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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.

169,051 papers · 148 categories

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0111 · Jun 199619922001200920182026
12 results for group-representative

A novel method for estimating group-representative functional networks from multi-subject fMRI data.

problem Estimating common neuronal characteristics in a population from multi-subject fMRI data.
method Two-phase approach: clustering-based ICA for component maps, MAP-MRF labeling for group-representative map estimation.
result Demonstrated the viability of the proposed method in extracting group-representative functional networks from simulated fMRI data.

The paper introduces group-representative clustering to ensure fair representation of different groups in clusters.

problem Ensuring fair representation of different groups in clusters.
method Developed a new clustering approach called group-representative clustering, which parallels fairness notions in classification.
result Presented approximation algorithms for group representative kk-median clustering and evaluated on real-world data.

Quadratic-time algorithm computes stretch factors and foliations for pseudo-Anosov mapping classes.

problem Computing stretch factors and foliations for pseudo-Anosov mapping classes efficiently.
method Quadratic-time algorithm using input word and length as complexity measure.
result First algorithm to compute stretch factors and foliations in sub-exponential time.

There are multiple sides to every story, and while statistical topic models have been highly successful at topically summarizing the stories in corpora of text documents, they do not explicitly address the issue of learning the different sides, the viewpoints, expressed in the documents. In this paper, we show how thes…

2016-08-14abs ↗pdf ↗

Factor analysis provides linear factors that describe relationships between individual variables of a data set. We extend this classical formulation into linear factors that describe relationships between groups of variables, where each group represents either a set of related variables or a data set. The model also na…

2014-11-21abs ↗pdf ↗

For a oriented genus g surface with one boundary component, S, the Torelli group is the group of orientation preserving homeomorphisms of S that induce the identity on homology. The Magnus representation of the Torelli group represents the action on F/F" where F=pi_1(S) and F" is the second term of the derived series. …

2013-08-16abs ↗pdf ↗

The paper proves rigidity results for Anosov flows and their orbit equivalences.

problem Characterizing orbit equivalences of Anosov flows and their dynamics.
method Using hyperbolic-like dynamics, the paper proves a spectral rigidity theorem and gives efficient criteria for orbit equivalences.
result Characterizes orbit equivalent flows in terms of fundamental group elements represented by periodic orbits.

Bayesian model transfers knowledge across different engineering fleets.

problem Data sparsity in predictive models for engineering infrastructure.
method Hierarchical Bayesian approach with multitask learning.
result Improves survival analysis and power prediction in truck fleets and wind farms.

A new algorithm reduces frequentist regret in multi-agent bandit problems with sparse hypergraphs.

problem Deriving a frequentist regret bound for Thompson sampling in multi-agent settings with sparse hypergraphs.
method Proposed εε-exploring Multi-Agent Thompson Sampling (εε-MATS) algorithm that combines exploration and exploitation strategies.
result Achieves a worst-case frequentist regret bound sublinear in time horizon and local arm size, optimal up to constants and logarithms for sparse hypergraphs.