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.

169,051 papers · 148 categories

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11 results for “SCN”

Two Dimensional Stochastic Configuration Networks for Image Data Analyticscs.LG

2DSCNs improve image data analytics by extending SCN to handle spatial information.

problem Limitation of 1D SCNs in preserving spatial information of images.

method Extend SCN to 2DSCNs by stochastically configuring hidden nodes in a matrix-inputs framework.

result 2DSCNs outperform 1D SCNs in image data analytics tasks.

SCNs 2DSCNs image data analytics spatial information randomized learners

2018-09-06abs ↗pdf ↗

Recurrent Control Nets for Deep Reinforcement Learningcs.LG

RCNs match and exceed MLPs and SCNs in reinforcement learning tasks.

problem Efficiently learning rhythmic motion in reinforcement learning.

method Combining RNNs and SCN structures to create RCNs.

result RCNs outperform MLPs and SCNs across all environment tasks.

Reinforcement Learning RNNs SCNs Rhythmic Motion Control Nets

2019-01-06abs ↗pdf ↗

Bias Reduction via End-to-End Shift Learning: Application to Citizen Sciencecs.LG

SCN learns and compensates for data bias in citizen science projects.

problem Data bias in citizen science datasets.

method End-to-end learning scheme that learns and compensates for data shift.

result SCN outperforms models that ignore data bias and handles massive high-dimensional data.

Citizen Science Data Bias Shift Learning SCN Bird Observational Data

2018-11-01abs ↗pdf ↗

Estimating the impact of supply chain network contagion on financial stabilityq-fin.ST

Study quantifies financial contagion risks in supply chains.

problem Supply chain shocks contribute to financial losses.

method Multi-layer network framework, micro-dataset of Hungarian firms.

result Supply chain shocks amplify financial losses by 4-3x.

financial contagion supply chain systemic risk credit risk Hungary

2023-05-04abs ↗pdf ↗

An end-to-end convolutional selective autoencoder approach to Soybean Cyst Nematode eggs detectioncs.CV

This paper proposes a novel selective autoencoder approach within the framework of deep convolutional networks. The crux of the idea is to train a deep convolutional autoencoder to suppress undesired parts of an image frame while allowing the desired parts resulting in efficient object detection. The efficacy of the fr…

2016-03-25abs ↗pdf ↗

Inferring firm-level supply chain networks with realistic systemic risk from industry sector-level dataphysics.soc-ph

Researchers infer firm-level supply chain networks from sector-level data to assess systemic risk.

problem Estimating systemic risk in economic systems using firm-level data.

method Maximum-entropy algorithms applied to input-output tables and firm-level aggregate output data.

result The most realistic systemic risk content is retrieved by models incorporating disaggregated firm-specific inputs by sector.

supply chain networks systemic risk economic system firm-level data input-output tables

2024-08-05abs ↗pdf ↗

Time Evolution of a Supply Chain Network: Kinetic Modelingcond-mat.stat-mech

Model predicts time evolution of supply chain networks under varying costs.

problem Regulating downstream relationships for sustainable SMEs.

method Time varying SCN model based on Lagrangian mechanics, incorporating EDES cost kernels.

result Model predicts bankruptcy and break-even states under different cost scenarios.

Supply Chain Network Sustainable SME Time Evolution Lagrangian Mechanics Economic Inertia

2022-09-02abs ↗pdf ↗

Deep Stacked Stochastic Configuration Networks for Lifelong Learning of Non-Stationary Data Streamscs.LG

DSSCN improves lifelong learning of non-stationary data streams through adaptive network construction.

problem Lifelong learning of non-stationary data streams with efficient and adaptive models.

method Deep stacked stochastic configuration network (DSSCN) with self-constructing deep stacked network structure and adaptive hidden unit parameters.

result DSSCN outperforms existing data stream algorithms in continual learning of non-stationary data streams.

Lifelong learning Non-stationary data streams Deep stacked networks Adaptive structure Inverse covariance matrix

2018-08-07abs ↗pdf ↗

Stochastic Newton and Cubic Newton Methods with Simple Local Linear-Quadratic Ratescs.LG

Simple stochastic Newton and cubic Newton methods with fast convergence.

problem Minimizing large numbers of smooth and strongly convex functions.

method Stochastic Newton and cubic Newton methods with simple local linear-quadratic rates.

result Local linear-quadratic convergence results with fast adaptation to problem's curvature.

Newton methods stochastic optimization second-order methods local linear-quadratic convergence cubic regularization

2019-12-03abs ↗pdf ↗

Self-Organizing Recurrent Stochastic Configuration Networks for Nonstationary Data Modellingcs.LG

SORSCNs improve nonstationary data modeling by self-organizing and adjusting network parameters.

problem Nonstationary data challenges traditional models in continuous learning.

method SORSCNs autonomously adjust network parameters and structure in real-time using adaptive algorithms.

result SORSCNs outperform other models in generalizing to nonstationary data.

nonstationary data self-organizing recurrent stochastic configuration networks continuous learning nonlinear dynamics

2024-10-14abs ↗pdf ↗

Limits of Entrainment of Circadian Neuronal Networksq-bio.NC

Study limits of circadian synchronization under different light signals.

problem Disruption of circadian rhythms due to misalignment with external light signals.

method Matrix-free approach for locating periodic steady states, numerical continuation, bifurcation diagrams, unsupervised learning.

result Limits of circadian synchronization to external light signals of different frequency and duty cycle.

circadian rhythms neuronal networks Suprachiasmatic Nucleus light signals bifurcation diagrams

2022-08-23abs ↗pdf ↗