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Information on didactic, research and institutional assignments on this page are certified by the University; more information, prepared by the professor, are available on the personal web page and in the curriculum vitae indicated on this webpage.
Information on professor
ProfessorRestelli Marcello
QualificationAssociate professor full time
Belonging DepartmentDipartimento di Elettronica, Informazione e Bioingegneria
Scientific-Disciplinary SectorING-INF/05 - Information Processing Systems
Curriculum VitaeDownload CV (518.02Kb - 01/09/2022)

Professor's office hours
DEI----WednesdayFrom 11:00
To 13:00
4015--Si consiglia di prendere appuntamento via email con il docente
Professor's personal websitehttp://home.deib.polimi.it/restelli/

Data source: RE.PUBLIC@POLIMI - Research Publications at Politecnico di Milano

List of publications and reserach products for the year 2023
No product yet registered in the year 2023

List of publications and reserach products for the year 2022 (Show all details | Hide all details)
Type Title of the Publicaiton/Product
Contributions on scientific books
AI, Machine Learning e Data Mining (Show >>)
Conference proceedings
Balancing Sample Efficiency and Suboptimality in Inverse Reinforcement Learning (Show >>)
Goal-Directed Planning via Hindsight Experience Replay (Show >>)
Lifelong Hyper-Policy Optimization with Multiple Importance Sampling Regularization (Show >>)
Stochastic Rising Bandits (Show >>)
Storehouse: a Reinforcement Learning Environment for Optimizing Warehouse Management (Show >>)
Journal Articles
Machine Learning Using Real-World and Translational Data to Improve Treatment Selection for NSCLC Patients Treated with Immunotherapy (Show >>)
Online joint bid/daily budget optimization of Internet advertising campaigns (Show >>)

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

List of publications and reserach products for the year 2020 (Show all details | Hide all details)
Type Title of the Publicaiton/Product
Conference proceedings
A Data-Based Approach for the Prediction of Stuck-Pipe Events in Oil Drilling Operations (Show >>)
A Novel Confidence-Based Algorithm for Structured Bandits (Show >>)
An Asymptotically Optimal Primal-Dual Incremental Algorithm for Contextual Linear Bandits (Show >>)
An Intrinsically-Motivated Approach for Learning Highly Exploring and Fast Mixing Policies (Show >>)
Balancing Learning Speed and Stability in Policy Gradient via Adaptive Exploration (Show >>)
Control Frequency Adaptation via Action Persistence in Batch Reinforcement Learning (Show >>)
Dealing with Transaction Costs in Portfolio Optimization: Online Gradient Descent with Momentum (Show >>)
Driving exploration by maximum distribution in gaussian process bandits (Show >>)
Fast direct calibration of interest rate derivatives pricing models (Show >>)
Foreign exchange trading: A risk-averse batch reinforcement learning approach (Show >>)
Gradient-Aware Model-Based Policy Search (Show >>)
Inverse Reinforcement Learning from a Gradient-based Learner (Show >>)
Model-Free Non-Stationarity Detection and Adaptation in Reinforcement Learning (Show >>)
Option Hedging with Risk Averse Reinforcement Learning (Show >>)
Risk-Averse Trust Region Optimization for Reward-Volatility Reduction (Show >>)
Sequential Transfer in Reinforcement Learning with a Generative Model (Show >>)
Sharing Knowledge in Multi-Task Deep Reinforcement Learning (Show >>)
Truly Batch Model-Free Inverse Reinforcement Learning about Multiple Intentions (Show >>)
Journal Articles
Combining reinforcement learning with rule-based controllers for transparent and general decision-making in autonomous driving (Show >>)
Importance Sampling Techniques for Policy Optimization (Show >>)
On the use of the policy gradient and Hessian in inverse reinforcement learning (Show >>)
Sliding-Window Thompson Sampling for Non-Stationary Settings (Show >>)

List of publications and reserach products for the year 2019 (Show all details | Hide all details)
Type Title of the Publicaiton/Product
Conference proceedings
Dealing with interdependencies and uncertainty in multi-channel advertising campaigns optimization (Show >>)
Exploiting Action-Value Uncertainty to Drive Exploration in Reinforcement Learning (Show >>)
Exploration Driven by an Optimistic Bellman Equation (Show >>)
Feature Selection via Mutual Information: New Theoretical Insights (Show >>)
IDIL: Exploiting Interdependence to Optimize Multi-Channel Advertising Campaigns (Show >>)
Optimistic Policy Optimization via Multiple Importance Sampling (Show >>)
Propagating Uncertainty in Reinforcement Learning via Wasserstein Barycenters (Show >>)
Reinforcement Learning Based Control of Coherent Transport by Adiabatic Passage of Spin Qubits (Show >>)
Reinforcement Learning in Configurable Continuous Environments (Show >>)
Transfer of Samples in Policy Search via Multiple Importance Sampling (Show >>)
Journal Articles
Coherent transport of quantum states by deep reinforcement learning (Show >>)
manifesti v. 3.5.4 / 3.5.4
Area Servizi ICT