7 citations · 20 across the 16 of their papers we have counts for
16 papers
Coarsening Latent-Class Probabilities: Directional Distortion and Coverage Loss
Marcell T. Kurbucz
Outcomes are regressed on a calibrated probability vector for unobserved class membership. Under a structural conditional mean excluding the score and conditional calibration, the…
When to Trust Confidence Thresholding: Calibration Diagnostics for Pseudo-Labelled Regression
Marcell T. Kurbucz
Calibrated probability outputs of trained classifiers are increasingly used as inputs to downstream regression estimands such as effects, prevalences, or disparities for a latent g…
Identification of Latent Group Effects under Conditional Calibration
Marcell T. Kurbucz
We study identification of a structural group effect when the group indicator is unobserved but the analyst observes a calibrated probability score satisfying $E[…
Adaptive Conditional Residual Sampling for Spectral Risk Optimisation under Decision-Dependent Uncertainty
Marcell T. Kurbucz
We consider minimising a spectral risk objective, the expected cost plus a weighted conditional value-at-risk, when the distribution of the uncertain parameters depends on the deci…
SplitWise Regression: Stepwise Modeling with Adaptive Dummy Encoding
Marcell T. Kurbucz, Nikolaos Tzivanakis, Nilufer Sari Aslam +1
Capturing nonlinear relationships without sacrificing interpretability remains a persistent challenge in regression modeling. We introduce SplitWise, a novel framework that enhance…
ALT: A Python Package for Lightweight Feature Representation in Time Series Classification
Balázs P. Halmos, Balázs Hajós, Vince Á. Molnár +2
We introduce ALT, an open-source Python package created for efficient and accurate time series classification (TSC). The package implements the adaptive law-based transformation (A…
Eigenvalue-Based Randomness Test for Residual Diagnostics in Panel Data Models
Marcell T. Kurbucz, Betsabé Pérez Garrido, Antal Jakovác
This paper introduces the Eigenvalue-Based Randomness (EBR) test - a novel approach rooted in the Tracy-Widom law from random matrix theory - and applies it to the context of resid…
Adaptive Law-Based Transformation (ALT): A Lightweight Feature Representation for Time Series Classification
Marcell T. Kurbucz, Balázs Hajós, Balázs P. Halmos +2
Time series classification (TSC) is fundamental in numerous domains, including finance, healthcare, and environmental monitoring. However, traditional TSC methods often struggle wi…
Unified Causality Analysis Based on the Degrees of Freedom
András Telcs, Marcell T. Kurbucz, Antal Jakovác
Temporally evolving systems are typically modeled by dynamic equations. A key challenge in accurate modeling is understanding the causal relationships between subsystems, as well a…
Learning ECG Signal Features Without Backpropagation Using Linear Laws
Péter Pósfay, Marcell T. Kurbucz, Péter Kovács +1
This paper introduces LLT-ECG, a novel method for electrocardiogram (ECG) signal classification that leverages concepts from theoretical physics to automatically generate features…
Feature space reduction method for ultrahigh-dimensional, multiclass data: Random forest-based multiround screening (RFMS)
Gergely Hanczár, Marcell Stippinger, Dávid Hanák +4
In recent years, numerous screening methods have been published for ultrahigh-dimensional data that contain hundreds of thousands of features; however, most of these features canno…
LLT: An R package for Linear Law-based Feature Space Transformation
Marcell T. Kurbucz, Péter Pósfay, Antal Jakovác
The goal of the linear law-based feature space transformation (LLT) algorithm is to assist with the classification of univariate and multivariate time series. The presented R packa…
Predicting the Price Movement of Cryptocurrencies Using Linear Law-based Transformation
Marcell T. Kurbucz, Péter Pósfay, Antal Jakovác
The aim of this paper is to investigate the effect of a novel method called linear law-based feature space transformation (LLT) on the accuracy of intraday price movement predictio…
BiometricBlender: Ultra-high dimensional, multi-class synthetic data generator to imitate biometric feature space
Marcell Stippinger, Dávid Hanák, Marcell T. Kurbucz +3
The lack of freely available (real-life or synthetic) high or ultra-high dimensional, multi-class datasets may hamper the rapidly growing research on feature screening, especially…
Reconstruction of observed mechanical motions with Artificial Intelligence tools
Antal Jakovac, Marcell T. Kurbucz, Peter Posfay
The goal of this paper is to determine the laws of observed trajectories assuming that there is a mechanical system in the background and using these laws to continue the observed…
Linear Laws of Markov Chains with an Application for Anomaly Detection in Bitcoin Prices
Marcell T. Kurbucz, Péter Pósfay, Antal Jakovác
The goals of this paper are twofold: (1) to present a new method that is able to find linear laws governing the time evolution of Markov chains and (2) to apply this method for ano…