フォロー
Pier Giuseppe Sessa
Pier Giuseppe Sessa
Google DeepMind
確認したメール アドレス: google.com - ホームページ
タイトル
引用先
引用先
Gemma: Open models based on gemini research and technology
G Team, T Mesnard, C Hardin, R Dadashi, S Bhupatiraju, S Pathak, ...
arXiv preprint arXiv:2403.08295, 2024
5892024
Gemma 2: Improving open language models at a practical size
G Team, M Riviere, S Pathak, PG Sessa, C Hardin, S Bhupatiraju, ...
arXiv preprint arXiv:2408.00118, 2024
1412024
Exploring the Vickrey-Clarke-Groves mechanism for electricity markets
PG Sessa, N Walton, M Kamgarpour
IFAC-PapersOnLine 50 (1), 189-194, 2017
502017
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
442019
Charline Le Lan, Christopher A
G Team, T Mesnard, C Hardin, R Dadashi, S Bhupatiraju, S Pathak, ...
312024
Boosting search engines with interactive agents
L Adolphs, B Boerschinger, C Buck, MC Huebscher, M Ciaramita, ...
arXiv preprint arXiv:2109.00527, 2021
252021
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
242020
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
242019
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
212020
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
192020
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
142019
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
142018
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
122022
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
112022
Gemma 2: Improving open language models at a practical size, 2024
G Team, M Riviere, S Pathak, PG Sessa, C Hardin, S Bhupatiraju, ...
URL https://arxiv. org/abs/2408.00118 1 (2), 3, 0
11
Bond: Aligning llms with best-of-n distillation
PG Sessa, R Dadashi, L Hussenot, J Ferret, N Vieillard, A Ramé, ...
arXiv preprint arXiv:2407.14622, 2024
102024
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
102024
Filtering approaches for online train motion estimation with onboard power measurements
PG Sessa, V De Martinis, F Corman
Computer‐Aided Civil and Infrastructure Engineering 35 (5), 415-429, 2020
102020
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
102020
Exploiting structure of chance constrained programs via submodularity
D Frick*, PG Sessa*, TA Wood, M Kamgarpour
Automatica 105, 89-95, 2019
72019
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