引用次数
引用: 6,700
H-指数: 37
I10-指数 : 67
出版物: 99
The pareto regret frontier for bandits
Tor Lattimore
neural information processing systems 28 208 -216
11
2015
Free Lunch for optimisation under the universal distribution
Tom Everitt , Tor Lattimore , Marcus Hutter
congress on evolutionary computation 167 -174
9
2014
Bounded Regret for Finite-Armed Structured Bandits
Remi Munos , Tor Lattimore
neural information processing systems 27 550 -558
33
2014
Linear multi-resource allocation with semi-bandit feedback
Csaba Szepesvári , Tor Lattimore , Koby Crammer
neural information processing systems 28 964 -972
18
2015
Regret Analysis of the Anytime Optimally Confident UCB Algorithm
Tor Lattimore
arXiv: Learning
18
2016
A Scale Free Algorithm for Stochastic Bandits with Bounded Kurtosis
Tor Lattimore
neural information processing systems 30 1584 -1593
5
2017
Online Learning with Gated Linear Networks
Joel Veness , Tor Lattimore , Agnieszka Grabska-Barwinska , Peter Toth
arXiv: Learning
23
2017
Soft-Bayes: Prod for Mixtures of Experts with Log-Loss.
Tor Lattimore , Shane Legg , Laurent Orseau
algorithmic learning theory 372 -399
5
2017
Following the Leader and Fast Rates in Online Linear Prediction: Curved Constraint Sets and Other Regularities
Csaba Szepesvári , Tor Lattimore , Ruitong Huang , András György
Journal of Machine Learning Research 18 ( 145) 1 -31
24
2017
Refining the Confidence Level for Optimistic Bandit Strategies
Tor Lattimore
Journal of Machine Learning Research 19 ( 20) 1 -32
16
2018
Theory of general reinforcement learning
Tor Lattimore
The Australian National University
12
2014
Conservative bandits
Csaba Szepesvári , Tor Lattimore , Roshan Shariff , Yifan Wu
international conference on machine learning 1254 -1262
27
2016
Single-Agent Policy Tree Search With Guarantees
Tor Lattimore , Théophane Weber , Laurent Orseau , Levi H. S. Lelis
neural information processing systems 31 3201 -3211
1
2018
TopRank: A practical algorithm for online stochastic ranking
Tor Lattimore , Branislav Kveton , Shuai Li , Csaba Szepesvari
neural information processing systems 31 3945 -3954
26
2018
Regret Analysis of the Finite-Horizon Gittins Index Strategy for Multi-Armed Bandits
Tor Lattimore
conference on learning theory 1214 -1245
5
2016
Refined Lower Bounds for Adversarial Bandits
Sébastien Gerchinovitz , Tor Lattimore
neural information processing systems 29 1190 -1198
22
2016
Cleaning up the neighborhood: A full classification for adversarial partial monitoring
Csaba Szepesvári , Tor Lattimore
algorithmic learning theory 529 -556
7
2019
Unifying PAC and Regret: Uniform PAC Bounds for Episodic Reinforcement Learning
Emma Brunskill , Tor Lattimore , Christoph Dann
neural information processing systems 30 5713 -5723
88
2017
Online Learning to Rank with Features.
Csaba Szepesvári , Tor Lattimore , Shuai Li
international conference on machine learning 3856 -3865
3
2019
On Explore-Then-Commit strategies
Aurélien Garivier , Tor Lattimore , Emilie Kaufmann
neural information processing systems 29 784 -792
28
2016