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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.

168,932 papers · 148 categories

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0111 · Sep 201119922001200920172026
15 results for Terrorism

New approach predicts crime and terrorism events with high accuracy and transparency.

problem Predicting crime and terrorism events with high accuracy and interpretability.
method Granger Network inference for local transport rules learning.
result Achieved AUC of ~90% for crime predictions and ~80% for terrorism predictions.

New method predicts dynamic relationships in terrorist networks.

problem Dynamic co-evolution of multiplex graphs and nodal attributes in terrorism networks.
method Time-varying stochastic latent factor models with neural network Gaussian processes.
result Superior performance in predicting unobserved dynamic relationships.

Proposes a new model for complex multivariate event data.

problem Modeling complex multivariate event data with spatio-temporal dynamics.
method Integrates spatial information into latent state evolution through learned temporal and spatial decay dynamics.
result Successfully recovers sensible temporal and spatial intensity structure in multivariate spatio-temporal point patterns.

The objective of this research is to enhance performance of Stochastic Gradient Descent (SGD) algorithm in text classification. In our research, we proposed using SGD learning with Grid-Search approach to fine-tuning hyper-parameters in order to enhance the performance of SGD classification. We explored different setti…

2019-02-18abs ↗pdf ↗

'There is no terror in the bang, only is the anticipation of it' - Alfred Hitchcock. Yet there is everything in correctly anticipating the bang a movie would make in the box-office. Movies make a high profile, billion dollar industry and prediction of movie revenue can be very lucrative. Predicted revenues can be used …

2018-04-03abs ↗pdf ↗

Inspired by the tremendous success of deep generative models on generating continuous data like image and audio, in the most recent year, few deep graph generative models have been proposed to generate discrete data such as graphs. They are typically unconditioned generative models which has no control on modes of the …

2018-05-25abs ↗pdf ↗

A new model predicts discrete events with flexible, nonparametric baseline and excitation.

problem Limited flexibility in discrete Hawkes models for event prediction.
method Gaussian Process Discrete Hawkes Process (GP-DHP) with collapsed latent representation.
result Improves predictive log-likelihood for diverse event patterns.

Managers of US National Forests must decide what policy to apply for dealing with lightning-caused wildfires. Conflicts among stakeholders (e.g., timber companies, home owners, and wildlife biologists) have often led to spirited political debates and even violent eco-terrorism. One way to transform these conflicts into…

2017-03-28abs ↗pdf ↗

FCMs model feedback in complex systems, combining expert knowledge and statistical learning.

problem Modeling feedback in complex, interconnected systems.
method Fuzzy cognitive maps (FCMs) as fuzzy signed directed graphs, allowing for feedback loops and nonlinear dynamics.
result FCMs can better represent domain knowledge and simulate policy scenarios compared to DAGs.