Mohammad Ghavamzadeh                  Google Scholar

 
 

2018


  1. Bullet    Two papers on “A Lyapunov-based Approach to Safe Reinforcement Learning” and “A Block Coordinate Ascent Algorithm for Mean-Variance Optimization” got accepted at NIPS-2018.


  1. Bullet    Our paper on “Finite-sample Analysis of Proximal Gradient TD Algorithms” got accepted at Journal of Artificial Intelligence Research (JAIR).


  1. Bullet    Two papers on “Path Consistency Learning in Tsallis Entropy Regularized MDPs” and “More Robust Doubly Robust Off-policy Evaluation” got accepted at ICML-2018.


  1. Bullet    I taught at the Deep Learning & Reinforcement Learning summer school organized by CIFAR and the Vector Institute at the University of Toronto in August.


  1. Bullet    Our paper on “Robust Locally-Linear Controllable Embedding” got accepted at AISTATS-2018.


  1. Bullet    Our paper on “Risk-Constrained Reinforcement Learning with Percentile Risk Criteria” published at Journal of Machine Learning Research (JMLR).


  1. Bullet    I served as an area chair for NIPS-2018 and ICML-2018, and as a senior program committee member for IJCAI-2018 and AAAI-2018.    


2017


  1. Bullet    A journal paper published: “Sequential Decision-making with Coherent Risk” at IEEE Transaction on Automatic Control (TAC).


  1. Bullet    Eight conference papers published: “Conservative Contextual Linear Bandits” at NIPS-2017, “Active Learning for Accurate Estimation of Linear Models”, “Bottleneck Conditional Density Estimation”, “Diffusion Independent Semi-Bandit Influence Maximization”, and “Online Learning to Rank in Stochastic Click Models” at ICML-2017, “Sequential Multiple Hypothesis Testing with Type I Error Control” at AISTATS-2017, “Predictive Off-Policy Evaluation for Nonstationary Decision Problems” and “Automated Data Cleansing through Meta-Learning” at IAAI-2017.


  1. Bullet    Together with Marek Petrik, we gave a tutorial on “Risk-averse Decision-making and Control” at AAAI-2017. (tutorial website)    


  1. Bullet    I gave an invited talk at the 2nd Asian Workshop on Reinforcement Learning in Seoul, South Korea on November 15, 2017.


  1. Bullet    I served as an area chair for NIPS-2017 and as a senior program committee member for AAAI-2017. 


2016   


  1. Bullet    Four journal papers published: “Analysis of Classification-based Policy Iteration Algorithms”, “Bayesian Policy Gradient and Actor-Critic Algorithms”, and “Regularized Policy Iteration for Non-Parametric Function Spaces” at Journal of Machine Learning Research (JMLR), and “Variance-constrained Actor-Critic Algorithms for Discounted and Average Reward MDPs” at Machine Learning Journal (MLJ).


  1. Bullet    Four conference papers published: “Safe Policy Improvement by Minimizing Robust Baseline Regret” at NIPS-2016, “Improved Learning Complexity in Combinatorial Pure Exploration Bandits” at AISTATS-2016, “Proximal Gradient Temporal Difference Learning Algorithms” at the sister conference best paper track at IJCAI-2016, and “Graphical Model Sketch” at ECML-2016. 


  1. Bullet    I gave an invited talk at the 13th European Workshop on Reinforcement Learning (EWRL) in Barcelona on December 3-4, 2016.


  1. Bullet    I served as a senior program committee member for IJCAI-2016 and ECML-2016.


2015   


  1. Bullet    Three journal papers published: “Approximate Modified Policy Iteration and its Application to the Game of Tetris” at Journal of Machine Learning Research (JMLR), “Classification-based Approximate Policy Iteration” at IEEE Transactions on Automatic Control (TAC), and “Bayesian Reinforcement Learning: A Survey” at Foundation and Trends in Machine Learning. 


  1. Bullet    Five conference papers published: “High Confidence Off-Policy Evaluation” at AAAI-2015, “Maximum Entropy Semi-Supervised Inverse Reinforcement Learning” at IJCAI-2015, “Building Personalized Ad Recommendation Systems for Life-Time Value Optimization with Guarantees” at IJCAI-2015, “High Confidence Policy Improvement” at ICML-2015, and “Policy Gradient for Coherent Risk Measures” at NIPS-2015.


  1. Bullet    Our paper entitled “Finite-Sample Analysis of Proximal Gradient TD Algorithms” won the Facebook best student paper award at UAI-2015


  1. Bullet    I co-chaired two workshops: 12th European Workshop on Reinforcement Learning (EWRL-12) as a workshop at ICML-2015 and “Machine Learning in eCommerce” at NIPS-2015.


  1. Bullet    My student, Victor Gabillon, won the AFIA (French Association for Artificial Intelligence) prize for the 2nd best Ph.D. thesis (completed in 2014) on artificial intelligence in France.


  1. Bullet    I served as a senior program committee member for IJCAI-2015. 


2014


  1. Bullet    A paper published: “Algorithms for CVaR Optimization in MDPs” at NIPS-2014.


  1. Bullet    I co-chaired three workshops: “Sequential Decision-Making with Big Data” at AAAI-2014, Customers Value Optimization in Digital Marketing” at ICML-2014, and Large-scale Reinforcement Learning and Markov Decision Problems” at NIPS-2014.


  1. Bullet    I successfully defended my “Habilitation à Diriger des Recherches” (HDR) thesis and graduated my Ph.D. student Victor Gabillon in June 2014. Victor will be a postdoc with Prof. Peter Bartlett at UC Berkeley starting October 2014.


  1. Bullet    I served as an area chair for NIPS-2014.


Professional Experience


Senior Research Scientist (on leave from INRIA)

Facebook AI Research (FAIR), CA  (Oct. 2018 - present)


Senior Research Scientist (on leave from INRIA)

Google DeepMind, CA  (Jun. 2017 - Oct. 2018)


Senior Analytics Researcher

Adobe Research, San Jose, CA  (Oct. 2013 - Jun. 2017)


Habilitation à Diriger des Recherches (HDR)

Université Lille 1, France  (June 2014)


Chargé de Recherche  CR1 (on leave at Adobe)

INRIA Lille - Team SequeL, France  (2010 - Oct. 2013)


Chargé de recherche  CR2

INRIA Lille - Team SequeL, France  (2008 - 2010)


postdoctoral Fellow

University of Alberta, Canada  (2005 - 2008)


Ph.D. in Computer Science

University of Massachusetts Amherst, USA  (2001 - 2005)




Research Interests


Machine Learning

Artificial Intelligence

Control

Reinforcement Learning




Contact Information


Mailing Address

1 Facebook Way

Menlo Park, CA 94025


Office

Facebook Building 21


Email

mgh at fb dot com

mohammad dot ghavamzadeh at inria dot fr

 

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