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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.

168,657 papers · 148 categories

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48 results for incidence graphs

In a recent work of Ayaka Shimizu[5]^{[5]}, she defined an operation named region crossing change on link diagrams, and showed that region crossing change is an unknotting operation for knot diagrams. In this paper, we prove that region crossing change on a 2-component link diagram is an unknotting operation if and only…

2011-01-06abs ↗pdf ↗

The paper explains the topological origin of the distinction between incidence theorems over division rings and fields.

problem Understanding the distinction between incidence theorems over division rings and fields.
method Extending the surface-graph approach to noncommutative settings, the paper analyzes the topological properties of graphs embedded on surfaces of different genera.
result Theorems associated with graphs on the sphere hold over any division ring, while those on surfaces of positive genus typically hold only if the ground ring is a field.

Sparse incidence tensors can represent a variety of structured data. For example, we may represent attributed graphs using their node-node, node-edge, or edge-edge incidence matrices. In higher dimensions, incidence tensors can represent simplicial complexes and polytopes. In this paper, we formalize incidence tensors,…

2019-05-27abs ↗pdf ↗

The intersection pattern of the translates of the limit set of a quasi-convex subgroup of a hyperbolic group can be coded in a natural incidence graph, which suggests connections with the splittings of the ambient group. A similar incidence graph exists for any subgroup of a group. We show that the disconnectedness of …

2009-06-05abs ↗pdf ↗

This paper addresses questions of quasi-isometric rigidity and classification for fundamental groups of finite graphs of groups, under the assumption that the Bass-Serre tree of the graph of groups has finite depth. The main example of a finite depth graph of groups is one whose vertex and edge groups are coarse Poinca…

2004-05-13abs ↗pdf ↗

Symmetric TSP is structurally equivalent to a constrained Group Steiner Tree Problem.

problem Finding the shortest tour in a symmetric TSP.
method Structural equivalence between symmetric TSP and constrained Group Steiner Tree Problem.
result Maximizing net weight in the cGSTP is equivalent to minimizing the TSP tour length.

Given a bordified space, Karlsson defines an incidence geometry of stars at infinity. These stars and their incidence are closely related to well-understood objects when the space is hyperbolic, CAT(0), or a bounded convex domain with the Hilbert metric. A question stemming from Karlsson's original paper was whether or…

2020-01-17abs ↗pdf ↗

The paper extends group constructions to coset geometries, creating new ways to combine geometries.

problem Combining and gluing incidence geometries in a general framework.
method Extending classical group-theoretic constructions to coset geometries.
result Provides a general framework for combining or gluing incidence geometries.

CT improves neural network performance on cell complex data.

problem Improving predictive performance of neural networks on complex data.
method Introducing the Cellular Transformer (CT) that generalizes graph-based transformers to cell complexes.
result CT achieves state-of-the-art performance on cell complex datasets without complex enhancements.

A ``hyperideal circle pattern'' in S2S^2 is a finite family of oriented circles, similar to the ``usual'' circle patterns but such that the closed disks bounded by the circles do not cover the whole sphere. Hyperideal circle patterns are directly related to hyperideal hyperbolic polyhedra, and also to circle packings. …

2004-07-03abs ↗pdf ↗

Crowdsourced data helps detect incidents faster, balancing accuracy and practicality.

problem Detecting incidents from crowdsourced data is challenging due to noise and uncertainty.
method CROME (Crowdsourced Multi-objective Event Detection) uses CNN and Pareto optimization.
result The approach outperforms existing methods in incident detection and practicality.

Study uses vehicle trajectory data to predict traffic incidents on highways.

problem Early detection of traffic incidents to reduce secondary crashes.
method Machine learning algorithms (Logistic Regression, Random Forest, Extreme Gradient Boost, Artificial Neural Network) applied to vehicle trajectory data.
result Random Forest model performs best for incident prediction.

HYVINT generates hypergraphs with intensity-driven incidence formation and variational learning.

problem Challenges in generating hypergraphs with mechanistic interpretation and limited latent space.
method HYVINT uses intensity-driven incidence formation and a lower-bound variational estimator for latent representations.
result HYVINT achieves strong fidelity and novelty on synthetic and real-world hypergraphs.

New algorithm estimates edge density of random graphs robustly, achieving optimal breakdown point.

problem Estimating edge density of Erdős-Rényi graphs under adversarial edge manipulation.
method Sum-of-Squares (SoS) hierarchy, constructing constant-degree certificates for concentration.
result First polynomial-time algorithm with optimal breakdown point and matching error guarantees.

Study shows data breaches cause significant financial losses for firms, especially in health sector.

problem Understanding the economic impact of cyber incidents on listed firms.
method Event study using abnormal returns over 2012-2022, adjusting for event-induced variance and residual cross-correlation.
result Data breaches cause significant financial losses for firms, especially in health sector.

Automated suggestions help train technicians diagnose incidents faster.

problem Manual and time-consuming incident diagnosis by train maintenance technicians.
method Developed and deployed a learning machine to suggest diagnostics to technicians.
result The model refines its accuracy through feedback from experts and uses feature engineering.

This paper presents a construction of fibered links (K,Σ)(K,Σ) out of chord diagrams $\sL$. Let ΓΓ be the incidence graph of $\sL$. Under certain conditions on $\sL$ the symmetrized Seifert matrix of (K,Σ)(K,Σ) equals the bilinear form of the simply-laced Coxeter system (W,S)(W,S) associated to ΓΓ; and the monodromy of $(K,Σ)…

2002-04-02abs ↗pdf ↗

This paper proposes a real-time signal plan recommendation system for traffic incidents.

problem Limited effectiveness of traffic incident management due to late response and workload.
method Decomposes recommendation task into real-time traffic prediction and plan association, learning from historical data and metric learning.
result Precision score of 96.75% and recall of 87.5% on testing plan, with 22.5 minutes lead time ahead of Waze alerts.

The paper studies how points and lines can move while preserving incidences.

problem Understanding how point-line configurations can move while maintaining their geometric relationships.
method Developed a projective rigidity matrix to analyze the infinitesimal motions and dependencies of point-line configurations.
result The symmetry-adapted projective rigidity matrix provides a more detailed analysis of symmetric configurations and their motions.

Crimes emerge out of complex interactions of human behaviors and situations. Linkages between crime incidents are highly complex. Detecting crime linkage given a set of incidents is a highly challenging task since we only have limited information, including text descriptions, incident times, and locations. In practice,…

2019-02-01abs ↗pdf ↗

Develops regression trees for estimating cumulative incidence curves in competing risks.

problem Estimating cumulative incidence functions in competing risks settings.
method Uses augmented estimators of the Brier score risk to build and prune regression trees.
result Demonstrates the utility of the proposed methods through simulation studies and real data.

Enhances cyber risk assessment with entity-specific features.

problem Lack of high-quality public cyber incident data.
method Develops an InsurTech framework to enrich cyber incident data with entity-specific attributes and implements machine learning models.
result InsurTech features improve prediction robustness and provide customized risk profiles.

This study examines how removing edges from complete graphs affects Ollivier Ricci curvature.

problem Conditions under which Ollivier Ricci curvature changes sign after edge removal.
method Defined and analyzed graphs obtained by removing matching, vertex incident, and cycle edges from complete graphs.
result Ollivier Ricci curvature remains positive or zero for graphs formed by removing edges from complete graphs.

Study finds companies react negatively to material cybersecurity incident disclosures.

problem Understanding market reactions to cybersecurity incidents.
method Examined daily stock price movements of companies disclosing material cybersecurity incidents.
result Companies tend to experience negative price reactions after disclosing material cybersecurity incidents.

Critical nets in Rk\mathbb{R}^k (sometimes called geodesic nets) are embedded graph with the property that their embedding is a critical point of the total (edge) length functional and under the constraint that certain 1-valent vertices (leaves) have a fixed position. In contrast to what happens on generic manifolds, w…

2019-10-20abs ↗pdf ↗

Statistical models outperform mechanistic models in short-term COVID-19 incidence forecasts.

problem Comparing accuracy of mechanistic vs statistical models for short-term COVID-19 incidence forecasts.
method Empirical comparison of forecasts from mechanistic and statistical models using daily incidence data from six US states.
result Statistical models are at least as accurate as mechanistic models and better capture volatility.

The paper improves alignment methods for deep neural networks using geometric and spectral analysis.

problem Improving alignment methods for deep neural networks.
method Geometric and spectral analysis of residual Jacobian chains.
result Deterministic and margin-verified results on the transport of dominant singular subspaces across layers.

We estimate treatment cost-savings from early cancer diagnosis. For breast, lung, prostate and colorectal cancers and melanoma, which account for more than 50% of new incidences projected in 2017, we combine published cancer treatment cost estimates by stage with incidence rates by stage at diagnosis. We extrapolate to…

2017-08-30abs ↗pdf ↗

Despite the robust structure of the Internet, it is still susceptible to disruptive routing updates that prevent network traffic from reaching its destination. Our research shows that BGP announcements that are associated with disruptive updates tend to occur in groups of relatively high frequency, followed by periods …

2019-05-14abs ↗pdf ↗

Spectral clustering is widely used to partition graphs into distinct modules or communities. Existing methods for spectral clustering use the eigenvalues and eigenvectors of the graph Laplacian, an operator that is closely associated with random walks on graphs. We propose a new spectral partitioning method that exploi…

2013-03-11abs ↗pdf ↗