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ICML
1994
IEEE
14 years 1 months ago
Learning Without State-Estimation in Partially Observable Markovian Decision Processes
Reinforcement learning (RL) algorithms provide a sound theoretical basis for building learning control architectures for embedded agents. Unfortunately all of the theory and much ...
Satinder P. Singh, Tommi Jaakkola, Michael I. Jord...

Publication
233views
12 years 8 months ago
Sparse reward processes
We introduce a class of learning problems where the agent is presented with a series of tasks. Intuitively, if there is relation among those tasks, then the information gained duri...
Christos Dimitrakakis

Lab
652views
15 years 9 months ago
Electronic Enterprises Laboratory
Our research is motivated by a strong conviction that business processes in electronic enterprises can be designed to deliver high levels of performance through the use of mathemat...
ISAAC
2005
Springer
138views Algorithms» more  ISAAC 2005»
14 years 3 months ago
On the Complexity of Rocchio's Similarity-Based Relevance Feedback Algorithm
In this paper, we prove for the first time that the learning complexity of Rocchio’s algorithm is O(d+d2 (log d+log n)) over the discretized vector space {0, . . . , n − 1}d ,...
Zhixiang Chen, Bin Fu
ICCV
2009
IEEE
15 years 3 months ago
Action Detection in Complex Scenes with Spatial and Temporal Ambiguities
In this paper, we investigate the detection of semantic human actions in complex scenes. Unlike conventional action recognition in well-controlled environments, action detection...
Yuxiao Hu, Liangliang Cao, Fengjun Lv, Shuicheng Y...