Person: Shie Mannor

DBLP: Mannor:Shie

Contributed to:

2015

2014

2014

2013

2013

2012

2011

2009

2008

2007

2006

2005

2004

2003

2001

Wrote 30 papers:

ICML-2015-HallakSMM #learning #modelling

Off-policy Model-based Learning under Unknown Factored Dynamics (AH, FS, TAM, SM), pp. 711–719.

ICML-2015-RichmanM #classification #constraints

Dynamic Sensing: Better Classification under Acquisition Constraints (OR, SM), pp. 267–275.

ICML-c1-2014-GopalanMM #online #problem

Thompson Sampling for Complex Online Problems (AG, SM, YM), pp. 100–108.

ICML-c1-2014-MaillardM

Latent Bandits (OAM, SM), pp. 136–144.

ICML-c1-2014-MannM #approximate #policy #scalability

Scaling Up Approximate Value Iteration with Options: Better Policies with Fewer Iterations (TAM, SM), pp. 127–135.

ICML-c2-2014-HarelMEC #concept #detection

Concept Drift Detection Through Resampling (MH, SM, REY, KC), pp. 1009–1017.

ICML-c2-2014-MannMM

Time-Regularized Interrupting Options (TRIO) (TAM, DJM, SM), pp. 1350–1358.

ICML-c2-2014-TamarMX #approximate #robust #scalability #using

Scaling Up Robust MDPs using Function Approximation (AT, SM, HX), pp. 181–189.

ICML-c3-2013-ChenCM #robust

Robust Sparse Regression under Adversarial Corruption (YC, CC, SM), pp. 774–782.

ICML-c3-2013-TamarCM #difference

Temporal Difference Methods for the Variance of the Reward To Go (AT, DDC, SM), pp. 495–503.

KDD-2013-HallakCM #markov #process

Model selection in markovian processes (AH, DDC, SM), pp. 374–382.

ICML-2012-AvnerMS #multi

Decoupling Exploration and Exploitation in Multi-Armed Bandits (OA, SM, OS), p. 145.

ICML-2012-CastroTM #policy

Policy Gradients with Variance Related Risk Criteria (DDC, AT, SM), p. 215.

ICML-2012-MannorMX #nondeterminism #robust

Lightning Does Not Strike Twice: Robust MDPs with Coupled Uncertainty (SM, OM, HX), p. 62.

ICML-2011-HarelM #learning #multi

Learning from Multiple Outlooks (MH, SM), pp. 401–408.

ICML-2011-MannorT #markov #optimisation #process

Mean-Variance Optimization in Markov Decision Processes (SM, JNT), pp. 177–184.

ICML-2011-VainsencherDM #estimation #online

Bundle Selling by Online Estimation of Valuation Functions (DV, OD, SM), pp. 1137–1144.

ICML-2011-YuM

Unimodal Bandits (JYY, SM), pp. 41–48.

ICML-2009-YuM #problem

Piecewise-stationary bandit problems with side observations (JYY, SM), pp. 1177–1184.

ICML-2008-FrankMP #learning

Reinforcement learning in the presence of rare events (JF, SM, DP), pp. 336–343.

ICML-2007-DelageM #markov #nondeterminism #optimisation #performance #process

Percentile optimization in uncertain Markov decision processes with application to efficient exploration (ED, SM), pp. 225–232.

ICML-2006-KellerMP #approximate #automation #learning #programming

Automatic basis function construction for approximate dynamic programming and reinforcement learning (PWK, SM, DP), pp. 449–456.

ICML-2005-EngelMM #learning #process

Reinforcement learning with Gaussian processes (YE, SM, RM), pp. 201–208.

ICML-2005-MannorPR #classification

The cross entropy method for classification (SM, DP, RYR), pp. 561–568.

ICML-2004-MannorMHK #abstraction #clustering #learning

Dynamic abstraction in reinforcement learning via clustering (SM, IM, AH, UK).

ICML-2004-MannorSST #bias #estimation

Bias and variance in value function estimation (SM, DS, PS, JNT).

ICML-2003-EngelMM #approach #difference #learning #process

Bayes Meets Bellman: The Gaussian Process Approach to Temporal Difference Learning (YE, SM, RM), pp. 154–161.

ICML-2003-Even-DarMM #learning

Action Elimination and Stopping Conditions for Reinforcement Learning (EED, SM, YM), pp. 162–169.

ICML-2003-MannorRG #performance #policy

The Cross Entropy Method for Fast Policy Search (SM, RYR, YG), pp. 512–519.

ICML-2001-EngelM #embedded #learning #markov #process

Learning Embedded Maps of Markov Processes (YE, SM), pp. 138–145.