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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.

168,742 papers · 148 categories

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1122 · Nov 201719922001200920172026
39 results for dendritic democracy

This paper uses natural language processing to create the first machine-coded democracy index, which I call Automated Democracy Scores (ADS). The ADS are based on 42 million news articles from 6,043 different sources and cover all independent countries in the 1993-2012 period. Unlike the democracy indices we have today…

2015-02-22abs ↗pdf ↗

In accordance with "Democracy's Effect on Development: More Questions than Answers", we seek to carry out a study in following the description in the 'Questions for Further Study.' To that end, we studied 33 countries in the Sub-Saharan Africa region, who all went through an election which should signal a "step-up" for…

2017-12-12abs ↗pdf ↗

This chapter tackles class imbalance in datasets to promote data democracy.

problem Class imbalance in datasets leading to biased decisions and policies.
method Statistical measures and data-level methods (oversampling, undersampling, etc.) applied to a real dataset.
result Popular data-level methods improve performance in handling class imbalance.

Novel data acquisition schemes have been an emerging need for scanning microscopy based imaging techniques to reduce the time in data acquisition and to minimize probing radiation in sample exposure. Varies sparse sampling schemes have been studied and are ideally suited for such applications where the images can be re…

2018-07-06abs ↗pdf ↗

We give a short answer to the question in the title: {\em dendrits}. Precisely we show that the CC^{\ast}-algebra C(X)C(X) of all complex-valued continuous functions on a compactum XX is projective in the category C1{\mathcal C}^{1} of all (not necessarily commutative) unital CC^{\ast}-algebras if and only if XX is a…

2009-02-17abs ↗pdf ↗

Many machine learning systems make extensive use of large amounts of data regarding human behaviors. Several researchers have found various discriminatory practices related to the use of human-related machine learning systems, for example in the field of criminal justice, credit scoring and advertising. Fair machine le…

2019-03-22abs ↗pdf ↗

This paper analyzes voter coalitions in MakerDAO's decentralized governance.

problem Understanding the governance structure and influence of voter coalitions in DAOs.
method Applied clustering algorithm to voting history of MakerDAO to identify voter coalitions.
result The emergence of a dominant voter coalition signals governance centralization in DAOs.

Study of projective Fraïssé limits of trees with confluent epimorphisms.

problem Finite trees with monotone epimorphisms do not amalgamate.
method Developed new mappings and properties of continua to apply to topological graphs.
result Topological realization of the Fraïssé limit of finite trees with ramification vertices of order at most 3 is the Wa\. zewski dendrite D3D_3.

Labyrinth fractals are self-similar dendrites in the unit square that are defined with the help of a labyrinth set or a labyrinth pattern. In the case when the fractal is generated by a horizontally and vertically blocked pattern, the arc between any two points in the fractal has infinite length [Cristea\&Steinsky 2009…

2018-10-03abs ↗pdf ↗

Anti-ELAB protests affected Hong Kong firms' stock prices, especially those linked to pan-democrats.

problem Impact of anti-ELAB protests on Hong Kong firms' stock prices.
method Daily protesting intensity measured by number of protestors from 2019/6/6 to 2020/1/17; analyzed stock price changes of firms.
result Anti-ELAB protests negatively affected firms linked to pan-democrats, positively affected red chips.

Study shows how activation functions impact the storage capacity of treelike neural networks.

problem Understanding the role of activation functions in neural network expressive power.
method Analysis of treelike two-layer networks with various activation functions in the infinite-width limit.
result Activation functions affect storage capacity and robustness, with nonlinearity increasing capacity and decreasing robustness.

When 1 -> H -> G -> Q -> 1 is a short exact sequence of three infinite, word-hyperbolic groups, Mahan Mitra (Mj) has shown that the inclusion map from H to G extends continuously to a map between the Gromov boundaries of H and G. This boundary map is known as the Cannon-Thurston map. In this context, Mitra associates t…

2019-07-14abs ↗pdf ↗

Study properties of self-similar continua with finite intersection property.

problem Characterize self-similar continua with finite intersection property.
method Prove intersection graph criterion, finite order theorem, and parameter matching theorem.
result All Jordan arcs starting from a intersection point in such continuum on a plane should have the same slope parameter at that point.

Paper accelerates nonlinear mapping in online systems with lower time complexity.

problem Speeding up nonlinear mapping in online systems.
method Integrates an acceleration module into Dendrite Net (DD) to reduce time complexity.
result DD with AC has lower time complexity while maintaining nonlinear mapping and system identification properties.

Labyrinth fractals are dendrites in the unit square. They were introduced and studied in the last decade first in the self-similar case [Cristea & Steinsky (2009,2011)], then in the mixed case [Cristea & Steinsky (2017), Cristea & Leobacher (2017)]. Supermixed fractals constitute a significant generalisation of mixed l…

2018-02-15abs ↗pdf ↗

Paper develops robust methods for panel data with latent groups, improving inference under group separation violations.

problem Inference in latent group panel models under group separation violations.
method Selective conditional inference approach to derive conditional distribution of coefficients given estimated group structure.
result Valid inference under violations of group separation, superior to traditional asymptotic methods.

This article asks how planning scholarship may effectively gain impact in planning practice through media exposure. In liberal democracies the public sphere is dominated by mass media. Therefore, working with such media is a prerequisite for effective public impact of planning research. Using the example of megaproject…

2013-04-05abs ↗pdf ↗

The paper examines how algorithmic classification affects behavior and proposes democratizing stakes to mitigate predatory practices.

problem The impact of algorithmic classification on individual behavior and fairness in decision-making processes.
method Characterization of optimal classification by an algorithm designer and analysis of the effect of democratizing stakes.
result Optimal classification can lead to surprising behavior patterns, and democratizing stakes can mitigate predatory practices.

Neural networks learn to mimic brain neurons with two-input activation functions, improving performance and robustness.

problem Training neural networks to mimic the complex interactions of brain neurons.
method Developed a network-in-network architecture with two-input activation functions, optimized hyperparameters, and compared to conventional ReLU networks.
result Two-input activation functions can learn soft XOR functions, improving network performance and robustness.

T2FSNN improves deep SNNs by reducing spikes and latency.

problem Inefficiency in spiking neural networks due to lack of scalable training algorithms.
method Introduces time-to-first-spike coding with kernel-based dynamic threshold and dendrite, combined with gradient-based optimization and early firing methods.
result Reduces inference latency and spike count by 22% and less than 1% compared to burst coding.

Biological neural network mimics CCA for multi-channel data.

problem Implementing CCA in a biologically plausible neural network.
method Derive an online CCA algorithm with local synaptic updates for multi-compartmental neurons.
result The derived neural network architecture and synaptic updates resemble cortical pyramidal neuron behavior.

Paper proposes forecast-necessity testing for accurate causal interpretation in nonlinear time-series models.

problem Misinterpretation of causal scores from nonlinear models as regression coefficients.
method Systematic edge ablation and forecast comparison to evaluate causal necessity.
result Causal relationships with similar scores can differ in their necessity for accurate prediction.

T-SVM improves learning in spiking neurons by maximizing dynamical margin.

problem Finding robust solutions in spiking neuronal networks with temporal correlations.
method Introduces Temporal Support Vector Machine (T-SVM) to maximize dynamical margin.
result T-SVM enables learning of tasks requiring nonlinear spatial integration.

India introduces NPS to manage pension liabilities and promote savings.

problem Managing pension liabilities and promoting savings among employees.
method Comparative analysis of NPS and OPS, addressing stakeholder claims.
result NPS reduces government pension liabilities and promotes disciplined saving.