Many learning algorithms rely on the curvature (in particular, strong convexity) of regularized objective functions to provide good theoretical performance guarantees. In practice...
Given observed data and a collection of parameterized candidate models, a 1- confidence region in parameter space provides useful insight as to those models which are a good fit t...
Brent Bryan, H. Brendan McMahan, Chad M. Schafer, ...
Central and subspace clustering methods are at the core of many segmentation problems in computer vision. However, both methods fail to give the correct segmentation in many pract...
String kernels which compare the set of all common substrings between two given strings have recently been proposed by Vishwanathan & Smola (2004). Surprisingly, these kernels...
Capturing the context of a user's query from the previous queries and clicks in the same session may help understand the user's information need. A context-aware approac...