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Le informazioni sulla didattica, sulla ricerca e sui compiti istituzionali riportate in questa pagina sono certificate dall'Ateneo; ulteriori informazioni, redatte a cura del docente, sono disponibili sulla pagina web personale e nel curriculum vitae indicati nella scheda.
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Informazioni sul docente
DocenteRestelli Marcello
QualificaProfessore associato a tempo pieno
Dipartimento d'afferenzaDipartimento di Elettronica, Informazione e Bioingegneria
Settore Scientifico DisciplinareING-INF/05 - Sistemi Di Elaborazione Delle Informazioni
Curriculum VitaeScarica il CV (518.02Kb - 01/09/2022)
OrcIDhttps://orcid.org/0000-0002-6322-1076

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E-mailmarcello.restelli@polimi.it
Pagina web redatta a cura del docentehttp://home.deib.polimi.it/restelli/

Fonte dati: RE.PUBLIC@POLIMI - Research Publications at Politecnico di Milano

Elenco delle pubblicazioni e dei prodotti della ricerca per l'anno 2023 (Mostra tutto | Nascondi tutto)
Tipologia Titolo Pubblicazione/Prodotto
Contributo in Atti di convegno
A Provably Efficient Option-Based Algorithm for both High-Level and Low-Level Learning (Mostra >>)
A Tale of Sampling and Estimation in Discounted Reinforcement Learning (Mostra >>)
Dynamic Pricing with Volume Discounts in Online Settings (Mostra >>)
Dynamical Linear Bandits (Mostra >>)
Information-Theoretic Regret Bounds for Bandits with Fixed Expert Advice (Mostra >>)
On the Relation between Policy Improvement and Off-Policy Minimum-Variance Policy Evaluation (Mostra >>)
Simultaneously Updating All Persistence Values in Reinforcement Learning (Mostra >>)
Switching Latent Bandits (Mostra >>)
Tight Performance Guarantees of Imitator Policies with Continuous Actions (Mostra >>)
Towards Theoretical Understanding of Inverse Reinforcement Learning (Mostra >>)
Truncating Trajectories in Monte Carlo Reinforcement Learning (Mostra >>)
Wasserstein Actor-Critic: Directed Exploration via Optimism for Continuous-Actions Control (Mostra >>)
Articoli su riviste
ARLO: A framework for Automated Reinforcement Learning (Mostra >>)
An Option-Dependent Analysis of Regret Minimization Algorithms in Finite-Horizon Semi-MDP (Mostra >>)
IWDA: Importance Weighting for Drift Adaptation in Streaming Supervised Learning Problems (Mostra >>)
The EU-funded I3LUNG Project: Integrative Science, Intelligent Data Platform for Individualized LUNG Cancer Care With Immunotherapy (Mostra >>)


Elenco delle pubblicazioni e dei prodotti della ricerca per l'anno 2022 (Mostra tutto | Nascondi tutto)
Tipologia Titolo Pubblicazione/Prodotto
Abstract in Atti di convegno
Advancing drought monitoring via feature extraction and multi-task learning algorithms (Mostra >>)
Brevetti
A COMPUTER IMPLEMENTED METHOD FOR REAL TIME QUANTUM COMPILING BASED ON ARTIFICIAL INTELLIGENCE (Mostra >>)
Contributi su volumi (Capitolo o Saggio)
AI, Machine Learning e Data Mining (Mostra >>)
Contributo in Atti di convegno
Addressing Non-Stationarity in FX Trading with Online Model Selection of Offline RL Experts (Mostra >>)
Balancing Sample Efficiency and Suboptimality in Inverse Reinforcement Learning (Mostra >>)
Challenging Common Assumptions in Convex Reinforcement Learning (Mostra >>)
Dark-Pool Smart Order Routing: a Combinatorial Multi-armed Bandit Approach (Mostra >>)
Delayed Reinforcement Learning by Imitation (Mostra >>)
Finite Sample Analysis of Mean-Volatility Actor-Critic for Risk-Averse Reinforcement Learning (Mostra >>)
Goal-Directed Planning via Hindsight Experience Replay (Mostra >>)
Learning in Markov Games: can we exploit a general-sum opponent? (Mostra >>)
Lifelong Hyper-Policy Optimization with Multiple Importance Sampling Regularization (Mostra >>)
Multi-Armed Bandit Problem with Temporally-Partitioned Rewards: When Partial Feedback Counts (Mostra >>)
Multi-Fidelity Best-Arm Identification (Mostra >>)
Off-Policy Evaluation with Deficient Support Using Side Information (Mostra >>)
Pricing the Long Tail by Explainable Product Aggregation and Monotonic Bandits (Mostra >>)
Reward-Free Policy Space Compression for Reinforcement Learning (Mostra >>)
Stochastic Rising Bandits (Mostra >>)
Storehouse: a Reinforcement Learning Environment for Optimizing Warehouse Management (Mostra >>)
The Importance of Non-Markovianity in Maximum State Entropy Exploration (Mostra >>)
Trust Region Meta Learning for Policy Optimization (Mostra >>)
Unsupervised Reinforcement Learning in Multiple Environments (Mostra >>)
Articoli su riviste
A practical guide to multi-objective reinforcement learning and planning (Mostra >>)
An online state of health estimation method for lithium-ion batteries based on time partitioning and data-driven model identification (Mostra >>)
Machine Learning Using Real-World and Translational Data to Improve Treatment Selection for NSCLC Patients Treated with Immunotherapy (Mostra >>)
Online joint bid/daily budget optimization of Internet advertising campaigns (Mostra >>)
Real-world data to build explainable trustworthy artificial intelligence models for prediction of immunotherapy efficacy in NSCLC patients (Mostra >>)
Risk-averse policy optimization via risk-neutral policy optimization (Mostra >>)
Smoothing policies and safe policy gradients (Mostra >>)


Elenco delle pubblicazioni e dei prodotti della ricerca per l'anno 2021 (Mostra tutto | Nascondi tutto)
Tipologia Titolo Pubblicazione/Prodotto
Abstract in Rivista
Abstract PO-065: Artificial intelligence to improve selection for NSCLC patients treated with immunotherapy (Mostra >>)
Abstract in Atti di convegno
Advancing drought monitoring via feature extraction (Mostra >>)
The Human Nasal Cavity: Towards the Optimal Surgery with CFD and Machine Learning (Mostra >>)
Brevetti
Metodo implementato mediante computer per compilazione quantistica in tempo reale basato su intelligenza artificiale (Mostra >>)
Contributo in Atti di convegno
Conservative Online Convex Optimization (Mostra >>)
Exploiting History Data for Nonstationary Multi-armed Bandit (Mostra >>)
Inferring Functional Properties from Fluid Dynamics Features (Mostra >>)
Learning FX trading strategies with FQI and persistent actions (Mostra >>)
Learning a Belief Representation for Delayed Reinforcement Learning (Mostra >>)
Learning in Non-Cooperative Configurable Markov Decision Processes (Mostra >>)
Leveraging Good Representations in Linear Contextual Bandits (Mostra >>)
Meta-Reinforcement Learning by Tracking Task Non-stationarity (Mostra >>)
Monte carlo tree search for trading and hedging (Mostra >>)
Newton Optimization on Helmholtz Decomposition for Continuous Games (Mostra >>)
Policy Optimization as Online Learning with Mediator Feedback (Mostra >>)
Provably Efficient Learning of Transferable Rewards (Mostra >>)
Reinforcement Learning in Linear MDPs: Constant Regret and Representation Selection (Mostra >>)
Subgaussian and Differentiable Importance Sampling for Off-Policy Evaluation and Learning (Mostra >>)
Task-Agnostic Exploration via Policy Gradient of a Non-Parametric State Entropy Estimate (Mostra >>)
Time-Variant Variational Transfer for Value Functions (Mostra >>)
Articoli su riviste
A voltage dynamic-based state of charge estimation method for batteries storage systems (Mostra >>)
Data-driven indicators for the detection and prediction of stuck-pipe events in oil&gas drilling operations (Mostra >>)
Dealing with multiple experts and non-stationarity in inverse reinforcement learning: an application to real-life problems (Mostra >>)
Gaussian approximation for bias reduction in Q-learning (Mostra >>)
MushroomRL: Simplifying Reinforcement Learning Research (Mostra >>)
Policy space identification in configurable environments (Mostra >>)
Quantum compiling by deep reinforcement learning (Mostra >>)
Safe policy iteration: A monotonically improving approximate policy iteration approach (Mostra >>)


Elenco delle pubblicazioni e dei prodotti della ricerca per l'anno 2020 (Mostra tutto | Nascondi tutto)
Tipologia Titolo Pubblicazione/Prodotto
Contributo in Atti di convegno
A Data-Based Approach for the Prediction of Stuck-Pipe Events in Oil Drilling Operations (Mostra >>)
A Novel Confidence-Based Algorithm for Structured Bandits (Mostra >>)
An Asymptotically Optimal Primal-Dual Incremental Algorithm for Contextual Linear Bandits (Mostra >>)
An Intrinsically-Motivated Approach for Learning Highly Exploring and Fast Mixing Policies (Mostra >>)
Balancing Learning Speed and Stability in Policy Gradient via Adaptive Exploration (Mostra >>)
Control Frequency Adaptation via Action Persistence in Batch Reinforcement Learning (Mostra >>)
Dealing with Transaction Costs in Portfolio Optimization: Online Gradient Descent with Momentum (Mostra >>)
Driving exploration by maximum distribution in gaussian process bandits (Mostra >>)
Fast direct calibration of interest rate derivatives pricing models (Mostra >>)
Foreign exchange trading: A risk-averse batch reinforcement learning approach (Mostra >>)
Gradient-Aware Model-Based Policy Search (Mostra >>)
Inverse Reinforcement Learning from a Gradient-based Learner (Mostra >>)
Model-Free Non-Stationarity Detection and Adaptation in Reinforcement Learning (Mostra >>)
Option Hedging with Risk Averse Reinforcement Learning (Mostra >>)
Risk-Averse Trust Region Optimization for Reward-Volatility Reduction (Mostra >>)
Sequential Transfer in Reinforcement Learning with a Generative Model (Mostra >>)
Sharing Knowledge in Multi-Task Deep Reinforcement Learning (Mostra >>)
Truly Batch Model-Free Inverse Reinforcement Learning about Multiple Intentions (Mostra >>)
Articoli su riviste
Combining reinforcement learning with rule-based controllers for transparent and general decision-making in autonomous driving (Mostra >>)
Importance Sampling Techniques for Policy Optimization (Mostra >>)
On the use of the policy gradient and Hessian in inverse reinforcement learning (Mostra >>)
Sliding-Window Thompson Sampling for Non-Stationary Settings (Mostra >>)


Elenco delle pubblicazioni e dei prodotti della ricerca per l'anno 2019 (Mostra tutto | Nascondi tutto)
Tipologia Titolo Pubblicazione/Prodotto
Contributo in Atti di convegno
Dealing with interdependencies and uncertainty in multi-channel advertising campaigns optimization (Mostra >>)
Exploiting Action-Value Uncertainty to Drive Exploration in Reinforcement Learning (Mostra >>)
Exploration Driven by an Optimistic Bellman Equation (Mostra >>)
Feature Selection via Mutual Information: New Theoretical Insights (Mostra >>)
IDIL: Exploiting Interdependence to Optimize Multi-Channel Advertising Campaigns (Mostra >>)
Optimistic Policy Optimization via Multiple Importance Sampling (Mostra >>)
Propagating Uncertainty in Reinforcement Learning via Wasserstein Barycenters (Mostra >>)
Reinforcement Learning Based Control of Coherent Transport by Adiabatic Passage of Spin Qubits (Mostra >>)
Reinforcement Learning in Configurable Continuous Environments (Mostra >>)
Transfer of Samples in Policy Search via Multiple Importance Sampling (Mostra >>)
Articoli su riviste
Coherent transport of quantum states by deep reinforcement learning (Mostra >>)
manifesti v. 3.5.10 / 3.5.10
Area Servizi ICT
01/10/2023