ML Anthology

Pál, Dávid

21 publications

AAAI 2020 Learning to Crawl Utkarsh Upadhyay, Róbert Busa-Fekete, Wojciech Kotlowski, Dávid Pál, Balázs Szörényi
ICML 2019 Bandit Multiclass Linear Classification: Efficient Algorithms for the Separable Case Alina Beygelzimer, David Pal, Balazs Szorenyi, Devanathan Thiruvenkatachari, Chen-Yu Wei, Chicheng Zhang
ICML 2019 The Information-Theoretic Value of Unlabeled Data in Semi-Supervised Learning Alexander Golovnev, David Pal, Balazs Szorenyi
ICML 2017 Adaptive Feature Selection: Computationally Efficient Online Sparse Linear Regression Under RIP Satyen Kale, Zohar Karnin, Tengyuan Liang, Dávid Pál
NeurIPS 2016 Coin Betting and Parameter-Free Online Learning Francesco Orabona, David Pal
NeurIPS 2016 Hardness of Online Sleeping Combinatorial Optimization Problems Satyen Kale, Chansoo Lee, David Pal
COLT 2016 Open Problem: Parameter-Free and Scale-Free Online Algorithms Francesco Orabona, Dávid Pál
AutoML 2016 Parameter-Free Convex Learning Through Coin Betting Francesco Orabona, Dávid Pál
ALT 2015 Scale-Free Algorithms for Online Linear Optimization Francesco Orabona, Dávid Pál
AISTATS 2012 Online-to-Confidence-Set Conversions and Application to Sparse Stochastic Bandits Yasin Abbasi-Yadkori, David Pal, Csaba Szepesvari
NeurIPS 2011 Improved Algorithms for Linear Stochastic Bandits Yasin Abbasi-yadkori, Dávid Pál, Csaba Szepesvári
COLT 2011 Minimax Regret of Finite Partial-Monitoring Games in Stochastic Environments Gábor Bartók, Dávid Pál, Csaba Szepesvári
AISTATS 2010 Contextual Multi-Armed Bandits Tyler Lu, David Pal, Martin Pal
NeurIPS 2010 Estimation of Rényi Entropy and Mutual Information Based on Generalized Nearest-Neighbor Graphs Dávid Pál, Barnabás Póczos, Csaba Szepesvári
AISTATS 2010 Impossibility Theorems for Domain Adaptation Shai Ben David, Tyler Lu, Teresa Luu, David Pal
ALT 2010 Toward a Classification of Finite Partial-Monitoring Games Gábor Bartók, Dávid Pál, Csaba Szepesvári
COLT 2009 Agnostic Online Learning Shai Ben-David, Dávid Pál, Shai Shalev-Shwartz
AISTATS 2009 Learning Low Density Separators Shai Ben-David, Tyler Lu, David Pal, Miroslava Sotakova
COLT 2008 Does Unlabeled Data Provably Help? Worst-Case Analysis of the Sample Complexity of Semi-Supervised Learning Shai Ben-David, Tyler Lu, Dávid Pál
COLT 2007 Stability of K -Means Clustering Shai Ben-David, Dávid Pál, Hans Ulrich Simon
COLT 2006 A Sober Look at Clustering Stability Shai Ben-David, Ulrike von Luxburg, Dávid Pál