104 citations · 195 across the 5 of their papers we have counts for
Showing 2014Show all
2 papers · 1 filter
cs.LG2014★ 40 cited
How to Scale Up Kernel Methods to Be As Good As Deep Neural Nets
Zhiyun Lu, Avner May, Kuan Liu +8
The computational complexity of kernel methods has often been a major barrier for applying them to large-scale learning problems. We argue that this barrier can be effectively over…
cs.CL2014★ 104 cited
A Tutorial on Dual Decomposition and Lagrangian Relaxation for Inference in Natural Language Processing
Alexander M. Rush, Michael Collins
Dual decomposition, and more generally Lagrangian relaxation, is a classical method for combinatorial optimization; it has recently been applied to several inference problems in na…