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ICML
2005
IEEE
16 years 3 months ago
Identifying useful subgoals in reinforcement learning by local graph partitioning
We present a new subgoal-based method for automatically creating useful skills in reinforcement learning. Our method identifies subgoals by partitioning local state transition gra...
Özgür Simsek, Alicia P. Wolfe, Andrew G....
154
Voted
ILP
2007
Springer
15 years 9 months ago
Structural Statistical Software Testing with Active Learning in a Graph
Structural Statistical Software Testing (SSST) exploits the control flow graph of the program being tested to construct test cases. Specifically, SSST exploits the feasible paths...
Nicolas Baskiotis, Michèle Sebag
270
Voted
ICCV
2011
IEEE
14 years 2 months ago
Learning Spatiotemporal Graphs of Human Activities
Complex human activities occurring in videos can be defined in terms of temporal configurations of primitive actions. Prior work typically hand-picks the primitives, their total...
William Brendel, Sinisa Todorovic
132
Voted
ICML
2004
IEEE
15 years 8 months ago
Kernel-based discriminative learning algorithms for labeling sequences, trees, and graphs
We introduce a new perceptron-based discriminative learning algorithm for labeling structured data such as sequences, trees, and graphs. Since it is fully kernelized and uses poin...
Hisashi Kashima, Yuta Tsuboi
CVPR
2008
IEEE
16 years 4 months ago
Manifold learning using robust Graph Laplacian for interactive image search
Interactive image search or relevance feedback is the process which helps a user refining his query and finding difficult target categories. This consists in partially labeling a ...
Hichem Sahbi, Patrick Etyngier, Jean-Yves Audibert...