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» On Kernel Methods for Relational Learning
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127
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IJCAI
2003
15 years 3 months ago
Covariant Policy Search
We investigate the problem of non-covariant behavior of policy gradient reinforcement learning algorithms. The policy gradient approach is amenable to analysis by information geom...
J. Andrew Bagnell, Jeff G. Schneider
121
Voted
ICML
2010
IEEE
15 years 2 months ago
A DC Programming Approach for Sparse Eigenvalue Problem
We investigate the sparse eigenvalue problem which arises in various fields such as machine learning and statistics. Unlike standard approaches relying on approximation of the l0n...
Mamadou Thiao, Pham Dinh Tao, Le Thi Hoai An
139
Voted
DMIN
2008
190views Data Mining» more  DMIN 2008»
15 years 4 months ago
Optimization of Self-Organizing Maps Ensemble in Prediction
The knowledge discovery process encounters the difficulties to analyze large amount of data. Indeed, some theoretical problems related to high dimensional spaces then appear and de...
Elie Prudhomme, Stéphane Lallich
149
Voted
WWW
2009
ACM
15 years 9 months ago
StatSnowball: a statistical approach to extracting entity relationships
Traditional relation extraction methods require pre-specified relations and relation-specific human-tagged examples. Bootstrapping systems significantly reduce the number of tr...
Jun Zhu, Zaiqing Nie, Xiaojiang Liu, Bo Zhang, Ji-...
130
Voted
ATAL
2007
Springer
15 years 8 months ago
Batch reinforcement learning in a complex domain
Temporal difference reinforcement learning algorithms are perfectly suited to autonomous agents because they learn directly from an agent’s experience based on sequential actio...
Shivaram Kalyanakrishnan, Peter Stone