On Groups which contain no HNN-Extensions. - Derek J. S. Robinson; Alessio Russo; Giovanni Vincenzi (Int. J. Algebra Comput., 2007)

Optimal Attacks on Reinforcement Learning Policies. - Alessio Russo; Alexandre Proutière (CoRR, 2019)

Optimal Algorithms for Multiplayer Multi-Armed Bandits. - Po-An Wang; Alexandre Proutière; Kaito Ariu; Yassir Jedra; Alessio Russo (AISTATS, 2020)

Poisoning Attacks against Data-Driven Control Methods. - Alessio Russo; Alexandre Proutière (ACC, 2021)

Towards Optimal Attacks on Reinforcement Learning Policies. - Alessio Russo; Alexandre Proutière (ACC, 2021)

Minimizing Information Leakage of Abrupt Changes in Stochastic Systems. - Alessio Russo; Alexandre Proutière (CDC, 2021)

Data-Driven Control and Data-Poisoning attacks in Buildings: the KTH Live-In Lab case study. - Alessio Russo; Marco Molinari 001; Alexandre Proutière (MED, 2021)

Subgaussian and Differentiable Importance Sampling for Off-Policy Evaluation and Learning. - Alberto Maria Metelli; Alessio Russo; Marcello Restelli (NeurIPS, 2021)

Some Ethical Issues in the Review Process of Machine Learning Conferences. - Alessio Russo (CoRR, 2021)

Balancing detectability and performance of attacks on the control channel of Markov Decision Processes. - Alessio Russo; Alexandre Proutière (ACC, 2022)

Model Based Residual Policy Learning with Applications to Antenna Control. - Viktor Eriksson Möllerstedt; Alessio Russo; Maxime Bouton (CoRR, 2022)

Analysis and Detectability of Offline Data Poisoning Attacks on Linear Systems. - Alessio Russo; Alexandre Proutière (CoRR, 2022)

On the Sample Complexity of Representation Learning in Multi-Task Bandits with Global and Local Structure. - Alessio Russo; Alexandre Proutière (AAAI, 2023)

Tube-Based Zonotopic Data-Driven Predictive Control. - Alessio Russo; Alexandre Proutière (ACC, 2023)

Self-Tuning Tube-based Model Predictive Control. - Damianos Tranos; Alessio Russo; Alexandre Proutière (ACC, 2023)

What influences occupants' behavior in residential buildings: An experimental study on window operation in the KTH Live-In Lab. - Mahsa Farjadnia; Angela Fontan; Alessio Russo; Karl Henrik Johansson; Marco Molinari 001 (CCTA, 2023)

Conformal Off-Policy Evaluation in Markov Decision Processes. - Daniele Foffano; Alessio Russo; Alexandre Proutière (CDC, 2023)

Visual Design Checklist for Glucose Monitor App User Interface Usability Evaluation. - Chan Juan Tu; Alessio Russo (HCI (24), 2023)

Analysis and Detectability of Offline Data Poisoning Attacks on Linear Dynamical Systems. - Alessio Russo (L4DC, 2023)

Model-Free Active Exploration in Reinforcement Learning. - Alessio Russo; Alexandre Proutière (NeurIPS, 2023)

Constrained Deep Reinforcement Learning for Fronthaul Compression Optimization. - Axel Grönland; Alessio Russo; Yassir Jedra; Bleron Klaiqi; Xavier Gelabert (CoRR, 2023)

Morphological analysis of historical landscapes based on cultural DNA approach. - Parichehr Goodarzi; Mojtaba Ansari; Mohammadjavad Mahdavinejad; Alessio Russo; Mahdi Haghighatbin; Farzad Pour Rahimian (Digit. Appl. Archaeol. Cult. Heritage, 2023)

Fair Best Arm Identification with Fixed Confidence. - Alessio Russo; Filippo Vannella (CDC, 2024)

Multi-Reward Best Policy Identification. - Alessio Russo; Filippo Vannella (NeurIPS, 2024)

Efficient Learning of POMDPs with Known Observation Model in Average-Reward Setting. - Alessio Russo; Alberto Maria Metelli; Marcello Restelli (CoRR, 2024)

Offline Reinforcement Learning and Sequence Modeling for Downlink Link Adaptation. - Samuele Peri; Alessio Russo; Gábor Fodor 001; Pablo Soldati (CoRR, 2024)

Switching Latent Bandits. - Alessio Russo; Alberto Maria Metelli; Marcello Restelli (Trans. Mach. Learn. Res., 2024)

Achieving $ widetilde{ mathcal{O}}( sqrt{T})$ Regret in Average-Reward POMDPs with Known Observation Models. - Alessio Russo; Alberto Maria Metelli; Marcello Restelli (AISTATS, 2025)

Pure Exploration with Feedback Graphs. - Alessio Russo; Yichen Song; Aldo Pacchiano (AISTATS, 2025)

Answer Set Programming for Feature-Based Explanation of Malware Prediction. - Alessio Russo; Eleonora Iotti; Alessandro Dal Palù (CILC, 2025)

Explainable Reinforcement Learning via Temporal Policy Decomposition. - Franco Ruggeri; Alessio Russo; Rafia Inam; Karl Henrik Johansson (CoRR, 2025)

Achieving O(√T) Regret in Average-Reward POMDPs with Known Observation Models. - Alessio Russo; Alberto Maria Metelli; Marcello Restelli (CoRR, 2025)

Adaptive Exploration for Multi-Reward Multi-Policy Evaluation. - Alessio Russo; Aldo Pacchiano (CoRR, 2025)

Learning to Explore: An In-Context Learning Approach for Pure Exploration. - Alessio Russo; Ryan Welch; Aldo Pacchiano (CoRR, 2025)

Gym4ReaL: A Suite for Benchmarking Real-World Reinforcement Learning. - Davide Salaorni; Vincenzo De Paola; Samuele Delpero; Giovanni Dispoto; Paolo Bonetti; Alessio Russo; Giuseppe Calcagno; Francesco Trovò; Matteo Papini; Alberto Maria Metelli; Marco Mussi; Marcello Restelli (CoRR, 2025)