Dávid Pál

Publication Activity (10 Years)

Years Active: 2006-2022
Publications (10 Years): 17

Top Venues

CoRR

ICML

NIPS

Theor. Comput. Sci.

University of Waterloo, Ontario, Canada (PHD)

Education History

University of Waterloo, Ontario, Canada

PHD

Publications

Jonathan Gu, Dávid Pál, Kevin Ryan
Auction for Double-Wide Ads. CoRR (2022)
Francesco Orabona, Dávid Pál
Parameter-free Stochastic Optimization of Variationally Coherent Functions. CoRR (2021)
Utkarsh Upadhyay, Róbert Busa-Fekete, Wojciech Kotlowski, Dávid Pál, Balázs Szörényi
Learning to Crawl. AAAI (2020)
Utkarsh Upadhyay, Róbert Busa-Fekete, Wojciech Kotlowski, Dávid Pál, Balázs Szörényi
Learning to Crawl. CoRR (2019)
Alina Beygelzimer, Dávid Pál, Balázs Szörényi, Devanathan Thiruvenkatachari, Chen-Yu Wei, Chicheng Zhang
Bandit Multiclass Linear Classification: Efficient Algorithms for the Separable Case. CoRR (2019)
Alina Beygelzimer, Dávid Pál, Balázs Szörényi, Devanathan Thiruvenkatachari, Chen-Yu Wei, Chicheng Zhang
Bandit Multiclass Linear Classification: Efficient Algorithms for the Separable Case. ICML (2019)
Alexander Golovnev, Dávid Pál, Balázs Szörényi
The information-theoretic value of unlabeled data in semi-supervised learning. ICML (2019)
Alexander Golovnev, Dávid Pál, Balázs Szörényi
The information-theoretic value of unlabeled data in semi-supervised learning. CoRR (2019)
Francesco Orabona, Dávid Pál
Scale-free online learning. Theor. Comput. Sci. 716 (2018)
Satyen Kale, Zohar S. Karnin, Tengyuan Liang, Dávid Pál
Adaptive Feature Selection: Computationally Efficient Online Sparse Linear Regression under RIP. ICML (2017)
Satyen Kale, Zohar S. Karnin, Tengyuan Liang, Dávid Pál
Adaptive Feature Selection: Computationally Efficient Online Sparse Linear Regression under RIP. CoRR (2017)
Satyen Kale, Chansoo Lee, Dávid Pál
Hardness of Online Sleeping Combinatorial Optimization Problems. NIPS (2016)
Francesco Orabona, Dávid Pál
Coin Betting and Parameter-Free Online Learning. NIPS (2016)
Francesco Orabona, Dávid Pál
From Coin Betting to Parameter-Free Online Learning. CoRR (2016)
Francesco Orabona, Dávid Pál
Scale-Free Online Learning. CoRR (2016)
Francesco Orabona, Dávid Pál
Open Problem: Parameter-Free and Scale-Free Online Algorithms. COLT (2016)
Francesco Orabona, Dávid Pál
Parameter-Free Convex Learning through Coin Betting. AutoML@ICML (2016)
Francesco Orabona, Dávid Pál
Scale-Free Algorithms for Online Linear Optimization. ALT (2015)
Satyen Kale, Chansoo Lee, Dávid Pál
Hardness of Online Sleeping Combinatorial Optimization Problems. CoRR (2015)
Francesco Orabona, Dávid Pál
Scale-Free Algorithms for Online Linear Optimization. CoRR (2015)
Francesco Orabona, Dávid Pál
Optimal Non-Asymptotic Lower Bound on the Minimax Regret of Learning with Expert Advice. CoRR (2015)
Gábor Bartók, Dean P. Foster, Dávid Pál, Alexander Rakhlin, Csaba Szepesvári
Partial Monitoring - Classification, Regret Bounds, and Algorithms. Math. Oper. Res. 39 (4) (2014)
Dávid Pál
Online problémy v strojovom učení. ITAT (2013)
András Antos, Gábor Bartók, Dávid Pál, Csaba Szepesvári
Toward a classification of finite partial-monitoring games. Theor. Comput. Sci. 473 (2013)
Yasin Abbasi-Yadkori, Dávid Pál, Csaba Szepesvári
Online-to-Confidence-Set Conversions and Application to Sparse Stochastic Bandits. AISTATS (2012)
András Antos, Gábor Bartók, Dávid Pál, Csaba Szepesvári
Toward a Classification of Finite Partial-Monitoring Games CoRR (2011)
Yasin Abbasi-Yadkori, Dávid Pál, Csaba Szepesvári
Online Least Squares Estimation with Self-Normalized Processes: An Application to Bandit Problems CoRR (2011)
Gábor Bartók, Dávid Pál, Csaba Szepesvári
Minimax Regret of Finite Partial-Monitoring Games in Stochastic Environments. COLT (2011)
Yasin Abbasi-Yadkori, Dávid Pál, Csaba Szepesvári
Improved Algorithms for Linear Stochastic Bandits. NIPS (2011)
Shai Ben-David, Tyler Lu, Teresa Luu, Dávid Pál
Impossibility Theorems for Domain Adaptation. AISTATS (2010)
Tyler Lu, Dávid Pál, Martin Pal
Contextual Multi-Armed Bandits. AISTATS (2010)
Gábor Bartók, Dávid Pál, Csaba Szepesvári
Toward a Classification of Finite Partial-Monitoring Games. ALT (2010)
Dávid Pál, Barnabás Póczos, Csaba Szepesvári
Estimation of Renyi Entropy and Mutual Information Based on Generalized Nearest-Neighbor Graphs. NIPS (2010)
Dávid Pál, Barnabás Póczos, Csaba Szepesvári
Estimation of Rényi Entropy and Mutual Information Based on Generalized Nearest-Neighbor Graphs CoRR (2010)
Gagan Aggarwal, S. Muthukrishnan, Dávid Pál, Martin Pál
General auction mechanism for search advertising. WWW (2009)
Shai Ben-David, Tyler Lu, Dávid Pál, Miroslava Sotáková
Learning Low Density Separators. AISTATS (2009)
Shai Ben-David, Dávid Pál, Shai Shalev-Shwartz
Agnostic Online Learning. COLT (2009)
Shai Ben-David, Tyler Lu, Dávid Pál, Miroslava Sotáková
Learning Low-Density Separators CoRR (2008)
Shai Ben-David, Tyler Lu, Dávid Pál
Does Unlabeled Data Provably Help? Worst-case Analysis of the Sample Complexity of Semi-Supervised Learning. COLT (2008)
Gagan Aggarwal, S. Muthukrishnan, Dávid Pál, Martin Pál
General Auction Mechanism for Search Advertising CoRR (2008)
Dávid Pál, Martin Skoviera
Edge-Colourings of Cubic Graphs and Universal Steiner Triple Systems. Electron. Notes Discret. Math. 28 (2007)
Dávid Pál, Martin Skoviera
Colouring Cubic Graphs by Small Steiner Triple Systems. Graphs Comb. 23 (2) (2007)
Shai Ben-David, Dávid Pál, Hans Ulrich Simon
-Means Clustering. COLT (2007)
Shai Ben-David, Ulrike von Luxburg, Dávid Pál
A Sober Look at Clustering Stability. COLT (2006)

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Publication Activity (10 Years)

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Dávid Pál