27 search results - page 3 / 6 » Graph Kernels and Gaussian Processes for Relational Reinforc... |
NIPS
2008
13 years 6 months ago
2008
In kernel-based regression learning, optimizing each kernel individually is useful when the data density, curvature of regression surfaces (or decision boundaries) or magnitude of...
SDM
2012
SIAM
11 years 7 months ago
2012
SIAM
We propose a new matrix completion algorithm— Kernelized Probabilistic Matrix Factorization (KPMF), which effectively incorporates external side information into the matrix fac...
IROS
2007
IEEE
13 years 11 months ago
2007
IEEE
— In this paper, we present an approach that applies the reinforcement learning principle to the problem of learning height control policies for aerial blimps. In contrast to pre...
NIPS
2008
13 years 6 months ago
2008
Stochastic relational models (SRMs) [15] provide a rich family of choices for learning and predicting dyadic data between two sets of entities. The models generalize matrix factor...
IJCV
2007
13 years 5 months ago
2007
We derive a family of kernels on dynamical systems by applying the Binet-Cauchy theorem to trajectories of states. Our derivation provides a unifying framework for all kernels on d...