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Alberto Marchesi 0001
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- affiliation (PhD 2020): Polytechnic University of Milan, Italy
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- Alberto Marchesi — disambiguation page
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2020 – today
- 2024
- [c37]Martino Bernasconi, Alberto Marchesi, Francesco Trovò:
Learning Extensive-Form Perfect Equilibria in Two-Player Zero-Sum Sequential Games. AISTATS 2024: 2152-2160 - [c36]Matteo Castiglioni, Alberto Latino, Alberto Marchesi, Giulia Romano, Nicola Gatti, Chokha Palayamkottai:
Finding Effective Ad Allocations: How to Exploit User History. AAMAS 2024: 262-270 - [c35]Francesco Bacchiocchi, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti:
Learning Optimal Contracts: How to Exploit Small Action Spaces. ICLR 2024 - [c34]Francesco Emanuele Stradi, Jacopo Germano, Gianmarco Genalti, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti:
Online Learning in CMDPs: Handling Stochastic and Adversarial Constraints. ICML 2024 - [i38]Francesco Bacchiocchi, Francesco Emanuele Stradi, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti:
Markov Persuasion Processes: Learning to Persuade from Scratch. CoRR abs/2402.03077 (2024) - [i37]Martino Bernasconi, Matteo Castiglioni, Alberto Marchesi:
Regret-Minimizing Contracts: Agency Under Uncertainty. CoRR abs/2402.13156 (2024) - [i36]Francesco Emanuele Stradi, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti:
Learning Adversarial MDPs with Stochastic Hard Constraints. CoRR abs/2403.03672 (2024) - [i35]Francesco Bacchiocchi, Matteo Bollini, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti:
The Sample Complexity of Stackelberg Games. CoRR abs/2405.06977 (2024) - [i34]Francesco Emanuele Stradi, Anna Lunghi, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti:
Learning Constrained Markov Decision Processes With Non-stationary Rewards and Constraints. CoRR abs/2405.14372 (2024) - [i33]Francesco Emanuele Stradi, Anna Lunghi, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti:
Best-of-Both-Worlds Policy Optimization for CMDPs with Bandit Feedback. CoRR abs/2410.02269 (2024) - [i32]Francesco Emanuele Stradi, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti:
Optimal Strong Regret and Violation in Constrained MDPs via Policy Optimization. CoRR abs/2410.02275 (2024) - 2023
- [j11]Matteo Castiglioni
, Andrea Celli, Alberto Marchesi, Nicola Gatti
Regret minimization in online Bayesian persuasion: Handling adversarial receiver's types under full and partial feedback models. Artif. Intell. 314: 103821 (2023) - [j10]Matteo Castiglioni, Alberto Marchesi, Nicola Gatti
Designing menus of contracts efficiently: The power of randomization. Artif. Intell. 318: 103881 (2023) - [j9]Matteo Castiglioni, Alberto Marchesi, Giulia Romano, Nicola Gatti
Increasing revenue in Bayesian posted price auctions through signaling. Artif. Intell. 323: 103990 (2023) - [c33]Martino Bernasconi, Matteo Castiglioni, Andrea Celli, Alberto Marchesi, Francesco Trovò, Nicola Gatti:
Optimal Rates and Efficient Algorithms for Online Bayesian Persuasion. ICML 2023: 2164-2183 - [c32]Martino Bernasconi, Matteo Castiglioni, Alberto Marchesi, Francesco Trovò, Nicola Gatti:
Constrained Phi-Equilibria. ICML 2023: 2184-2205 - [c31]Martino Bernasconi, Matteo Castiglioni, Alberto Marchesi, Mirco Mutti:
Persuading Farsighted Receivers in MDPs: the Power of Honesty. NeurIPS 2023 - [c30]Matteo Castiglioni
Multi-Agent Contract Design: How to Commission Multiple Agents with Individual Outcomes. EC 2023: 412-448 - [i31]Martino Bernasconi, Matteo Castiglioni, Alberto Marchesi, Francesco Trovò, Nicola Gatti:
Constrained Phi-Equilibria. CoRR abs/2301.13600 (2023) - [i30]Matteo Castiglioni, Alberto Marchesi, Nicola Gatti:
Multi-Agent Contract Design: How to Commission Multiple Agents with Individual Outcome. CoRR abs/2301.13654 (2023) - [i29]Matteo Castiglioni, Francesco Bacchiocchi, Alberto Marchesi, Giulia Romano, Nicola Gatti:
Selling Information while Being an Interested Party. CoRR abs/2301.13790 (2023) - [i28]Martino Bernasconi, Matteo Castiglioni, Andrea Celli, Alberto Marchesi, Nicola Gatti, Francesco Trovò:
Optimal Rates and Efficient Algorithms for Online Bayesian Persuasion. CoRR abs/2303.01296 (2023) - [i27]Jacopo Germano, Francesco Emanuele Stradi, Gianmarco Genalti, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti:
A Best-of-Both-Worlds Algorithm for Constrained MDPs with Long-Term Constraints. CoRR abs/2304.14326 (2023) - [i26]Martino Bernasconi, Matteo Castiglioni, Alberto Marchesi, Mirco Mutti:
Persuading Farsighted Receivers in MDPs: the Power of Honesty. CoRR abs/2306.12221 (2023) - [i25]Francesco Bacchiocchi, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti:
Learning Optimal Contracts: How to Exploit Small Action Spaces. CoRR abs/2309.09801 (2023) - 2022
- [j8]Matteo Castiglioni, Alberto Marchesi, Nicola Gatti
Bayesian agency: Linear versus tractable contracts. Artif. Intell. 307: 103684 (2022) - [j7]Gabriele Farina
Simple Uncoupled No-regret Learning Dynamics for Extensive-form Correlated Equilibrium. J. ACM 69(6): 41:1-41:41 (2022) - [c29]Matteo Castiglioni, Diodato Ferraioli, Nicola Gatti, Alberto Marchesi, Giulia Romano:
Efficiency of Ad Auctions with Price Displaying. AAAI 2022: 4933-4940 - [c28]Matteo Castiglioni, Giulia Romano, Alberto Marchesi, Nicola Gatti:
Signaling in Posted Price Auctions. AAAI 2022: 4941-4948 - [c27]Matteo Castiglioni, Alberto Marchesi, Nicola Gatti:
Bayesian Persuasion Meets Mechanism Design: Going Beyond Intractability with Type Reporting. AAMAS 2022: 226-234 - [c26]Martino Bernasconi, Federico Cacciamani, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti, Francesco Trovò:
Safe Learning in Tree-Form Sequential Decision Making: Handling Hard and Soft Constraints. ICML 2022: 1854-1873 - [c25]Francesco Bacchiocchi, Matteo Castiglioni, Alberto Marchesi, Giulia Romano, Nicola Gatti:
Public Signaling in Bayesian Ad Auctions. IJCAI 2022: 39-45 - [c24]Giulia Romano, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti:
The Power of Media Agencies in Ad Auctions: Improving Utility through Coordinated Bidding. IJCAI 2022: 461-467 - [c23]Martino Bernasconi, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti, Francesco Trovò:
Sequential Information Design: Learning to Persuade in the Dark. NeurIPS 2022 - [c22]Matteo Castiglioni, Andrea Celli, Alberto Marchesi, Giulia Romano, Nicola Gatti:
A Unifying Framework for Online Optimization with Long-Term Constraints. NeurIPS 2022 - [c21]Matteo Castiglioni, Alberto Marchesi, Nicola Gatti:
Designing Menus of Contracts Efficiently: The Power of Randomization. EC 2022: 705-735 - [i24]Francesco Bacchiocchi, Matteo Castiglioni, Alberto Marchesi, Giulia Romano, Nicola Gatti:
Public Signaling in Bayesian Ad Auctions. CoRR abs/2201.09728 (2022) - [i23]Matteo Castiglioni, Giulia Romano, Alberto Marchesi, Nicola Gatti:
Signaling in Posted Price Auctions. CoRR abs/2201.12183 (2022) - [i22]Matteo Castiglioni, Diodato Ferraioli, Nicola Gatti, Alberto Marchesi, Giulia Romano:
Efficiency of Ad Auctions with Price Displaying. CoRR abs/2201.12275 (2022) - [i21]Matteo Castiglioni, Alberto Marchesi, Nicola Gatti:
Bayesian Persuasion Meets Mechanism Design: Going Beyond Intractability with Type Reporting. CoRR abs/2202.00605 (2022) - [i20]Matteo Castiglioni, Alberto Marchesi, Nicola Gatti:
Designing Menus of Contracts Efficiently: The Power of Randomization. CoRR abs/2202.10966 (2022) - [i19]Giulia Romano, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti:
The Power of Media Agencies in Ad Auctions: Improving Utility through Coordinated Bidding. CoRR abs/2204.13772 (2022) - [i18]Martino Bernasconi
Last-iterate Convergence to Trembling-hand Perfect Equilibria. CoRR abs/2208.08238 (2022) - [i17]Martino Bernasconi
Sequential Information Design: Learning to Persuade in the Dark. CoRR abs/2209.03927 (2022) - [i16]Matteo Castiglioni, Andrea Celli, Alberto Marchesi, Giulia Romano, Nicola Gatti:
A Unifying Framework for Online Optimization with Long-Term Constraints. CoRR abs/2209.07454 (2022) - 2021
- [j6]Matteo Castiglioni
Committing to correlated strategies with multiple leaders. Artif. Intell. 300: 103549 (2021) - [c20]Matteo Castiglioni, Andrea Celli, Alberto Marchesi, Nicola Gatti:
Signaling in Bayesian Network Congestion Games: the Subtle Power of Symmetry. AAAI 2021: 5252-5259 - [c19]Alberto Marchesi, Nicola Gatti:
Trembling-Hand Perfection and Correlation in Sequential Games. AAAI 2021: 5566-5574 - [c18]Giulia Romano, Gianluca Tartaglia, Alberto Marchesi, Nicola Gatti:
Online Posted Pricing with Unknown Time-Discounted Valuations. AAAI 2021: 5682-5689 - [c17]Matteo Castiglioni, Alberto Marchesi, Andrea Celli, Nicola Gatti:
Multi-Receiver Online Bayesian Persuasion. ICML 2021: 1314-1323 - [c16]Andrea Celli, Alberto Marchesi, Gabriele Farina, Nicola Gatti:
Decentralized No-regret Learning Algorithms for Extensive-form Correlated Equilibria (Extended Abstract). IJCAI 2021: 4755-4759 - [c15]Martino Bernasconi de Luca, Federico Cacciamani, Simone Fioravanti, Nicola Gatti, Alberto Marchesi, Francesco Trovò:
Exploiting Opponents Under Utility Constraints in Sequential Games. NeurIPS 2021: 13177-13188 - [c14]Matteo Castiglioni, Alberto Marchesi, Nicola Gatti:
Bayesian Agency: Linear versus Tractable Contracts. EC 2021: 285-286 - [i15]Gabriele Farina, Andrea Celli, Alberto Marchesi, Nicola Gatti:
Simple Uncoupled No-Regret Learning Dynamics for Extensive-Form Correlated Equilibrium. CoRR abs/2104.01520 (2021) - [i14]Matteo Castiglioni, Alberto Marchesi, Nicola Gatti:
Bayesian Agency: Linear versus Tractable Contracts. CoRR abs/2106.00319 (2021) - [i13]Matteo Castiglioni, Alberto Marchesi, Andrea Celli, Nicola Gatti:
Multi-Receiver Online Bayesian Persuasion. CoRR abs/2106.06480 (2021) - 2020
- [b1]Alberto Marchesi:
Leadership games: multiple followers, multiple leaders, and perfection. Polytechnic University of Milan, Italy, 2020 - [j5]Stefano Coniglio
Computing a Pessimistic Stackelberg Equilibrium with Multiple Followers: The Mixed-Pure Case. Algorithmica 82(5): 1189-1238 (2020) - [j4]Nicola Basilico
Bilevel programming methods for computing single-leader-multi-follower equilibria in normal-form and polymatrix games. EURO J. Comput. Optim. 8(1): 3-31 (2020) - [j3]Nicola Gatti
A characterization of quasi-perfect equilibria. Games Econ. Behav. 122: 240-255 (2020) - [c13]Alberto Marchesi, Francesco Trovò, Nicola Gatti:
Learning Probably Approximately Correct Maximin Strategies in Simulation-Based Games with Infinite Strategy Spaces. AAMAS 2020: 834-842 - [c12]Matteo Castiglioni, Andrea Celli, Alberto Marchesi, Nicola Gatti:
Online Bayesian Persuasion. NeurIPS 2020 - [c11]Andrea Celli, Alberto Marchesi, Gabriele Farina, Nicola Gatti:
No-Regret Learning Dynamics for Extensive-Form Correlated Equilibrium. NeurIPS 2020 - [i12]Matteo Castiglioni, Andrea Celli, Alberto Marchesi, Nicola Gatti:
Signaling in Bayesian Network Congestion Games: the Subtle Power of Symmetry. CoRR abs/2002.05190 (2020) - [i11]Andrea Celli, Alberto Marchesi, Gabriele Farina, Nicola Gatti:
No-regret learning dynamics for extensive-form correlated and coarse correlated equilibria. CoRR abs/2004.00603 (2020) - [i10]Giulia Romano, Gianluca Tartaglia, Alberto Marchesi, Nicola Gatti:
Online Posted Pricing with Unknown Time-Discounted Valuations. CoRR abs/2012.05774 (2020) - [i9]Alberto Marchesi, Nicola Gatti:
Trembling-Hand Perfection and Correlation in Sequential Games. CoRR abs/2012.06528 (2020)
2010 – 2019
- 2019
- [j2]Matteo Castiglioni, Alberto Marchesi, Nicola Gatti, Stefano Coniglio
Leadership in singleton congestion games: What is hard and what is easy. Artif. Intell. 277 (2019) - [c10]Alberto Marchesi, Gabriele Farina, Christian Kroer, Nicola Gatti, Tuomas Sandholm:
Quasi-Perfect Stackelberg Equilibrium. AAAI 2019: 2117-2124 - [c9]Matteo Castiglioni, Alberto Marchesi, Nicola Gatti:
Be a Leader or Become a Follower: The Strategy to Commit to with Multiple Leaders. IJCAI 2019: 123-129 - [c8]Alberto Marchesi, Matteo Castiglioni, Nicola Gatti:
Leadership in Congestion Games: Multiple User Classes and Non-Singleton Actions. IJCAI 2019: 485-491 - [c7]Andrea Celli, Alberto Marchesi, Tommaso Bianchi, Nicola Gatti:
Learning to Correlate in Multi-Player General-Sum Sequential Games. NeurIPS 2019: 13055-13065 - [i8]Matteo Castiglioni, Alberto Marchesi, Nicola Gatti:
Be a Leader or Become a Follower: The Strategy to Commit to with Multiple Leaders (Extended Version). CoRR abs/1905.13106 (2019) - [i7]Alberto Marchesi, Matteo Castiglioni, Nicola Gatti:
Leadership in Congestion Games: Multiple User Classes and Non-Singleton Actions (Extended Version). CoRR abs/1905.13108 (2019) - [i6]Andrea Celli, Alberto Marchesi, Tommaso Bianchi, Nicola Gatti:
Learning to Correlate in Multi-Player General-Sum Sequential Games. CoRR abs/1910.06228 (2019) - [i5]Alberto Marchesi, Francesco Trovò, Nicola Gatti:
Learning Probably Approximately Correct Maximin Strategies in Simulation-Based Games with Infinite Strategy Spaces. CoRR abs/1911.07755 (2019) - 2018
- [j1]Andrea Celli
Learning dynamics in limited-control repeated games. Intelligenza Artificiale 12(2): 89-101 (2018) - [c6]Giuseppe De Nittis, Alberto Marchesi, Nicola Gatti:
Computing the Strategy to Commit to in Polymatrix Games. AAAI 2018: 989-996 - [c5]Gabriele Farina, Alberto Marchesi, Christian Kroer, Nicola Gatti, Tuomas Sandholm:
Trembling-Hand Perfection in Extensive-Form Games with Commitment. IJCAI 2018: 233-239 - [c4]Alberto Marchesi, Stefano Coniglio
Leadership in Singleton Congestion Games. IJCAI 2018: 447-453 - [i4]Giuseppe De Nittis, Alberto Marchesi, Nicola Gatti:
Computing the Strategy to Commit to in Polymatrix Games (Extended Version). CoRR abs/1807.11914 (2018) - [i3]Stefano Coniglio, Nicola Gatti, Alberto Marchesi:
Computing a Pessimistic Leader-Follower Equilibrium with Multiple Followers: the Mixed-Pure Case. CoRR abs/1808.01438 (2018) - [i2]Matteo Castiglioni, Alberto Marchesi, Nicola Gatti, Stefano Coniglio:
Leadership in Singleton Congestion Games: What is Hard and What is Easy. CoRR abs/1808.10209 (2018) - [i1]Alberto Marchesi, Gabriele Farina, Christian Kroer, Nicola Gatti, Tuomas Sandholm:
Quasi-Perfect Stackelberg Equilibrium. CoRR abs/1811.03871 (2018) - 2017
- [c3]Stefano Coniglio
Pessimistic Leader-Follower Equilibria with Multiple Followers. IJCAI 2017: 171-177 - [c2]Andrea Celli, Alberto Marchesi, Nicola Gatti:
On the Complexity of Nash Equilibrium Reoptimization. UAI 2017 - [c1]Nicola Basilico, Stefano Coniglio
Bilevel Programming Approaches to the Computation of Optimistic and Pessimistic Single-Leader-Multi-Follower Equilibria. SEA 2017: 31:1-31:14
Coauthor Index
Martino Bernasconi
aka: Martino Bernasconi de Luca
aka: Martino Bernasconi de Luca
[c36] [c35] [c34] [i38] [i37] [i36] [i35] [i34] [i33] [i32] [j11] [j10] [j9] [c33] [c32] [c31] [c30] [i31] [i30] [i29] [i28] [i27] [i26] [i25] [j8] [c29] [c28] [c27] [c26] [c25] [c24] [c23] [c22] [c21] [i24] [i23] [i22] [i21] [i20] [i19] [i17] [i16] [j6] [c20] [c17] [c14] [i14] [i13] [c12] [i12] [j2] [c9] [c8] [i8] [i7] [i2]
[c36] [c35] [c34] [i38] [i36] [i35] [i34] [i33] [i32] [j11] [j10] [j9] [c33] [c32] [c30] [i31] [i30] [i29] [i28] [i27] [i25] [j8] [j7] [c29] [c28] [c27] [c26] [c25] [c24] [c23] [c22] [c21] [i24] [i23] [i22] [i21] [i20] [i19] [i17] [i16] [j6] [c20] [c19] [c18] [c17] [c16] [c15] [c14] [i15] [i14] [i13] [j5] [j4] [j3] [c13] [c12] [c11] [i12] [i11] [i10] [i9] [j2] [c10] [c9] [c8] [c7] [i8] [i7] [i6] [i5] [c6] [c5] [c4] [i4] [i3] [i2] [i1] [c3] [c2] [c1]
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