239 citations · 387 across the 14 of their papers we have counts for
15 papers
MiNCE: Nonparametric, Strongly Consistent Confidence Envelopes for Band-Limited Functions and their Smoothed Spectra
Balázs Csanád Csáji, Bálint Horváth
Minimum-norm confidence envelope strategies offer a nonparametric approach to constructing nonasymptotic, simultaneous confidence regions for band-limited functions, exploiting the…
Signed-Perturbed Sums Estimation of ARX Systems: Exact Coverage and Strong Consistency (Extended Version)
Algo Carè, Erik Weyer, Balázs Cs. Csáji +1
Sign-Perturbed Sums (SPS) is a system identification method that constructs confidence regions for the unknown system parameters. In this paper, we study SPS for ARX systems, and e…
Robust Independence Tests with Finite Sample Guarantees for Synchronous Stochastic Linear Systems
Ambrus Tamás, Dániel Ágoston Bálint, Balázs Csanád Csáji
The paper introduces robust independence tests with non-asymptotically guaranteed significance levels for stochastic linear time-invariant systems, assuming that the observed outpu…
Resampled Confidence Regions with Exponential Shrinkage for the Regression Function of Binary Classification
Ambrus Tamás, Balázs Csanád Csáji
The regression function is one of the key objects of binary classification, since it not only determines a Bayes optimal classifier, hence, defines an optimal decision boundary, bu…
Recursive Estimation of Conditional Kernel Mean Embeddings
Ambrus Tamás, Balázs Csanád Csáji
Kernel mean embeddings, a widely used technique in machine learning, map probability distributions to elements of a reproducing kernel Hilbert space (RKHS). For supervised learning…
Non-Asymptotic State-Space Identification of Closed-Loop Stochastic Linear Systems using Instrumental Variables
Szabolcs Szentpéteri, Balázs Csanád Csáji
The paper suggests a generalization of the Sign-Perturbed Sums (SPS) finite sample system identification method for the identification of closed-loop observable stochastic linear s…
Nonparametric, Nonasymptotic Confidence Bands with Paley-Wiener Kernels for Band-Limited Functions
Balázs Csanád Csáji, Bálint Horváth
The paper introduces a method to construct confidence bands for bounded, band-limited functions based on a finite sample of input-output pairs. The approach is distribution-free w.…
Exact Distribution-Free Hypothesis Tests for the Regression Function of Binary Classification via Conditional Kernel Mean Embeddings
Ambrus Tamás, Balázs Csanád Csáji
In this paper we suggest two statistical hypothesis tests for the regression function of binary classification based on conditional kernel mean embeddings. The regression function…
Stochastic Approximation in a Markovian Framework Revisited: Lipschitz Continuity of the Poisson Equation
Algo Carè, Balázs Csanád Csáji, Balázs Gerencsér +2
In this paper we revisit a fundamental technical issue within the theory of stochastic approximation (SA) in a Markovian framework, first proposed in the book by Djereveckii and Fr…
Semi-Parametric Uncertainty Bounds for Binary Classification
Balázs Csanád Csáji, Ambrus Tamás
The paper studies binary classification and aims at estimating the underlying regression function which is the conditional expectation of the class labels given the inputs. The reg…
Score Permutation Based Finite Sample Inference for Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) Models
Balázs Csanád Csáji
A standard model of (conditional) heteroscedasticity, i.e., the phenomenon that the variance of a process changes over time, is the Generalized AutoRegressive Conditional Heteroske…
Sign-Perturbed Sums: A New System Identification Approach for Constructing Exact Non-Asymptotic Confidence Regions in Linear Regression Models
Balázs Cs. Csáji, Marco C. Campi, Erik Weyer
We propose a new system identification method, called Sign-Perturbed Sums (SPS), for constructing non-asymptotic confidence regions under mild statistical assumptions. SPS is intro…
Sign-Perturbed Sums (SPS) with Instrumental Variables for the Identification of ARX Systems - Extended Version
Valerio Volpe, Balázs Cs. Csáji, Algo Carè +2
We propose a generalization of the recently developed system identification method called Sign-Perturbed Sums (SPS). The proposed construction is based on the instrumental variable…
Exploring the Mobility of Mobile Phone Users
Balázs Cs. Csáji, Arnaud Browet, V. A. Traag +5
Mobile phone datasets allow for the analysis of human behavior on an unprecedented scale. The social network, temporal dynamics and mobile behavior of mobile phone users have often…
PageRank Optimization by Edge Selection
Balázs Csanád Csáji, Raphaël M. Jungers, Vincent D. Blondel
The importance of a node in a directed graph can be measured by its PageRank. The PageRank of a node is used in a number of application contexts - including ranking websites - and…