L. Addario-Berry,
A. Branderberger,
S. Briend,
N. Broutin,
and G. Lugosi.
Leaf stripping on uniform attachment trees.
(PDF )
G. Lugosi
and
E. Nualart.
Convergence of continuous-time stochastic gradient descent with applications to linear deep neural networks.
(PDF )
L. Devroye,
G. Lugosi,
and
P. Zwiernik.
Learning latent tree models with small query complexity.
(PDF )
L. Devroye,
G. Lugosi,
and
P. Zwiernik.
Property testing in graphical models: testing small separation numbers.
(PDF )
F. Calvillo,
L. Devroye,
and G. Lugosi.
Subtractive random forests with two choices,
(PDF )
G. Lugosi
and M. Matabuena,
Uncertainty quantification in metric spaces
(PDF )
L. Addario-Berry,
G. Lugosi,
and
R. Imbuzeiro Oliveira.
The top eigenvalue of uniformly random trees.
(PDF )
L. Addario-Berry,
S. Briend,
L. Devroye,
S. Donderwinkel,
C. Kerriou,
and G. Lugosi.
Random friend trees.
(PDF )
S. Briend,
C. Giraud,
G. Lugosi,
and
D. Sulem.,
Estimating the history of a random recursive tree.
(PDF )
C. Atamanchuk,
L. Devroye,
and G. Lugosi.
On the size of temporal cliques in subcritical random temporal graphs.
(PDF )
S. Briend,
G. Lugosi, and
R. Imbuzeiro Oliveira.
On the quality of randomized approximations of Tukey's depth.
(PDF )
S. Briend,
L. Devroye, and
G. Lugosi.
Broadcasting in random recursive dags.
(PDF )
G. Lugosi and
G. Neu.
Online-to-PAC Conversions: Generalization Bounds via Regret Analysis.
(PDF )
G. Lugosi,
G. Neu,
and J. Olkhovskaya.
Learning to maximize global influence from local observations.
(PDF )
Conference papers with no journal version:
N. Cesa-Bianchi,
Claudio Gentile,
G. Lugosi,
and
G. Neu.
Boltzmann exploration done right.
NIPS, 2017.
(PDF )
T. Liu,
G. Lugosi,
G. Neu
and
D. Tao.
Algorithmic stability and hypothesis complexity.
34th International Conference on Machine Learning (ICML), 2017.
(PDF )
Y. Seldin,
and G. Lugosi,
(2017).
An Improved Parametrization and Analysis of the EXP3++ Algorithm for Stochastic and Adversarial Bandits.
COLT 2017. (PDF )
Y. Seldin,
and G. Lugosi,
(2016).
A Lower Bound for Multi-Armed Bandits with Expert Advice
EWRL 2016. (PDF )
M. Alamgir,
G. Lugosi,
and U. von Luxburg (2014).
Density-preserving quantization with application to graph.
downsampling
COLT 2014. (PDF )
N. Cesa-Bianchi,
P. Gaillard,
G. Lugosi,
and G. Stoltz (2012).
Mirror descent meets fixed share (and feels no regret).
NIPS 2012. (PDF )
G. Lugosi,
O.Papaspiliopoulos,
and G. Stoltz
(2009).
Online Multi-task Learning with Hard Constraints.
(PDF)
COLT 2009.