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2020 – today
- 2023
[j28]Massimiliano Bonetti, Lorenzo Bisi
, Marcello Restelli:
Risk-averse optimization of reward-based coherent risk measures. Artif. Intell. 316: 103845 (2023)- [j27]Marco Mussi, Davide Lombarda, Alberto Maria Metelli, Francesco Trovò, Marcello Restelli:
ARLO: A framework for Automated Reinforcement Learning. Expert Syst. Appl. 224: 119883 (2023) - [j26]Mirco Mutti, Riccardo De Santi, Piersilvio De Bartolomeis, Marcello Restelli:
Convex Reinforcement Learning in Finite Trials. J. Mach. Learn. Res. 24: 250:1-250:42 (2023) - [j25]Filippo Fedeli, Alberto Maria Metelli, Francesco Trovò, Marcello Restelli:
IWDA: Importance Weighting for Drift Adaptation in Streaming Supervised Learning Problems. IEEE Trans. Neural Networks Learn. Syst. 34(10): 6813-6823 (2023) - [c144]Amarildo Likmeta, Matteo Sacco, Alberto Maria Metelli, Marcello Restelli:
Wasserstein Actor-Critic: Directed Exploration via Optimism for Continuous-Actions Control. AAAI 2023: 8782-8790 - [c143]Davide Maran, Alberto Maria Metelli, Marcello Restelli:
Tight Performance Guarantees of Imitator Policies with Continuous Actions. AAAI 2023: 9073-9080 - [c142]Mirco Mutti, Riccardo De Santi, Emanuele Rossi, Juan Felipe Calderón, Michael M. Bronstein, Marcello Restelli:
Provably Efficient Causal Model-Based Reinforcement Learning for Systematic Generalization. AAAI 2023: 9251-9259 - [c141]Luca Sabbioni, Luca Al Daire, Lorenzo Bisi, Alberto Maria Metelli, Marcello Restelli:
Simultaneously Updating All Persistence Values in Reinforcement Learning. AAAI 2023: 9668-9676 - [c140]Marco Mussi, Gianmarco Genalti, Alessandro Nuara, Francesco Trovò, Marcello Restelli, Nicola Gatti:
Dynamic Pricing with Volume Discounts in Online Settings. AAAI 2023: 15560-15568 - [c139]Alberto Maria Metelli, Mirco Mutti, Marcello Restelli:
A Tale of Sampling and Estimation in Discounted Reinforcement Learning. AISTATS 2023: 4575-4601 - [c138]Conor F. Hayes, Roxana Radulescu, Eugenio Bargiacchi, Johan Källström, Matthew Macfarlane, Mathieu Reymond, Timothy Verstraeten, Luisa M. Zintgraf, Richard Dazeley, Fredrik Heintz, Enda Howley, Athirai A. Irissappane, Patrick Mannion, Ann Nowé, Gabriel de Oliveira Ramos, Marcello Restelli, Peter Vamplew, Diederik M. Roijers:
A Brief Guide to Multi-Objective Reinforcement Learning and Planning. AAMAS 2023: 1988-1990 - [c137]Ahmed Elmaraghy, Jacopo Montali, Marcello Restelli, Francesco Causone, Pierpaolo Ruttico:
Towards an AI-Based Framework for Autonomous Design and Construction: Learning from Reinforcement Learning Success in RTS Games. CAAD Futures 2023: 376-392 - [c136]Alberto Maria Metelli, Filippo Lazzati, Marcello Restelli:
Towards Theoretical Understanding of Inverse Reinforcement Learning. ICML 2023: 24555-24591 - [c135]Marco Mussi, Alberto Maria Metelli, Marcello Restelli:
Dynamical Linear Bandits. ICML 2023: 25563-25587 - [c134]Riccardo Poiani, Alberto Maria Metelli, Marcello Restelli:
Truncating Trajectories in Monte Carlo Reinforcement Learning. ICML 2023: 27994-28042 - [c133]Khaled Eldowa, Nicolò Cesa-Bianchi, Alberto Maria Metelli, Marcello Restelli:
Information-Theoretic Regret Bounds for Bandits with Fixed Expert Advice. ITW 2023: 30-35 - [c132]Luca Sabbioni, Francesco Corda, Marcello Restelli:
Stepsize Learning for Policy Gradient Methods in Contextual Markov Decision Processes. ECML/PKDD (4) 2023: 506-523 - [c131]Alberto Maria Metelli, Samuele Meta, Marcello Restelli:
On the Relation between Policy Improvement and Off-Policy Minimum-Variance Policy Evaluation. UAI 2023: 1423-1433 - [i62]Marco Mussi, Alessandro Montenegro, Francesco Trovò, Marcello Restelli, Alberto Maria Metelli:
Best Arm Identification for Stochastic Rising Bandits. CoRR abs/2302.07510 (2023) - [i61]Amarildo Likmeta, Matteo Sacco, Alberto Maria Metelli, Marcello Restelli:
Wasserstein Actor-Critic: Directed Exploration via Optimism for Continuous-Actions Control. CoRR abs/2303.02378 (2023) - [i60]Khaled Eldowa, Nicolò Cesa-Bianchi, Alberto Maria Metelli, Marcello Restelli:
Information-Theoretic Regret Bounds for Bandits with Fixed Expert Advice. CoRR abs/2303.08102 (2023) - [i59]Paolo Bonetti, Alberto Maria Metelli, Marcello Restelli:
Interpretable Linear Dimensionality Reduction based on Bias-Variance Analysis. CoRR abs/2303.14734 (2023) - [i58]Alberto Maria Metelli, Mirco Mutti, Marcello Restelli:
A Tale of Sampling and Estimation in Discounted Reinforcement Learning. CoRR abs/2304.05073 (2023) - [i57]Alberto Maria Metelli, Filippo Lazzati, Marcello Restelli:
Towards Theoretical Understanding of Inverse Reinforcement Learning. CoRR abs/2304.12966 (2023) - [i56]Riccardo Poiani, Alberto Maria Metelli, Marcello Restelli:
Truncating Trajectories in Monte Carlo Reinforcement Learning. CoRR abs/2305.04361 (2023) - [i55]Gianluca Drappo, Alberto Maria Metelli, Marcello Restelli:
An Option-Dependent Analysis of Regret Minimization Algorithms in Finite-Horizon Semi-Markov Decision Processes. CoRR abs/2305.06936 (2023) - [i54]Luca Sabbioni, Francesco Corda, Marcello Restelli:
Stepsize Learning for Policy Gradient Methods in Contextual Markov Decision Processes. CoRR abs/2306.07741 (2023) - [i53]Paolo Bonetti, Alberto Maria Metelli, Marcello Restelli:
Nonlinear Feature Aggregation: Two Algorithms driven by Theory. CoRR abs/2306.11143 (2023) - [i52]Riccardo Poiani, Alberto Maria Metelli, Marcello Restelli:
Pure Exploration under Mediators' Feedback. CoRR abs/2308.15552 (2023) - [i51]Mirco Mutti, Riccardo De Santi, Marcello Restelli, Alexander Marx, Giorgia Ramponi:
Exploiting Causal Graph Priors with Posterior Sampling for Reinforcement Learning. CoRR abs/2310.07518 (2023) - [i50]Paolo Bonetti, Alberto Maria Metelli, Marcello Restelli:
Causal Feature Selection via Transfer Entropy. CoRR abs/2310.11059 (2023) - 2022
- [j24]Conor F. Hayes, Roxana Radulescu, Eugenio Bargiacchi, Johan Källström, Matthew Macfarlane, Mathieu Reymond, Timothy Verstraeten, Luisa M. Zintgraf, Richard Dazeley, Fredrik Heintz, Enda Howley, Athirai A. Irissappane, Patrick Mannion, Ann Nowé, Gabriel de Oliveira Ramos, Marcello Restelli, Peter Vamplew, Diederik M. Roijers:
A practical guide to multi-objective reinforcement learning and planning. Auton. Agents Multi Agent Syst. 36(1): 26 (2022) - [j23]Alessandro Nuara, Francesco Trovò, Nicola Gatti, Marcello Restelli:
Online joint bid/daily budget optimization of Internet advertising campaigns. Artif. Intell. 305: 103663 (2022) - [j22]Lorenzo Bisi, Davide Santambrogio, Federico Sandrelli, Andrea Tirinzoni, Brian D. Ziebart, Marcello Restelli:
Risk-averse policy optimization via risk-neutral policy optimization. Artif. Intell. 311: 103765 (2022) - [j21]Alberto Maria Metelli, Guglielmo Manneschi, Marcello Restelli:
Policy space identification in configurable environments. Mach. Learn. 111(6): 2093-2145 (2022) - [j20]Matteo Papini, Matteo Pirotta, Marcello Restelli:
Smoothing policies and safe policy gradients. Mach. Learn. 111(11): 4081-4137 (2022) - [c130]Pierre Liotet, Francesco Vidaich, Alberto Maria Metelli, Marcello Restelli:
Lifelong Hyper-Policy Optimization with Multiple Importance Sampling Regularization. AAAI 2022: 7525-7533 - [c129]Mirco Mutti, Mattia Mancassola, Marcello Restelli:
Unsupervised Reinforcement Learning in Multiple Environments. AAAI 2022: 7850-7858 - [c128]Mirco Mutti, Stefano Del Col, Marcello Restelli:
Reward-Free Policy Space Compression for Reinforcement Learning. AISTATS 2022: 3187-3203 - [c127]Khaled Eldowa, Lorenzo Bisi, Marcello Restelli:
Finite Sample Analysis of Mean-Volatility Actor-Critic for Risk-Averse Reinforcement Learning. AISTATS 2022: 10028-10066 - [c126]Manuel Occorso, Luca Sabbioni, Alberto Maria Metelli, Marcello Restelli:
Trust Region Meta Learning for Policy Optimization. Meta-Knowledge Transfer @ ECML/PKDD 2022: 62-74 - [c125]Martino Bernasconi, Stefano Martino, Edoardo Vittori, Francesco Trovò, Marcello Restelli:
Dark-Pool Smart Order Routing: a Combinatorial Multi-armed Bandit Approach. ICAIF 2022: 352-360 - [c124]Antonio Riva, Lorenzo Bisi, Pierre Liotet, Luca Sabbioni, Edoardo Vittori, Marco Pinciroli, Michele Trapletti, Marcello Restelli:
Addressing Non-Stationarity in FX Trading with Online Model Selection of Offline RL Experts. ICAIF 2022: 394-402 - [c123]Lorenzo Moro, Amarildo Likmeta, Enrico Prati, Marcello Restelli:
Goal-Directed Planning via Hindsight Experience Replay. ICLR 2022 - [c122]Angelo Damiani, Giorgio Manganini, Alberto Maria Metelli, Marcello Restelli:
Balancing Sample Efficiency and Suboptimality in Inverse Reinforcement Learning. ICML 2022: 4618-4629 - [c121]Pierre Liotet, Davide Maran, Lorenzo Bisi, Marcello Restelli:
Delayed Reinforcement Learning by Imitation. ICML 2022: 13528-13556 - [c120]Alberto Maria Metelli, Francesco Trovò, Matteo Pirola, Marcello Restelli:
Stochastic Rising Bandits. ICML 2022: 15421-15457 - [c119]Mirco Mutti, Riccardo De Santi, Marcello Restelli:
The Importance of Non-Markovianity in Maximum State Entropy Exploration. ICML 2022: 16223-16239 - [c118]Giulia Romano, Andrea Agostini, Francesco Trovò, Nicola Gatti, Marcello Restelli:
Multi-Armed Bandit Problem with Temporally-Partitioned Rewards: When Partial Feedback Counts. IJCAI 2022: 3401-3407 - [c117]Julen Cestero, Marco Quartulli, Alberto Maria Metelli, Marcello Restelli:
Storehouse: a Reinforcement Learning Environment for Optimizing Warehouse Management. IJCNN 2022: 1-9 - [c116]Marco Mussi, Gianmarco Genalti, Francesco Trovò, Alessandro Nuara, Nicola Gatti, Marcello Restelli:
Pricing the Long Tail by Explainable Product Aggregation and Monotonic Bandits. KDD 2022: 3623-3633 - [c115]Nicolò Felicioni, Maurizio Ferrari Dacrema, Marcello Restelli, Paolo Cremonesi:
Off-Policy Evaluation with Deficient Support Using Side Information. NeurIPS 2022 - [c114]Mirco Mutti, Riccardo De Santi, Piersilvio De Bartolomeis, Marcello Restelli:
Challenging Common Assumptions in Convex Reinforcement Learning. NeurIPS 2022 - [c113]Riccardo Poiani, Alberto Maria Metelli, Marcello Restelli:
Multi-Fidelity Best-Arm Identification. NeurIPS 2022 - [c112]Giorgia Ramponi, Marcello Restelli:
Learning in Markov games: Can we exploit a general-sum opponent? UAI 2022: 1665-1675 - [i49]Mirco Mutti, Riccardo De Santi, Piersilvio De Bartolomeis, Marcello Restelli:
Challenging Common Assumptions in Convex Reinforcement Learning. CoRR abs/2202.01511 (2022) - [i48]Mirco Mutti, Riccardo De Santi, Marcello Restelli:
The Importance of Non-Markovianity in Maximum State Entropy Exploration. CoRR abs/2202.03060 (2022) - [i47]Mirco Mutti, Riccardo De Santi, Emanuele Rossi, Juan Felipe Calderón, Michael M. Bronstein, Marcello Restelli:
Provably Efficient Causal Model-Based Reinforcement Learning for Systematic Generalization. CoRR abs/2202.06545 (2022) - [i46]Mirco Mutti, Stefano Del Col, Marcello Restelli:
Reward-Free Policy Space Compression for Reinforcement Learning. CoRR abs/2202.11079 (2022) - [i45]Pierre Liotet, Davide Maran, Lorenzo Bisi, Marcello Restelli:
Delayed Reinforcement Learning by Imitation. CoRR abs/2205.05569 (2022) - [i44]Marco Mussi, Davide Lombarda, Alberto Maria Metelli, Francesco Trovò, Marcello Restelli:
ARLO: A Framework for Automated Reinforcement Learning. CoRR abs/2205.10416 (2022) - [i43]Giulia Romano, Andrea Agostini, Francesco Trovò, Nicola Gatti, Marcello Restelli:
Multi-Armed Bandit Problem with Temporally-Partitioned Rewards: When Partial Feedback Counts. CoRR abs/2206.00586 (2022) - [i42]Julen Cestero, Marco Quartulli, Alberto Maria Metelli, Marcello Restelli:
Storehouse: a Reinforcement Learning Environment for Optimizing Warehouse Management. CoRR abs/2207.03851 (2022) - [i41]Sancho Salcedo-Sanz, Jorge Pérez-Aracil, Guido Ascenso, Javier Del Ser, David Casillas-Pérez, Christopher Kadow, Dusan Fister, David Barriopedro, Ricardo García-Herrera, Marcello Restelli, Matteo Giuliani, Andrea Castelletti:
Analysis, Characterization, Prediction and Attribution of Extreme Atmospheric Events with Machine Learning: a Review. CoRR abs/2207.07580 (2022) - [i40]Riccardo Poiani, Ciprian Stirbu, Alberto Maria Metelli, Marcello Restelli:
Optimizing Empty Container Repositioning and Fleet Deployment via Configurable Semi-POMDPs. CoRR abs/2207.12509 (2022) - [i39]Marco Mussi, Alberto Maria Metelli, Marcello Restelli:
Dynamical Linear Bandits. CoRR abs/2211.08997 (2022) - [i38]Marco Mussi, Gianmarco Genalti, Alessandro Nuara, Francesco Trovò, Marcello Restelli, Nicola Gatti:
Dynamic Pricing with Volume Discounts in Online Settings. CoRR abs/2211.09612 (2022) - [i37]Luca Sabbioni, Luca Al Daire, Lorenzo Bisi, Alberto Maria Metelli, Marcello Restelli:
Simultaneously Updating All Persistence Values in Reinforcement Learning. CoRR abs/2211.11620 (2022) - [i36]Alberto Maria Metelli, Francesco Trovò, Matteo Pirola, Marcello Restelli:
Stochastic Rising Bandits. CoRR abs/2212.03798 (2022) - [i35]Davide Maran, Alberto Maria Metelli, Marcello Restelli:
Tight Performance Guarantees of Imitator Policies with Continuous Actions. CoRR abs/2212.03922 (2022) - [i34]Francesco Bacchiocchi, Gianmarco Genalti, Davide Maran, Marco Mussi, Marcello Restelli, Nicola Gatti, Alberto Maria Metelli:
Autoregressive Bandits. CoRR abs/2212.06251 (2022) - 2021
- [j19]Alberto Maria Metelli, Matteo Pirotta, Daniele Calandriello, Marcello Restelli:
Safe Policy Iteration: A Monotonically Improving Approximate Policy Iteration Approach. J. Mach. Learn. Res. 22: 97:1-97:83 (2021) - [j18]Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters:
MushroomRL: Simplifying Reinforcement Learning Research. J. Mach. Learn. Res. 22: 131:1-131:5 (2021) - [j17]Carlo D'Eramo, Andrea Cini, Alessandro Nuara, Matteo Pirotta, Cesare Alippi, Jan Peters, Marcello Restelli:
Gaussian Approximation for Bias Reduction in Q-Learning. J. Mach. Learn. Res. 22: 277:1-277:51 (2021) - [j16]Amarildo Likmeta, Alberto Maria Metelli, Giorgia Ramponi, Andrea Tirinzoni, Matteo Giuliani, Marcello Restelli:
Dealing with multiple experts and non-stationarity in inverse reinforcement learning: an application to real-life problems. Mach. Learn. 110(9): 2541-2576 (2021) - [c111]Alberto Maria Metelli, Matteo Papini, Pierluca D'Oro, Marcello Restelli:
Policy Optimization as Online Learning with Mediator Feedback. AAAI 2021: 8958-8966 - [c110]Mirco Mutti, Lorenzo Pratissoli, Marcello Restelli:
Task-Agnostic Exploration via Policy Gradient of a Non-Parametric State Entropy Estimate. AAAI 2021: 9028-9036 - [c109]Giorgia Ramponi, Marcello Restelli:
Newton Optimization on Helmholtz Decomposition for Continuous Games. AAAI 2021: 11325-11333 - [c108]Edoardo Vittori, Amarildo Likmeta, Marcello Restelli:
Monte carlo tree search for trading and hedging. ICAIF 2021: 37:1-37:9 - [c107]Antonio Riva, Lorenzo Bisi, Pierre Liotet, Luca Sabbioni, Edoardo Vittori, Marco Pinciroli, Michele Trapletti, Marcello Restelli:
Learning FX trading strategies with FQI and persistent actions. ICAIF 2021: 38:1-38:9 - [c106]Alberto Maria Metelli, Giorgia Ramponi, Alessandro Concetti, Marcello Restelli:
Provably Efficient Learning of Transferable Rewards. ICML 2021: 7665-7676 - [c105]Matteo Papini, Andrea Tirinzoni, Marcello Restelli, Alessandro Lazaric, Matteo Pirotta:
Leveraging Good Representations in Linear Contextual Bandits. ICML 2021: 8371-8380 - [c104]Riccardo Poiani, Andrea Tirinzoni, Marcello Restelli:
Meta-Reinforcement Learning by Tracking Task Non-stationarity. IJCAI 2021: 2899-2905 - [c103]Pierre Liotet, Erick Venneri, Marcello Restelli:
Learning a Belief Representation for Delayed Reinforcement Learning. IJCNN 2021: 1-8 - [c102]Alberto Maria Metelli, Alessio Russo, Marcello Restelli:
Subgaussian and Differentiable Importance Sampling for Off-Policy Evaluation and Learning. NeurIPS 2021: 8119-8132 - [c101]Matteo Papini, Andrea Tirinzoni, Aldo Pacchiano, Marcello Restelli, Alessandro Lazaric, Matteo Pirotta:
Reinforcement Learning in Linear MDPs: Constant Regret and Representation Selection. NeurIPS 2021: 16371-16383 - [c100]Giorgia Ramponi, Alberto Maria Metelli, Alessandro Concetti, Marcello Restelli:
Learning in Non-Cooperative Configurable Markov Decision Processes. NeurIPS 2021: 22808-22821 - [c99]Martino Bernasconi de Luca, Edoardo Vittori, Francesco Trovò, Marcello Restelli:
Conservative Online Convex Optimization. ECML/PKDD (1) 2021: 19-34 - [c98]Gerlando Re, Fabio Chiusano, Francesco Trovò, Diego Carrera, Giacomo Boracchi, Marcello Restelli:
Exploiting History Data for Nonstationary Multi-armed Bandit. ECML/PKDD (1) 2021: 51-66 - [c97]Giuseppe Canonaco, Andrea Soprani, Matteo Giuliani, Andrea Castelletti, Manuel Roveri, Marcello Restelli:
Time-variant variational transfer for value functions. UAI 2021: 876-886 - [i33]Conor F. Hayes, Roxana Radulescu, Eugenio Bargiacchi, Johan Källström, Matthew Macfarlane, Mathieu Reymond, Timothy Verstraeten, Luisa M. Zintgraf, Richard Dazeley, Fredrik Heintz, Enda Howley, Athirai A. Irissappane, Patrick Mannion, Ann Nowé, Gabriel de Oliveira Ramos, Marcello Restelli, Peter Vamplew, Diederik M. Roijers:
A Practical Guide to Multi-Objective Reinforcement Learning and Planning. CoRR abs/2103.09568 (2021) - [i32]Matteo Papini, Andrea Tirinzoni, Marcello Restelli, Alessandro Lazaric, Matteo Pirotta:
Leveraging Good Representations in Linear Contextual Bandits. CoRR abs/2104.03781 (2021) - [i31]Riccardo Poiani, Andrea Tirinzoni, Marcello Restelli:
Meta-Reinforcement Learning by Tracking Task Non-stationarity. CoRR abs/2105.08834 (2021) - [i30]Matteo Papini, Andrea Tirinzoni, Aldo Pacchiano, Marcello Restelli, Alessandro Lazaric, Matteo Pirotta:
Reinforcement Learning in Linear MDPs: Constant Regret and Representation Selection. CoRR abs/2110.14798 (2021) - [i29]Pierre Liotet, Francesco Vidaich, Alberto Maria Metelli, Marcello Restelli:
Lifelong Hyper-Policy Optimization with Multiple Importance Sampling Regularization. CoRR abs/2112.06625 (2021) - [i28]Mirco Mutti, Mattia Mancassola, Marcello Restelli:
Unsupervised Reinforcement Learning in Multiple Environments. CoRR abs/2112.08746 (2021) - 2020
- [j15]Alberto Maria Metelli, Matteo Pirotta, Marcello Restelli:
On the use of the policy gradient and Hessian in inverse reinforcement learning. Intelligenza Artificiale 14(1): 117-150 (2020) - [j14]Francesco Trovò, Marcello Restelli, Nicola Gatti:
Sliding-Window Thompson Sampling for Non-Stationary Settings. J. Artif. Intell. Res. 68: 311-364 (2020) - [j13]Alberto Maria Metelli, Matteo Papini, Nico Montali, Marcello Restelli:
Importance Sampling Techniques for Policy Optimization. J. Mach. Learn. Res. 21: 141:1-141:75 (2020) - [j12]Amarildo Likmeta, Alberto Maria Metelli, Andrea Tirinzoni, Riccardo Giol, Marcello Restelli, Danilo Romano:
Combining reinforcement learning with rule-based controllers for transparent and general decision-making in autonomous driving. Robotics Auton. Syst. 131: 103568 (2020) - [c96]Pierluca D'Oro, Alberto Maria Metelli, Andrea Tirinzoni, Matteo Papini, Marcello Restelli:
Gradient-Aware Model-Based Policy Search. AAAI 2020: 3801-3808 - [c95]Mirco Mutti, Marcello Restelli:
An Intrinsically-Motivated Approach for Learning Highly Exploring and Fast Mixing Policies. AAAI 2020: 5232-5239 - [c94]Matteo Papini, Andrea Battistello, Marcello Restelli:
Balancing Learning Speed and Stability in Policy Gradient via Adaptive Exploration. AISTATS 2020: 1188-1199 - [c93]Giorgia Ramponi, Amarildo Likmeta, Alberto Maria Metelli, Andrea Tirinzoni, Marcello Restelli:
Truly Batch Model-Free Inverse Reinforcement Learning about Multiple Intentions. AISTATS 2020: 2359-2369 - [c92]Andrea Tirinzoni, Alessandro Lazaric, Marcello Restelli:
A Novel Confidence-Based Algorithm for Structured Bandits. AISTATS 2020: 3175-3185 - [c91]Alessandro Nuara, Francesco Trovò, Dominic Crippa, Nicola Gatti, Marcello Restelli:
Driving Exploration by Maximum Distribution in Gaussian Process Bandits. AAMAS 2020: 948-956 - [c90]Giuseppe Canonaco, Marcello Restelli, Manuel Roveri:
Model-Free Non-Stationarity Detection and Adaptation in Reinforcement Learning. ECAI 2020: 1047-1054 - [c89]Luca Sabbioni, Marcello Restelli, Andrea Prampolini:
Fast direct calibration of interest rate derivatives pricing models. ICAIF 2020: 6:1-6:8 - [c88]Edoardo Vittori, Martino Bernasconi de Luca, Francesco Trovò, Marcello Restelli:
Dealing with transaction costs in portfolio optimization: online gradient descent with momentum. ICAIF 2020: 11:1-11:8 - [c87]Lorenzo Bisi, Pierre Liotet, Luca Sabbioni, Gianmarco Reho, Nico Montali, Marcello Restelli, Cristiana Corno:
Foreign exchange trading: a risk-averse batch reinforcement learning approach. ICAIF 2020: 26:1-26:8 - [c86]Edoardo Vittori, Michele Trapletti, Marcello Restelli:
Option hedging with risk averse reinforcement learning. ICAIF 2020: 27:1-27:8 - [c85]Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters:
Sharing Knowledge in Multi-Task Deep Reinforcement Learning. ICLR 2020 - [c84]Alberto Maria Metelli, Flavio Mazzolini, Lorenzo Bisi, Luca Sabbioni, Marcello Restelli:
Control Frequency Adaptation via Action Persistence in Batch Reinforcement Learning. ICML 2020: 6862-6873 - [c83]Andrea Tirinzoni, Riccardo Poiani, Marcello Restelli:
Sequential Transfer in Reinforcement Learning with a Generative Model. ICML 2020: 9481-9492 - [c82]Andrea Schillaci, Maurizio Quadrio, Carlotta Pipolo, Marcello Restelli, Giacomo Boracchi:
Inferring Functional Properties from Fluid Dynamics Features. ICPR 2020: 4091-4098 - [c81]