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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.

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6 results for “Kumaraswamy”

Stabilizing the Kumaraswamy Distributioncs.LG

We stabilize the Kumaraswamy distribution for efficient sampling and differentiation.

problem Numerical instabilities in the Kumaraswamy distribution's inverse CDF and log-pdf.

method Identified and resolved numerical issues, introduced a stabilized KS distribution.

result Stabilized Kumaraswamy distribution supports efficient sampling and differentiation.

Kumaraswamy distribution numerical stability reparameterization trick latent variable models contextual bandits

2024-10-01abs ↗pdf ↗

A New Distribution on the Simplex with Auto-Encoding Applicationscs.LG

New distribution on simplex for auto-encoding tasks.

problem Developing a new distribution for sparsity in auto-encoding models.

method Using Kumaraswamy distribution and ordered stick-breaking process.

result The new distribution has an exact and closed form reparameterization.

Auto-encoding Distribution on simplex Kumaraswamy Sparsity Deep variational Bayesian modeling

2019-05-28abs ↗pdf ↗

A Minimum Variance Path Principle for Accurate and Stable Score-Based Density Ratio Estimationcs.LG

We solve the paradox of score-based methods by minimizing path variance.

problem Score-based methods are path-dependent, leading to inaccurate and unstable estimators.

method Propose MVP Principle to minimize path variance, derive closed-form expression, and use flexible Kumaraswamy Mixture Model.

result Establishes new state-of-the-art results on challenging benchmarks.

Score-based methods Density ratio estimation Path variance MVP Principle Kumaraswamy Mixture Model

2026-01-31abs ↗pdf ↗

Optimal Trading Strategies as Measures of Market Disequilibriumq-fin.GN

For classification of the high frequency trading quantities, waiting times, price increments within and between sessions are referred to as the a-, b-, and c-increments. Statistics of the a-b-c-increments are computed for the Time & Sales records posted by the Chicago Mercantile Exchange Group for the futures traded on…

2013-12-06abs ↗pdf ↗

The Wandering of Cornq-fin.GN

Time and Sales of corn futures traded electronically on the CME Group Globex are studied. Theories of continuous prices turn upside down reality of intra-day trading. Prices and their increments are discrete and obey lattice probability distributions. A function for systematic evolution of futures trading volume is pro…

2017-04-03abs ↗pdf ↗

Credit scoring using neural networks and SURE posterior probability calibrationq-fin.ST

The article compares neural networks and logistic regression for credit scoring and introduces a new probability calibration technique.

problem Improving credit scoring accuracy using machine learning techniques.

method Comparison of logistic regression and neural networks, feature importance assessment, temporal feature inclusion, and SURE probability calibration.

result Neural networks can slightly improve credit scoring performance, and SURE calibration technique enhances probability calibration.

credit scoring neural networks logistic regression probability calibration SURE

2021-07-15abs ↗pdf ↗