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CORR
2010
Springer
47views Education» more  CORR 2010»
13 years 3 months ago
Robustness and Generalization
We derive generalization bounds for learning algorithms based on their robustness: the property that if a testing sample is "similar" to a training sample, then the test...
Huan Xu, Shie Mannor
SDM
2007
SIAM
81views Data Mining» more  SDM 2007»
13 years 5 months ago
A PAC Bound for Approximate Support Vector Machines
We study a class of algorithms that speed up the training process of support vector machines (SVMs) by returning an approximate SVM. We focus on algorithms that reduce the size of...
Dongwei Cao, Daniel Boley
NIPS
2007
13 years 5 months ago
Stability Bounds for Non-i.i.d. Processes
The notion of algorithmic stability has been used effectively in the past to derive tight generalization bounds. A key advantage of these bounds is that they are designed for spec...
Mehryar Mohri, Afshin Rostamizadeh
NIPS
2008
13 years 5 months ago
On the Complexity of Linear Prediction: Risk Bounds, Margin Bounds, and Regularization
This work characterizes the generalization ability of algorithms whose predictions are linear in the input vector. To this end, we provide sharp bounds for Rademacher and Gaussian...
Sham M. Kakade, Karthik Sridharan, Ambuj Tewari
ICML
2002
IEEE
14 years 4 months ago
On generalization bounds, projection profile, and margin distribution
We study generalization properties of linear learning algorithms and develop a data dependent approach that is used to derive generalization bounds that depend on the margin distr...
Ashutosh Garg, Sariel Har-Peled, Dan Roth
ECCV
2002
Springer
14 years 5 months ago
A Tale of Two Classifiers: SNoW vs. SVM in Visual Recognition
Numerous statistical learning methods have been developed for visual recognition tasks. Few attempts, however, have been made to address theoretical issues, and in particular, stud...
Ming-Hsuan Yang, Dan Roth, Narendra Ahuja