Romain Cosson

Inria Paris, France

Don't hesitate to reach out!

Email: romain (dot) cosson (at) inria (dot) fr
Linkedin profile, Google scholar

About

I am a PhD student at Inria Paris and affliated to Argo in DI ENS where I am advised by Prof. Laurent Massoulié. My research interest is in online algorithms, inference, and decision-making. Prior to my PhD, I received a M.S. degree in computer science from MIT where I was advised by Prof. Devavrat Shah. My undergraduate was in economics and computer science as an "élève ingénieur" at Ecole polytechnique. I was also fortunate to work with many other inspiring collaborators, among whom are Moïse Blanchard, Prof. Steve Hanneke, Prof. Ali Jadbabie, Prof. Anuran Makur, Amirhossein Reisizadeh, and Prof. Laurent Viennot.

Research Papers

• Barely Random Algorithms for Metrical Task Systems
  Romain Cosson and Laurent Massoulié.
  Preprint.
• Ariadne and Theseus: Exploration and Rendezvous with Two Mobile Agents in an Unknown Graph
  Romain Cosson.
  Preprint.
• Collective Tree Exploration via Potential Function Method
  Romain Cosson and Laurent Massoulié.
  15th Innovations in Theoretical Computer Science (ITCS), 2024.
• Breaking the k/log k Barrier in Collective Tree Exploration via Tree-Mining
  Romain Cosson.
  35th Annual Symposium on Discrete Algorithms (SODA), 2024.
• Efficient Collaborative Tree Exploration with Breadth-First Depth-Next
  Romain Cosson, Laurent Massoulié and Laurent Viennot.
  37th International Symposium on Distributed Computing (DISC), 2023. download paper
• Brief Announcement: Efficient Collaborative Tree Exploration with Breadth-First Depth-Next
  Romain Cosson, Laurent Massoulié and Laurent Viennot.
  42nd Symposium on Principles of Distributed Computing (PODC), 2023. download paper
• Universal Online Learning with Bounded Loss: Reduction to Binary Classification
  Moïse Blanchard and Romain Cosson.
  35th Annual Conference on Learning Theory (COLT), 2022.
• Universal Online Learning with Unbounded Losses: Memory Is All You Need
  Moïse Blanchard, Romain Cosson, and Steve Hanneke.
  33rd International Conference on Algorithmic Learning Theory (ALT), 2022.
• Quantifying Variational Approximation for the Log-Partition Function
  Romain Cosson, and Devavrat Shah.
  34th Annual Conference on Learning Theory (COLT), 2021.

Teaching Assistant

• ENPC | Introduction to Optimization | Fall 2023
• ENS | Randomized Algorithms (SAA) | Fall 2022, Fall 2023
• MIT | Algorithms for Inference (6.438) | Fall 2021
• Sorbonne | International Macroeconomics (L2) | Spring 2020
• Sorbonne | Intro to economics (L1) | Fall 2019
• Sorbonne | Statistics (L3) | Fall 2019
• Sorbonne | Statistics (L2) | Spring 2018

Recent Talks

• "Can we find a short path, without a map? Can we parallelize maze-solving?", Inria PhD Seminar 2024
• "Collective Tree Exploration and Layered Graph Traversal", ALGORIDAM Seminar 2024
• "Collective Tree Exploration via Potential Function Method", ITCS 2024 - recorded version
• "Breaking the k/log k Barrier in Collective Tree Exploration via Tree-Mining", SODA 2024
• "Competitive Analysis of Collective Tree Exploration: Can we parallelize maze-solving?", Talgo Seminar, 2023
• "Efficient Collaborative Tree Exploration with Breadth-First Depth-Next", DISC 2023
• "Additive Overhead for Online Problems", ARGO Seminar 2023
• "Reduction from Binary Classification for Universal Online Learning", COLT 2022
• "Approximating the Log-Partition Function", ARGO Seminar 2022
• "Approximating the Log-Partition Function", COLT 2021 - recorded version

-- Argo is a project team of INRIA Paris and affilitaed to DI ENS --

-- I am interested in the topic of collaborative exploration, above is an animated illustration --