Alessandro Nuara

According to our database1, Alessandro Nuara authored at least 14 papers between 2016 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2023
Dynamic Pricing with Volume Discounts in Online Settings.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Safe Online Bid Optimization with Return-On-Investment and Budget Constraints subject to Uncertainty.
CoRR, 2022

Online joint bid/daily budget optimization of Internet advertising campaigns.
Artif. Intell., 2022

Pricing the Long Tail by Explainable Product Aggregation and Monotonic Bandits.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

2021
Machine learning algorithms for the optimization of internet advertising campaigns.
PhD thesis, 2021

Gaussian Approximation for Bias Reduction in Q-Learning.
J. Mach. Learn. Res., 2021

2020
A privacy-preserving tests optimization algorithm for epidemics containment.
CoRR, 2020

Driving Exploration by Maximum Distribution in Gaussian Process Bandits.
Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

2019
Dealing with Interdependencies and Uncertainty in Multi-Channel Advertising Campaigns Optimization.
Proceedings of the World Wide Web Conference, 2019

2018
Targeting Optimization for Internet Advertising by Learning from Logged Bandit Feedback.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

A Combinatorial-Bandit Algorithm for the Online Joint Bid/Budget Optimization of Pay-per-Click Advertising Campaigns.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Exploiting structure and uncertainty of Bellman updates in Markov decision processes.
Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

Estimating the Maximum Expected Value in Continuous Reinforcement Learning Problems.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Estimating Maximum Expected Value through Gaussian Approximation.
Proceedings of the 33nd International Conference on Machine Learning, 2016


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