Worst-Case Regret Bounds for Combinatorial Bandits with Ranking Feedback
Advances in Neural Information Processing Systems (NeurIPS) · 2026
Publications
Scientific productivity
102Publications
75Conference papers
27Journal articles
54Papers in A* conferences · CORE/ICORE
16Articles in Q1 journals · SCImago
Selected conferences: ICML (25) · NeurIPS (16) · AISTATS (9) · AAAI (7) · COLT (3) · ICLR (2) · CoRL (1) · IJCAI (1) · RSS (1) · UAI (1)
Selected journals: JMLR (4)
Browse papers
How to read the author list: Unless explicitly marked otherwise, the first author is the main contributor. An asterisk (*) identifies authors who contributed equally; α–β order means authors are listed alphabetically.
Venue information: CORE/ICORE and SCImago SJR scores and quartiles show an applicable rating edition at the publication year, not today’s ranking. Missing values are not estimated.
International conferences
75 records2026
Why Does Action Chunking Improve Behavioral Cloning Performance in Robotic Control?
Conference on Robot Learning (CoRL) · 2026
Mind Your Steps: A General Learning Framework for Accurate Humanoid Foothold Tracking
Robotics: Science and Systems (RSS) · 2026
Fast Mixing Steady-State Control in Markov Decision Processes
International Conference on Machine Learning (ICML) · 2026
Learning to Rank from Incomplete Rankings
International Conference on Machine Learning (ICML) · 2026
Online Compatible Reward Identification from Preference Feedback
International Conference on Machine Learning (ICML) · 2026
Reusing Trajectories in Policy Gradients Enables Fast Convergence
International Conference on Machine Learning (ICML) · 2026
Catoni-Style Change Point Detection for Regret Minimization in Piecewise-Stationary Heavy-Tailed Bandits
International Conference on Artificial Intelligence and Statistics (AISTATS) · 2026
Generalizing Behavior via Inverse Reinforcement Learning with Closed-Form Reward Centroids
International Conference on Artificial Intelligence and Statistics (AISTATS) · 2026
Imitation Learning as Return Distribution Matching
International Conference on Learning Representations (ICLR) · 2026
Robustness in the Face of Partial Identifiability in Reward Learning
International Conference on Learning Representations (ICLR) · 2026
Thompson Sampling-like Algorithms for Stochastic Rising Bandits
International Conference on Artificial Intelligence and Statistics (AISTATS) · 2026
2025
Spectral Learning for Infinite-Horizon Average-Reward POMDPs
Advances in Neural Information Processing Systems (NeurIPS) · 2025
Tightening Regret Lower and Upper Bounds in Restless Rising Bandits
Advances in Neural Information Processing Systems (NeurIPS) · 2025
Convergence Analysis of Policy Gradient Methods with Dynamic Stochasticity
International Conference on Machine Learning (ICML) · 2025
Learning Utilities from Demonstrations in Markov Decision Processes
International Conference on Machine Learning (ICML) · 2025
Position: Constants are Critical in Regret Bounds for Reinforcement Learning
International Conference on Machine Learning (ICML) - Position Papers Track · 2025
Sleeping Reinforcement Learning
International Conference on Machine Learning (ICML) · 2025
Towards Theoretical Understanding of Sequential Decision Making with Preference Feedback
International Conference on Machine Learning (ICML) · 2025
Open Problem: Regret Minimization in Heavy-Tailed Bandits with Unknown Distributional Parameters
Conference on Learning Theory (COLT) - Open Problems Track · 2025
Achieving 𝒪(√T) Regret in Average-Reward POMDPs with Known Observation Models
International Conference on Artificial Intelligence and Statistics (AISTATS) · 2025
Efficient Exploitation of Hierarchical Structure in Sparse Reward Reinforcement Learning
International Conference on Artificial Intelligence and Statistics (AISTATS) · 2025
2024
How does Inverse RL Scale to Large State Spaces? A Provably Efficient Approach
Advances in Neural Information Processing Systems (NeurIPS) · 2024
Last-Iterate Global Convergence of Policy Gradients for Constrained Reinforcement Learning
Advances in Neural Information Processing Systems (NeurIPS) · 2024
Local Linearity: the Key for No-regret Reinforcement Learning in Continuous MDPs
Advances in Neural Information Processing Systems (NeurIPS) · 2024
Optimal Multi-Fidelity Best-Arm Identification
Advances in Neural Information Processing Systems (NeurIPS) · 2024
Sub-optimal Experts mitigate Ambiguity in Inverse Reinforcement Learning
Advances in Neural Information Processing Systems (NeurIPS) · 2024
Interpetable Target-Feature Aggregation for Multi-Task Learning based on Bias-Variance Analysis
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) · 2024
A Provably Efficient Option-Based Algorithm for both High-Level and Low-Level Learning
Reinforcement Learning Conference (RLC) · 2024
Online Learning with Off-Policy Feedback in Adversarial MDPs
International Joint Conference on Artificial Intelligence (IJCAI) · 2024
Policy Gradient with Active Importance Sampling
Reinforcement Learning Conference (RLC) · 2024
Best Arm Identification for Stochastic Rising Bandits
International Conference on Machine Learning (ICML) · 2024
Causal Feature Selection via Transfer Entropy
IEEE World Congress on Computational Intelligence - International Joint Conference on Neural Networks (IJCNN) · 2024
Factored-Reward Bandits with Intermediate Observations
International Conference on Machine Learning (ICML) · 2024
Graph-Triggered Rising Bandits
International Conference on Machine Learning (ICML) · 2024
Learning Optimal Deterministic Policies with Stochastic Policy Gradients
International Conference on Machine Learning (ICML) · 2024
No-Regret Reinforcement Learning in Smooth MDPs
International Conference on Machine Learning (ICML) · 2024
Offline Inverse RL: New Solution Concepts and Provably Efficient Algorithms
International Conference on Machine Learning (ICML) · 2024
The Power of Hybrid Learning in Industrial Robotics: Efficient Grasping Strategies with Supervised-Driven Reinforcement Learning
IEEE World Congress on Computational Intelligence - International Joint Conference on Neural Networks (IJCNN) · 2024
Projection by Convolution: Optimal Sample Complexity for RL in Continuous-Space MDPs
Annual Conference on Learning Theory (COLT) · 2024
Transfer Learning for Dynamical Systems Models via Autoencoders and GANs
American Control Conference (ACC) · 2024
(ε, u)-Adaptive Regret Minimization in Heavy-Tailed Bandits
Annual Conference on Learning Theory (COLT) · 2024
Autoregressive Bandits
International Conference on Artificial Intelligence and Statistics (AISTATS) · 2024
Dissimilarity Bandits
International Conference on Artificial Intelligence and Statistics (AISTATS) · 2024
Parameterized Projected Bellman Operator
AAAI Conference on Artificial Intelligence (AAAI) · 2024
2023
Distributional Policy Evaluation: a Maximum Entropy approach to Representation Learning
Advances in Neural Information Processing Systems (NeurIPS) · 2023
Truncating Trajectories in Monte Carlo Policy Evaluation: an Adaptive Approach
Advances in Neural Information Processing Systems (NeurIPS) · 2023
On the Relation between Policy Improvement and Off-Policy Minimum-Variance Policy Evaluation
Conference on Uncertainty in Artificial Intelligence (UAI) · 2023
Dynamical Linear Bandits
International Conference on Machine Learning (ICML) · 2023
Towards Theoretical Understanding of Inverse Reinforcement Learning
International Conference on Machine Learning (ICML) · 2023
Truncating Trajectories in Monte Carlo Reinforcement Learning
International Conference on Machine Learning (ICML) · 2023
A Tale of Sampling and Estimation in Discounted Reinforcement Learning
International Conference on Artificial Intelligence and Statistics (AISTATS) · 2023
Simultaneously Updating All Persistence Values in Reinforcement Learning
AAAI Conference on Artificial Intelligence (AAAI) · 2023
Tight Performance Guarantees of Imitator Policies with Continuous Actions
AAAI Conference on Artificial Intelligence (AAAI) · 2023
Wasserstein Actor-Critic: Directed Exploration via Optimism for Continuous-Actions Control
AAAI Conference on Artificial Intelligence (AAAI) · 2023
Information-Theoretic Regret Bounds for Bandits with Fixed Expert Advice
IEEE Information Theory Workshop (ITW) · 2023
2022
Multi-Fidelity Best-Arm Identification
Advances in Neural Information Processing Systems (NeurIPS) · 2022
Balancing Sample Efficiency and Suboptimality in Inverse Reinforcement Learning
International Conference on Machine Learning (ICML) · 2022
Stochastic Rising Bandits
International Conference on Machine Learning (ICML) · 2022
Storehouse: a Reinforcement Learning Environment for Optimizing Warehouse Management
IEEE World Congress on Computational Intelligence - International Joint Conference on Neural Networks (IJCNN) · 2022
Lifelong Hyper-Policy Optimization with Multiple Importance Sampling Regularization
AAAI Conference on Artificial Intelligence (AAAI) · 2022
2021
Learning in Non-Cooperative Configurable Markov Decision Processes
Advances in Neural Information Processing Systems (NeurIPS) · 2021
Subgaussian and Differentiable Importance Sampling for Off-Policy Evaluation and Learning
Advances in Neural Information Processing Systems (NeurIPS) · 2021
Provably Efficient Learning of Transferable Rewards
International Conference on Machine Learning (ICML) · 2021
Policy Optimization as Online Learning with Mediator Feedback
AAAI Conference on Artificial Intelligence (AAAI) · 2021
2020
Control Frequency Adaptation via Action Persistence in Batch Reinforcement Learning
International Conference on Machine Learning (ICML) · 2020
Truly Batch Model-Free Inverse Reinforcement Learning about Multiple Intentions
International Conference on Artificial Intelligence and Statistics (AISTATS) · 2020
Gradient-Aware Model-Based Policy Search
AAAI Conference on Artificial Intelligence (AAAI) · 2020
2019
Propagating Uncertainty in Reinforcement Learning via Wasserstein Barycenters
Advances in Neural Information Processing Systems (NeurIPS) · 2019
Feature Selection via Mutual Information: New Theoretical Insights
International Joint Conference on Neural Networks (IJCNN) · 2019
Optimistic Policy Optimization via Multiple Importance Sampling
International Conference on Machine Learning (ICML) · 2019
Reinforcement Learning in Configurable Continuous Environments
International Conference on Machine Learning (ICML) · 2019
2018
Policy Optimization via Importance Sampling
Advances in Neural Information Processing Systems (NeurIPS) · 2018
Configurable Markov Decision Processes
International Conference on Machine Learning (ICML) · 2018
2017
Compatible Reward Inverse Reinforcement Learning
Advances in Neural Information Processing Systems (NIPS) · 2017
Journal articles
27 records2026
A Hierarchical Reinforcement Learning and Predictive Control Framework for Automated Multi-Variable Anesthesia
Computers in Biology and Medicine (CBM) · 2026
Bridging Rested and Restless Bandits with Graph-Triggering: Rising and Rotting
Journal of Machine Learning Research (JMLR) · 2026
Feature aggregation in nonlinear systems: two interpretable supervised algorithms
Data Mining and Knowledge Discovery (DMKD) · 2026
Impact-Based Drought Detection via Interpretable Machine Learning and Causal Discovery
Journal of Geophysical Research: Machine Learning and Computation (JGR: MLC) · 2026
Rising Rested Bandits: Lower Bounds and Efficient Algorithms
Artificial Intelligence (AIJ) · 2026
Trading-Off Statistical and Computational Efficiency via W-Step Markov Decision Processes: A Policy Gradient Approach
Machine Learning (MLJ) · 2026
Article 174
2025
AReS: A patient simulator to facilitate testing of automated anesthesia
Computer Methods and Programs in Biomedicine (CMPB) · 2025
Factored-Reward Bandits with Intermediate Observations: Regret Minimization and Best Arm Identification
Artificial Intelligence (AIJ) · 2025
Generalizing the Regret: an Analysis of Lower and Upper Bounds
Journal of Artificial Intelligence Research (JAIR) · 2025
Human-AI interaction in safety-critical network infrastructures
iScience · 2025
Minimax off-policy evaluation and learning with subgaussian and differentiable importance weighting
Artificial Intelligence (AIJ) · 2025
Search or split: policy gradient with adaptive policy space
Machine Learning (MLJ) · 2025
2024
Information Capacity Regret Bounds for Bandits with Mediator Feedback
Journal of Machine Learning Research (JMLR) · 2024
Interpretable linear dimensionality reduction based on bias-variance analysis
Data Mining and Knowledge Discovery (DMKD) · 2024
Optimizing Empty Container Repositioning and Fleet Deployment via Configurable Semi-POMDPs
IEEE Transactions on Intelligent Transportation Systems (T-ITS) · 2024
Sample Complexity of Variance-Reduced Policy Gradient: Weaker Assumptions and Lower Bounds
Machine Learning (MLJ) · 2024
Switching Latent Bandits
Transactions on Machine Learning Research (TMLR) · 2024
2023
An Option-Dependent Analysis of Regret Minimization Algorithms in Finite-Horizon Semi-MDP
Transactions on Machine Learning Research (TMLR) · 2023
ARLO: A framework for Automated Reinforcement Learning
Expert Systems with Applications (ESWA) · 2023
IWDA: Importance Weighting for Drift Adaptation in Streaming Supervised Learning Problems
IEEE Transactions on Neural Networks and Learning Systems (TNNLS) · 2023
2022
A Unified View of Configurable Markov Decision Processes: Solution Concepts, Value Functions, and Operators
Intelligenza Artificiale (IA) · 2022
Invited publication as winner of the Premio Neodottori di Ricerca Marco Cadoli 2021
Policy space identification in configurable environments
Machine Learning (MLJ) · 2022
2021
Dealing with multiple experts and non-stationarity in inverse reinforcement learning: an application to real-life problems
Machine Learning (MLJ) · 2021
Safe Policy Iteration: A Monotonically Improving Approximate Policy Iteration Approach
Journal of Machine Learning Research (JMLR) · 2021
2020
Combining reinforcement learning with rule-based controllers for transparent and general decision-making in autonomous driving
Robotics and Autonomous Systems (RAS) · 2020
Importance Sampling Techniques for Policy Optimization
Journal of Machine Learning Research (JMLR) · 2020
On the use of the policy gradient and Hessian in inverse reinforcement learning
Intelligenza Artificiale (IA) · 2020
Invited publication as winner of the Premio NeoLaureati Leonardo Lesmo 2018
Workshop papers
36 records2026
Combinatorial Bandits with Plackett-Luce Feedback: A Worst-Case Analysis
European Workshop on Reinforcement Learning (EWRL) · 2026
Variance-Aware Optimal Ranking in Log-Concave Random Utility Models
European Workshop on Reinforcement Learning (EWRL) · 2026
Modeling Incomparability: A New Rationality Paradigm for Preference-Based Reinforcement Learning
Workshop on Epistemic Intelligence in Machine Learning at ICML · 2026
Robust Learning to Rank from Incomplete Rankings under Positional Censoring
Workshop on Epistemic Intelligence in Machine Learning at ICML · 2026
Addressing Stochastic Rising Bandits with Thompson Sampling
OPTIMAL: Optimisation and Post-Bayesian Inference in Machine Learning @ AISTATS 2026 · 2026
Closed-Form Reward Centroids for Inverse Reinforcement Learning
OPTIMAL: Optimisation and Post-Bayesian Inference in Machine Learning @ AISTATS 2026 · 2026
Reformulating Imitation Learning as Return Distribution Matching
The 2nd Workshop on Advances in Financial AI Workshop: Towards Agentic and Responsible Systems at ICLR · 2026
Robustness in the Face of Partial Identifiability in Reward Learning Problems
ICLR 2026 the 2nd Workshop on World Models: Understanding, Modelling and Scaling · 2026
2025
A Novel Self-Normalized Bernstein-Like Dimension-Free Inequality and Regret Bounds for Generalized Kernelized Bandits
European Workshop on Reinforcement Learning (EWRL) · 2025
A Theoretical Perspective on Sequential Decision Making with Preference Feedback
European Workshop on Reinforcement Learning (EWRL) · 2025
Gym4ReaL: A Benchmark Suite for Evaluating Reinforcement Learning in Realistic Domains
European Workshop on Reinforcement Learning (EWRL) · 2025
Trading-off Reward Maximization and Stability in Sequential Decision Making
European Workshop on Reinforcement Learning (EWRL) · 2025
Power Grid Control with Graph-Based Distributed Reinforcement Learning
ECML-PKDD 2025, Machine Learning for Sustainable Power Systems workshop · 2025
2024
Policy Gradient Methods with Adaptive Policy Spaces
Seventeenth European Workshop on Reinforcement Learning (EWRL 17) · 2024
The challenge of continuous MDPs: is no-regret learning feasible?
Seventeenth European Workshop on Reinforcement Learning (EWRL 17) · 2024
Thompson Sampling-like Algorithms for Stochastic Rising Rested Bandits
Seventeenth European Workshop on Reinforcement Learning (EWRL 17) · 2024
State and Action Factorization in Power Grids
ECML-PKDD 2024, Machine Learning for Sustainable Power Systems workshop · 2024
Interpretable Machine Learning for Extreme Events detection: An application to droughts in the Po River Basin
Tackling Climate Change with Machine Learning: Fostering the Maturity of ML Applications for Climate Change @ ICLR 2024 · 2024
Intermediate Observations in Factored-Reward Bandits
Adaptive and Learning Agents (ALA) Workshop @ AAMAS 2024 · 2024
2023
Pure Exploration under Mediators’ Feedback
NeurIPS 2023 Workshop on Adaptive Experimental Design and Active Learning in the Real World · 2023
Towards Fully Adaptive Regret Minimization in Heavy-Tailed Bandits
NeurIPS 2023 Workshop Heavy Tails in Machine Learning · 2023
Online Learning in Autoregressive Dynamics
Sixteenth European Workshop on Reinforcement Learning · 2023
On the Sample Complexity of Inverse Reinforcement Learning
Sixteenth European Workshop on Reinforcement Learning · 2023
Stochastic Rising Bandits: A Best Arm Identification Approach
Sixteenth European Workshop on Reinforcement Learning · 2023
A Best Arm Identification Approach for Stochastic Rising Bandits
ICML Workshop on New Frontiers in Learning, Control, and Dynamical Systems · 2023
2022
Trust Region Meta Learning for Policy Optimization
ECMLPKDD Workshop on Meta-Knowledge Transfer · 2022
Directed Exploration via Uncertainty-Aware Critics
Decision Awareness in Reinforcement Learning Workshop @ ICML 2022 · 2022
Dynamical Linear Bandits for Long-Lasting Vanishing Rewards
Complex Feedback in Online Learning Workshop @ ICML 2022 · 2022
Stochastic Rising Bandits for Online Model Selection
Complex Feedback in Online Learning Workshop @ ICML 2022 · 2022
2021
Policy Optimization via Optimal Policy Evaluation
Deep Reinforcement Learning Workshop - NeurIPS 2021 · 2021
Efficient Inverse Reinforcement Learning of Transferable Rewards
ICML-21 Workshop on Reinforcement Learning Theory · 2021
Subgaussian Importance Sampling for Off-Policy Evaluation and Learning
ICML-21 Workshop on Reinforcement Learning Theory · 2021
Online Learning in Non-Cooperative Configurable Markov Decision Process
AAAI-21 Workshop on Reinforcement Learning in Games · 2021
2020
Handling Non-Stationary Experts in Inverse Reinforcement Learning: A Water System Control Case Study
Challenges of Real-World RL Workshop @ NeurIPS 2020 · 2020
Autonomous Driving with Reinforcement Learning and Rule-based Policies
Workshop on AI for Autonomous Driving (AIAD) @ICML 2020 · 2020
2017
Content-Based Approaches for Cold-Start Job Recommendations
Proceedings of the Recommender Systems Challenge 2017 · 2017
Abstracts
9 records2025
A Reinforcement Learning Approach for Personalized Automated Anesthesia Control
Women in Machine Learning Workshop @ NeurIPS 2025 · 2025
How to Give Health-Behavioural Recommendations Using Meta-Reinforcement Learning to Reduce Cancer Risk
Women in Machine Learning Workshop @ NeurIPS 2025 · 2025
2024
Recent Advancements in Inverse Reinforcement Learning
AAAI Conference on Artificial Intelligence (AAAI) - Special Track AI for New Faculty Highlights · 2024
Machine Learning-Driven Enhancement of Predictors and Prediction for Tropical Cyclone Activity
36th Conference on Hurricanes and Tropical Meteorology · 2024
2022
Advancing drought monitoring via feature extraction and multi-task learning algorithms
EGU General Assembly 2022 · 2022
All-persistence Bellman Update for Reinforcement Learning
The Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM) · 2022
A Novel Inverse Reinforcement Learning Formulation for Sample-Aware Forward Learning
The Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM) · 2022
Seasonal forecasts for hydropower: downscaling of precipitation in South American basins
EGU General Assembly 2022 · 2022
2021
Advancing drought monitoring via feature extraction
Earth and Space Science Open Archive · 2021
Technical reports
2 records2025
A Regret Lower Bound for u-Adaptive Heavy-Tailed Bandits
Politecnico di Milano · 2025
2024
Position paper on AI for the operation of critical energy and mobility network infrastructures
AI4REALNET · 2024
Books
2 records2024
The machine learning gym. Train and test your skills
McGraw-Hill Education · 2024
2022
Exploiting environment configurability in reinforcement learning
IOS Press · 2022
Book chapters
1 records2022
Configurable Environments in Reinforcement Learning: An Overview
Special Topics in Information Technology · 2022
Theses
2 records2021
Exploiting Environment Configurability in Reinforcement Learning
Politecnico di Milano · 2021
2017
Compatible Reward Inverse Reinforcement Learning
Politecnico di Milano · 2017
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