受强制性开放获取政策约束的文章 - Pier Giuseppe Sessa了解详情
可在其他位置公开访问的文章：17 篇
Exploring the Vickrey-Clarke-Groves mechanism for electricity markets
PG Sessa, N Walton, M Kamgarpour
IFAC-PapersOnLine 50 (1), 189-194, 2017
强制性开放获取政策： European Commission
No-regret learning in unknown games with correlated payoffs
PG Sessa, I Bogunovic, M Kamgarpour, A Krause
Advances in Neural Information Processing Systems 32, 2019
强制性开放获取政策： Swiss National Science Foundation, European Commission
Learning to play sequential games versus unknown opponents
PG Sessa, I Bogunovic, M Kamgarpour, A Krause
Advances in neural information processing systems 33, 8971-8981, 2020
强制性开放获取政策： Swiss National Science Foundation, European Commission
Designing coalition-proof reverse auctions over continuous goods
O Karaca, PG Sessa, N Walton, M Kamgarpour
IEEE Transactions on Automatic Control 64 (11), 4803-4810, 2019
强制性开放获取政策： European Commission
Contextual games: Multi-agent learning with side information
PG Sessa, I Bogunovic, A Krause, M Kamgarpour
Advances in Neural Information Processing Systems 33, 21912-21922, 2020
强制性开放获取政策： Swiss National Science Foundation, European Commission
Mixed strategies for robust optimization of unknown objectives
PG Sessa, I Bogunovic, M Kamgarpour, A Krause
International Conference on Artificial Intelligence and Statistics, 2970-2980, 2020
强制性开放获取政策： Swiss National Science Foundation, European Commission
Bounding inefficiency of equilibria in continuous actions games using submodularity and curvature
PG Sessa, M Kamgarpour, A Krause
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
强制性开放获取政策： Swiss National Science Foundation, European Commission
From uncertainty data to robust policies for temporal logic planning
PG Sessa, D Frick, TA Wood, M Kamgarpour
Proceedings of the 21st International Conference on Hybrid Systems …, 2018
强制性开放获取政策： Swiss National Science Foundation
Efficient model-based multi-agent reinforcement learning via optimistic equilibrium computation
PG Sessa, M Kamgarpour, A Krause
International Conference on Machine Learning, 19580-19597, 2022
强制性开放获取政策： Swiss National Science Foundation, European Commission
Movement penalized Bayesian optimization with application to wind energy systems
SS Ramesh, PG Sessa, A Krause, I Bogunovic
Advances in Neural Information Processing Systems 35, 27036-27048, 2022
强制性开放获取政策： European Commission
No-regret learning from partially observed data in repeated auctions
O Karaca*, PG Sessa*, A Leidi, M Kamgarpour
IFAC-PapersOnLine 53 (2), 14-19, 2020
强制性开放获取政策： Swiss National Science Foundation, European Commission
Distributionally robust model-based reinforcement learning with large state spaces
SS Ramesh, PG Sessa, Y Hu, A Krause, I Bogunovic
International Conference on Artificial Intelligence and Statistics, 100-108, 2024
强制性开放获取政策： UK Engineering and Physical Sciences Research Council
Exploiting structure of chance constrained programs via submodularity
D Frick*, PG Sessa*, TA Wood, M Kamgarpour
Automatica 105, 89-95, 2019
强制性开放获取政策： Swiss National Science Foundation, US National Aeronautics and Space …
Online submodular resource allocation with applications to rebalancing shared mobility systems
PG Sessa, I Bogunovic, A Krause, M Kamgarpour
International Conference on Machine Learning, 9455-9464, 2021
强制性开放获取政策： Swiss National Science Foundation, European Commission
Multitask learning with no regret: from improved confidence bounds to active learning
PG Sessa, P Laforgue, N Cesa-Bianchi, A Krause
Advances in Neural Information Processing Systems 36, 6770-6781, 2023
强制性开放获取政策： European Commission
Adversarial Causal Bayesian Optimization
S Sussex, PG Sessa, A Makarova, A Krause
The Twelfth International Conference on Learning Representations, 2023
强制性开放获取政策： Swiss National Science Foundation, European Commission
How bad is selfish driving? Bounding the inefficiency of equilibria in urban driving games
A Zanardi, PG Sessa, N Käslin, S Bolognani, A Censi, E Frazzoli
IEEE Robotics and Automation Letters 8 (4), 2293-2300, 2023
强制性开放获取政策： Swiss National Science Foundation
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