Carlo Alfano

Carlo Alfano

DPhil Student

University of Oxford

Biography

I am a 3rd year PhD student in the Department of Statistics at the University of Oxford, under the supervision of Patrick Rebeschini and George Deligiannidis. I am funded by EPSRC.

My research interests include reinforcement learning, optimization and learning theory. In particular, I focus on building and analysing reinforcement learning algorithms using standard optimization tools, such as natural gradient descent and mirror descent.

Download my CV.

Interests
  • Theory of Reinforcement Learning
  • Optimization
Education
  • DPhil in Statistics, 2020-present

    University of Oxford

  • MSc in Statistical Sciences, 2019-2020

    University of Oxford

  • BSc in Statistics, Economics and Finance, 2016-2019

    Sapienza University of Rome

Publications

(2023). A Novel Framework for Policy Mirror Descent with General Parametrization and Linear Convergence. To appear in Advances in Neural Information Systems.

PDF

(2022). Linear Convergence for Natural Policy Gradient with Log-linear Policy Parametrization. arXiv preprint: 2209.15382.

PDF

(2021). Dimension-Free Rates for Natural Policy Gradient in Multi-Agent Reinforcement Learning. arXiv preprint: 2109.11692.

PDF

Teaching and Tutoring

 
 
 
 
 
Teaching Assistant
University of Oxford
Oct 2020 – Present United Kingdom

Taught Courses:

  • Algorithmic Foundation of Learning
  • Advanced Simulation Methods
 
 
 
 
 
Supervisor
UNIQ+ DeepMind internship at the University of Oxford
Jun 2022 – Sep 2022 United Kingdom

Awards

G-Research Grant for PhD students and postdocs in quantitative fields
EPSRC DTP full scholarship
Full scholarship holder
Honorable mention