Sites Inria

Version française

Best student paper award

MB Dernoncourt - 28/11/2019

Best student paper award to Mahsa Asadi

Mahsa Asadi, a PhD student in the Magnet* project team under the supervision of Marc Tommasi and Aurélien Bellet, received the best student paper award at the ACML 2019 conference. This prize is in recognition of his article "Model-Based Reinforcement Learning Exploiting State-Action Equivalence", produced in 2018 under the direction of Odalric Maillard of the Sequel** project team. The other authors are Mohammad Sadegh Talebi (Inria postdoc, ANR Badass); Hippolyte Bourel (ENS Rennes); Odalric Maillard (Inria).

343 submissions were sent and 87 papers were accepted, for a total of 25.4% acceptance.  The selection of finalists was revealed during the gala evening at the Nagoya Castle Hotel.

The 11th Asian Conference on Machine Learning, Nagoya, Japan

Date: November 17 - 19, 2019

The conference aims to provide a leading international forum for researchers in machine learning and related fields to share their new ideas, progress and achievements. Submissions from regions other than the Asia-Pacific are also highly encouraged.

The conference calls for high-quality, original research papers in the theory and practice of machine learning. The conference also solicits proposals focusing on frontier research, new ideas and paradigms in machine learning. ACML has taken place annually since 2009 in locations throughout the Asia-Pacific region. This is the 11th Conference to be held in Nagoya, Japan after previous conferences were held in Beijing, China (2018), Seoul, Korea (2017), Hamilton, New Zealand (2016), Hong Kong, China (2015), Nha Trang, Vietnam (2014), Canberra, Australia (2013), Singapore (2012), Taoyuan, Taiwan (2011), Tokyo, Japan (2010), and Nanjing, China (2009).

*Magnet is a research team at Inria and in CRIStAL (Centrale Lille, CNRS, Université de Lille)
**Sequel is a research team at Inria and in CRIStAL (Centrale Lille, CNRS, Université de Lille)

Keywords: Sequel team Machine learning Magnet team

Top