172 search results - page 15 / 35 » Scaling up Analogical Learning |
CICC
2011
12 years 7 months ago
2011
Efforts to achieve the long-standing dream of realizing scalable learning algorithms for networks of spiking neurons in silicon have been hampered by (a) the limited scalability of...
ATAL
2009
Springer
14 years 2 months ago
2009
Springer
Improving the sample efficiency of reinforcement learning algorithms to scale up to larger and more realistic domains is a current research challenge in machine learning. Model-ba...
ICML
2002
IEEE
14 years 8 months ago
2002
IEEE
One of the central challenges in reinforcement learning is to balance the exploration/exploitation tradeoff while scaling up to large problems. Although model-based reinforcement ...
DAC
2007
ACM
14 years 9 months ago
2007
ACM
The number and magnitude of process variation sources are increasing as we scale further into the nano regime. Today's most successful response surface methods limit us to lo...
CORR
2007
Springer
13 years 7 months ago
2007
Springer
Higher-order tensor decompositions are analogous to the familiar Singular Value Decomposition (SVD), but they transcend the limitations of matrices (second-order tensors). SVD is ...