`Travelled to:`

1 × Australia

1 × France

1 × Israel

1 × United Kingdom

6 × USA

`Collaborated with:`

A.Lazaric S.Mahadevan R.Munos B.Scherrer M.Geist V.Gabillon Y.Engel P.S.Thomas G.Theocharous H.Kadri P.Preux B.A.Pires C.Szepesvári M.W.Hoffman

`Talks about:`

polici (5) learn (5) algorithm (3) reinforc (3) hierarch (3) classif (3) analysi (3) iter (3) bayesian (2) approach (2)

## Person: Mohammad Ghavamzadeh

### DBLP: Ghavamzadeh:Mohammad

### Contributed to:

### Wrote 14 papers:

- ICML-2015-ThomasTG #policy
- High Confidence Policy Improvement (PST, GT, MG), pp. 2380–2388.
- ICML-c1-2013-KadriGP #approach #kernel #learning
- A Generalized Kernel Approach to Structured Output Learning (HK, MG, PP), pp. 471–479.
- ICML-c3-2013-PiresSG #bound #classification #multi
- Cost-sensitive Multiclass Classification Risk Bounds (BAP, CS, MG), pp. 1391–1399.
- ICML-2012-GeistSLG #approach #difference #learning
- A Dantzig Selector Approach to Temporal Difference Learning (MG, BS, AL, MG), p. 49.
- ICML-2012-ScherrerGGG #approximate #policy
- Approximate Modified Policy Iteration (BS, VG, MG, MG), p. 245.
- ICML-2011-GabillonLGS #classification #policy
- Classification-based Policy Iteration with a Critic (VG, AL, MG, BS), pp. 1049–1056.
- ICML-2011-GhavamzadehLMH #analysis
- Finite-Sample Analysis of Lasso-TD (MG, AL, RM, MWH), pp. 1177–1184.
- ICML-2010-LazaricG #learning #multi
- Bayesian Multi-Task Reinforcement Learning (AL, MG), pp. 599–606.
- ICML-2010-LazaricGM #algorithm #analysis #classification #policy
- Analysis of a Classification-based Policy Iteration Algorithm (AL, MG, RM), pp. 607–614.
- ICML-2010-LazaricGM10a #analysis
- Finite-Sample Analysis of LSTD (AL, MG, RM), pp. 615–622.
- ICML-2007-GhavamzadehE #algorithm
- Bayesian actor-critic algorithms (MG, YE), pp. 297–304.
- ICML-2003-GhavamzadehM #algorithm #policy
- Hierarchical Policy Gradient Algorithms (MG, SM), pp. 226–233.
- ICML-2002-GhavamzadehM #learning
- Hierarchically Optimal Average Reward Reinforcement Learning (MG, SM), pp. 195–202.
- ICML-2001-GhavamzadehM #learning
- Continuous-Time Hierarchical Reinforcement Learning (MG, SM), pp. 186–193.