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NIPS
1993
13 years 10 months ago
Robust Reinforcement Learning in Motion Planning
While exploring to nd better solutions, an agent performing online reinforcement learning (RL) can perform worse than is acceptable. In some cases, exploration might have unsafe, ...
Satinder P. Singh, Andrew G. Barto, Roderic A. Gru...
SIGECOM
2011
ACM
259views ECommerce» more  SIGECOM 2011»
12 years 12 months ago
Designing adaptive trading agents
ended abstract summarizes the research presented in Dr. Pardoe’s recently-completed Ph.D. thesis [Pardoe 2011]. The thesis considers how adaptive trading agents can take advantag...
David Pardoe, Peter Stone
NLE
2007
148views more  NLE 2007»
13 years 8 months ago
Abbreviated text input using language modeling
We address the problem of improving the efficiency of natural language text input under degraded conditions (for instance, on mobile computing devices or by disabled users), by ta...
Stuart M. Shieber, Rani Nelken
TMA
2010
Springer
137views Management» more  TMA 2010»
13 years 7 months ago
K-Dimensional Trees for Continuous Traffic Classification
Abstract. The network measurement community has proposed multiple machine learning (ML) methods for traffic classification during the last years. Although several research works ha...
Valentín Carela-Español, Pere Barlet...
ACL
2009
13 years 6 months ago
Stochastic Gradient Descent Training for L1-regularized Log-linear Models with Cumulative Penalty
Stochastic gradient descent (SGD) uses approximate gradients estimated from subsets of the training data and updates the parameters in an online fashion. This learning framework i...
Yoshimasa Tsuruoka, Jun-ichi Tsujii, Sophia Anania...