Francesco Trovò

Orcid: 0000-0001-5796-7667

According to our database1, Francesco Trovò authored at least 49 papers between 2012 and 2024.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Other 

Links

On csauthors.net:

Bibliography

2024
Evolving Fuzzy Prediction Intervals in Nonstationary Environments.
IEEE Trans. Emerg. Top. Comput. Intell., February, 2024

2023
IWDA: Importance Weighting for Drift Adaptation in Streaming Supervised Learning Problems.
IEEE Trans. Neural Networks Learn. Syst., October, 2023

ARLO: A framework for Automated Reinforcement Learning.
Expert Syst. Appl., August, 2023

Best Arm Identification for Stochastic Rising Bandits.
CoRR, 2023

Advancing Fraud Detection Systems Through Online Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track, 2023

MetaLung: Towards a Secure Architecture for Lung Cancer Patient Care on the Metaverse.
Proceedings of the IEEE International Conference on Metaverse Computing, 2023

Constrained Phi-Equilibria.
Proceedings of the International Conference on Machine Learning, 2023

Optimal Rates and Efficient Algorithms for Online Bayesian Persuasion.
Proceedings of the International Conference on Machine Learning, 2023

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

2022
Last-iterate Convergence to Trembling-hand Perfect Equilibria.
CoRR, 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

Sequential Information Design: Learning to Persuade in the Dark.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 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

Multi-Armed Bandit Problem with Temporally-Partitioned Rewards: When Partial Feedback Counts.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Stochastic Rising Bandits.
Proceedings of the International Conference on Machine Learning, 2022

Safe Learning in Tree-Form Sequential Decision Making: Handling Hard and Soft Constraints.
Proceedings of the International Conference on Machine Learning, 2022

Dark-Pool Smart Order Routing: a Combinatorial Multi-armed Bandit Approach.
Proceedings of the 3rd ACM International Conference on AI in Finance, 2022

The Evolutionary Dynamics of Soft-Max Policy Gradient in Multi-Agent Settings.
Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

2021
Adapting Bandit Algorithms for Settings with Sequentially Available Arms.
CoRR, 2021

Exploiting History Data for Nonstationary Multi-armed Bandit.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Conservative Online Convex Optimization.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Exploiting Opponents Under Utility Constraints in Sequential Games.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020
Sliding-Window Thompson Sampling for Non-Stationary Settings.
J. Artif. Intell. Res., 2020

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

Dealing with transaction costs in portfolio optimization: online gradient descent with momentum.
Proceedings of the ICAIF '20: The First ACM International Conference on AI in Finance, 2020

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

Learning Probably Approximately Correct Maximin Strategies in Simulation-Based Games with Infinite Strategy Spaces.
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
Improving multi-armed bandit algorithms in online pricing settings.
Int. J. Approx. Reason., 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
An Ensemble Approach for Cognitive Fault Detection and Isolation in Sensor Networks.
Int. J. Neural Syst., 2017

Regret Minimization Algorithms for the Followers Behaviour Identification in Leadership Games.
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Risk-averse trees for learning from logged bandit feedback.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Unimodal Thompson Sampling for Graph-Structured Arms.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Making Intelligent the Embedded Systems Through Cognitive Outlier and Fault Detection.
Proceedings of the Advances in Neural Networks - Computational Intelligence for ICT, 2016

Machine Learning Techniques for Stackelberg Security Games: a Survey.
CoRR, 2016

Budgeted Multi-Armed Bandit in Continuous Action Space.
Proceedings of the ECAI 2016 - 22nd European Conference on Artificial Intelligence, 29 August-2 September 2016, The Hague, The Netherlands, 2016

2015
A cognitive fault detection and diagnosis system for sensor networks.
PhD thesis, 2015

Truthful learning mechanisms for multi-slot sponsored search auctions with externalities.
Artif. Intell., 2015

2014
A Self-Building and Cluster-Based Cognitive Fault Diagnosis System for Sensor Networks.
IEEE Trans. Neural Networks Learn. Syst., 2014

An Ensemble of HMMs for Cognitive Fault Detection in Distributed Sensor Networks.
Proceedings of the Artificial Intelligence Applications and Innovations, 2014

Learning causal dependencies to etect and diagnose faults in sensor networks.
Proceedings of the IEEE Symposium on Intelligent Embedded Systems, 2014

On Power and Energy Consumption Modeling for Smart Mobile Devices.
Proceedings of the 12th IEEE International Conference on Embedded and Ubiquitous Computing, 2014

2013
Adaptive and Flexible Smartphone Power Modeling.
Mob. Networks Appl., 2013

2012
A truthful learning mechanism for contextual multi-slot sponsored search auctions with externalities.
Proceedings of the 13th ACM Conference on Electronic Commerce, 2012

A "Learning from Models" Cognitive Fault Diagnosis System.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2012, 2012

A truthful learning mechanism for multi-slot sponsored search auctions with externalities.
Proceedings of the International Conference on Autonomous Agents and Multiagent Systems, 2012


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