Mohammad Ghavamzadeh                  Google Scholar

 
 

2017


  1. Bullet    I will serve as an area chair for ICML-2018.


  1. Bullet    I will serve as a senior program committee member for IJCAI-2018.   


  1. Bullet    A paper on “Conservative Contextual Linear Bandits” got accepted at NIPS-2017.


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


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


  1. Bullet    Four papers on “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” got accepted at ICML-2017.


  1. Bullet    I will serve as a senior program committee member for AAAI-2018.


  1. Bullet    I will serve as an area chair for NIPS-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    Our paper on “Sequential Decision-making with Coherent Risk” got published at IEEE Transaction on Automatic Control (TAC).


  1. Bullet    Three conference papers got accepted: a paper on “Sequential Multiple Hypothesis Testing with Type I Error Control” at AISTATS-2017 and two papers on “Predictive Off-Policy Evaluation for Nonstationary Decision Problems” and on “Automated Data Cleansing through Meta-Learning” at IAAI-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.


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.


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)

Google DeepMind, CA  (Jun. 2017 - present)


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

1600 Amphitheatre Parkway

Mountain View, CA 94043


Office

Google MTV Building 41


Email

ghavamza at google dot com

mohammad dot ghavamzadeh at inria dot fr

 

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