learning Active Subspaces and Discovering Important Features with Gaussian Radial Basis Functions Neural Networkscs.LG

Proposes a neural network model to learn active subspaces and interpret important features.

problem Achieving strong predictive performance and human-interpretable models in machine learning.

method Modified Gaussian radial basis function neural network with learnable precision matrix.

result Extracts active subspaces and interpretable rankings of input variables.

machine learning neural networks interpretability active subspaces feature selection

2023-07-11abs ↗pdf ↗