Balázs Csanád Csáji

Publication Activity (10 Years)

Years Active: 2003-2024
Publications (10 Years): 34

Top Topics

Linear Regression Models

Confidence Bounds

Renewable Energy

Asymptotic Properties

Top Venues

IEEE Control. Syst. Lett.

Publications

Szabolcs Szentpéteri, Balázs Csanád Csáji
Finite-Sample Identification of Linear Regression Models with Residual-Permuted Sums. CoRR (2024)
Szabolcs Szentpéteri, Balázs Csanád Csáji
Finite-Sample Identification of Linear Regression Models With Residual-Permuted Sums. IEEE Control. Syst. Lett. 8 (2024)
Szabolcs Szentpéteri, Balázs Csanád Csáji
Sample Complexity of the Sign-Perturbed Sums Identification Method: Scalar Case. CoRR (2024)
Ambrus Tamás, Szabolcs Szentpéteri, Balázs Csanád Csáji
Data-Driven Confidence Intervals with Optimal Rates for the Mean of Heavy-Tailed Distributions. AISTATS (2024)
Ambrus Tamás, Szabolcs Szentpéteri, Balázs Csanád Csáji
Data-Driven Upper Confidence Bounds with Near-Optimal Regret for Heavy-Tailed Bandits. CoRR (2024)
Balázs Csanád Csáji, Bálint Horváth
Improving Kernel-Based Nonasymptotic Simultaneous Confidence Bands. CoRR (2024)
Algo Carè, Erik Weyer, Balázs Csanád Csáji, Marco C. Campi
Signed-Perturbed Sums Estimation of ARX Systems: Exact Coverage and Strong Consistency (Extended Version). CoRR (2024)
Ambrus Tamás, Dániel Ágoston Bálint, Balázs Csanád Csáji
Robust Independence Tests with Finite Sample Guarantees for Synchronous Stochastic Linear Systems. CoRR (2023)
Ambrus Tamás, Balázs Csanád Csáji
Recursive Estimation of Conditional Kernel Mean Embeddings. CoRR (2023)
Szabolcs Szentpéteri, Balázs Csanád Csáji
Non-Asymptotic State-Space Identification of Closed-Loop Stochastic Linear Systems using Instrumental Variables. CoRR (2023)
Ambrus Tamás, Balázs Csanád Csáji
Distribution-Free Inference for the Regression Function of Binary Classification. CoRR (2023)
Ambrus Tamás, Dániel Ágoston Bálint, Balázs Csanád Csáji
Robust Independence Tests With Finite Sample Guarantees for Synchronous Stochastic Linear Systems. IEEE Control. Syst. Lett. 7 (2023)
Balázs Csanád Csáji, László Györfi, Ambrus Tamás
On rate-optimal classification from non-private and from private data. CoRR (2023)
Szabolcs Szentpéteri, Balázs Csanád Csáji
Non-asymptotic state-space identification of closed-loop stochastic linear systems using instrumental variables. Syst. Control. Lett. 178 (2023)
Balázs Csanád Csáji, Bálint Horváth
Nonparametric, Nonasymptotic Confidence Bands With Paley-Wiener Kernels for Band-Limited Functions. IEEE Control. Syst. Lett. 6 (2022)
Ambrus Tamás, Balázs Csanád Csáji
Exact Distribution-Free Hypothesis Tests for the Regression Function of Binary Classification via Conditional Kernel Mean Embeddings. IEEE Control. Syst. Lett. 6 (2022)
Balázs Csanád Csáji, Bálint Horváth
Nonparametric, Nonasymptotic Confidence Bands with Paley-Wiener Kernels for Band-Limited Functions. CoRR (2022)
Ambrus Tamás, Balázs Csanád Csáji
Exact Distribution-Free Hypothesis Tests for the Regression Function of Binary Classification via Conditional Kernel Mean Embeddings. CoRR (2021)
Algo Carè, Marco Claudio Campi, Balázs Csanád Csáji, Erik Weyer
Facing undermodelling in Sign-Perturbed-Sums system identification. Syst. Control. Lett. 153 (2021)
Balázs Csanád Csáji, Ambrus Tamás
Semi-Parametric Uncertainty Bounds for Binary Classification. CDC (2019)
Balázs Csanád Csáji, Krisztián Balázs Kis
Distribution-free uncertainty quantification for kernel methods by gradient perturbations. Mach. Learn. 108 (8-9) (2019)
Balázs Csanád Csáji, Ambrus Tamás
Semi-Parametric Uncertainty Bounds for Binary Classification. CoRR (2019)
Algo Carè, Balázs Csanád Csáji, Balázs Gerencsér, László Gerencsér, Miklós Rásonyi
On the Poisson Equation of Parameter-Dependent Markov Chains. CoRR (2019)
Algo Carè, Balázs Csanád Csáji, Balázs Gerencsér, László Gerencsér, Miklós Rásonyi
Parameter-Dependent Poisson Equations: Tools for Stochastic Approximation in a Markovian Framework. CDC (2019)
Balázs Csanád Csáji, Marco C. Campi, Erik Weyer
Sign-Perturbed Sums: A New System Identification Approach for Constructing Exact Non-Asymptotic Confidence Regions in Linear Regression Models. CoRR (2018)
László Gerencsér, Balázs Csanád Csáji, Sotirios Sabanis
Asymptotic Analysis of the LMS Algorithm with Momentum. CDC (2018)
Balázs Csanád Csáji
Score Permutation Based Finite Sample Inference for Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) Models. CoRR (2018)
Balázs Csanád Csáji, Zsolt Kemény, Gianfranco Pedone, András Kuti, József Váncza
Wireless Multi-Sensor Networks for Smart Cities: A Prototype System with Statistical Data Analysis. CoRR (2018)
Balázs Csanád Csáji, Krisztián Balázs Kis
Uncertainty Quantification for Kernel Methods. CoRR (2018)
Algo Carè, Balázs Csanád Csáji, Marco C. Campi, Erik Weyer
Finite-Sample System Identification: An Overview and a New Correlation Method. IEEE Control. Syst. Lett. 2 (1) (2018)
Erik Weyer, Marco Claudio Campi, Balázs Csanád Csáji
Asymptotic properties of SPS confidence regions. Autom. 82 (2017)
Balázs Csanád Csáji, András Kovács, József Váncza
Online Learning for Aggregating Forecasts in Renewable Energy Systems. ERCIM News 2016 (107) (2016)
Algo Carè, Balázs Csanád Csáji, Marco C. Campi
Sign-Perturbed Sums (SPS) with asymmetric noise: Robustness analysis and robustification techniques. CDC (2016)
Balázs Csanád Csáji
Score Permutation Based Finite Sample Inference for Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) Models. AISTATS (2016)
Valerio Volpe, Balázs Csanád Csáji, Algo Carè, Erik Weyer, Marco C. Campi
Sign-Perturbed Sums (SPS) with instrumental variables for the identification of ARX systems. CDC (2015)
Balázs Csanád Csáji, Erik Weyer
Closed-loop applicability of the Sign-Perturbed Sums method. CDC (2015)
László Monostori, Paul Valckenaers, Alexandre Dolgui, Hervé Panetto, Mietek Brdys, Balázs Csanád Csáji
Cooperative control in production and logistics. Annu. Rev. Control. 39 (2015)
László Monostori, Paul Valckenaers, Alexandre Dolgui, Hervé Panetto, Mietek Brdys, Balázs Csanád Csáji
Cooperative Control in Production and Logistics. CoRR (2015)
Balázs Csanád Csáji, Marco C. Campi, Erik Weyer
Sign-Perturbed Sums: A New System Identification Approach for Constructing Exact Non-Asymptotic Confidence Regions in Linear Regression Models. IEEE Trans. Signal Process. 63 (1) (2015)
Balázs Csanád Csáji, Raphaël M. Jungers, Vincent D. Blondel
PageRank optimization by edge selection. Discret. Appl. Math. 169 (2014)
Balázs Csanád Csáji, Marco C. Campi, Erik Weyer
Strong consistency of the Sign-Perturbed Sums method. CDC (2014)
Balázs Csanád Csáji, András Kovács, József Váncza
Adaptive aggregated predictions for renewable energy systems. ADPRL (2014)
Balázs Csanád Csáji, Borbála Háy, András Kovács, Gianfranco Pedone, Tibor Révész, József Váncza
Monitoring and Controlling Energy-positive Public Lighting: The E+grid System. ERCIM News 2014 (98) (2014)
Balázs Csanád Csáji, László Monostori
Adaptive Stochastic Resource Control: A Machine Learning Approach. CoRR (2014)
Erik Weyer, Balázs Csanád Csáji, Marco C. Campi
Guaranteed non-asymptotic confidence ellipsoids for FIR systems. CDC (2013)
Balázs Csanád Csáji, Arnaud Browet, Vincent A. Traag, Jean-Charles Delvenne, Etienne Huens, Paul Van Dooren, Zbigniew Smoreda, Vincent D. Blondel
Exploring the Mobility of Mobile Phone Users CoRR (2012)
Balázs Csanád Csáji, Marco C. Campi, Erik Weyer
Sign-perturbed sums (SPS): A method for constructing exact finite-sample confidence regions for general linear systems. CDC (2012)
Balázs Csanád Csáji, Erik Weyer
System identification with binary observations by stochastic approximation and active learning. CDC/ECC (2011)
László Monostori, Balázs Csanád Csáji, Botond Kádár, András Pfeiffer, Elisabeta Ilie Zudor, Zsolt Kemény, Marcell Szathmári
Towards adaptive and digital manufacturing. Annu. Rev. Control. 34 (1) (2010)
Balázs Csanád Csáji, Raphaël M. Jungers, Vincent D. Blondel
PageRank Optimization in Polynomial Time by Stochastic Shortest Path Reformulation. ALT (2010)
Balázs Csanád Csáji, Raphaël M. Jungers, Vincent D. Blondel
PageRank Optimization by Edge Selection CoRR (2009)
Balázs Csanád Csáji, László Monostori
Value Function Based Reinforcement Learning in Changing Markovian Environments. J. Mach. Learn. Res. 9 (2008)
Balázs Csanád Csáji, László Monostori
Adaptive Stochastic Resource Control: A Machine Learning Approach. J. Artif. Intell. Res. 32 (2008)
Balázs Csanád Csáji, László Monostori
Adaptive Sampling Based Large-Scale Stochastic Resource Control. AAAI (2006)
Balázs Csanád Csáji, László Monostori, Botond Kádár
Reinforcement learning in a distributed market-based production control system. Adv. Eng. Informatics 20 (3) (2006)
Balázs Csanád Csáji, László Monostori
Stochastic Reactive Production Scheduling by Multi-agent Based Asynchronous Approximate Dynamic Programming. CEEMAS (2005)
Balázs Csanád Csáji, Josef Küng, Jürgen Palkoska, Roland R. Wagner
On the Automation of Similarity Information Maintenance in Flexible Query Answering Systems. DEXA (2004)
Marco Gillies, Daniel Ballin, Balázs Csanád Csáji
Efficient Clothing Fitting from Data. WSCG (2004)
Balázs Csanád Csáji, Botond Kádár, László Monostori
Improving Multi-agent Based Scheduling by Neurodynamic Programming. HoloMAS (2003)