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» Evaluating learning algorithms and classifiers
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ISSTA
2007
ACM
13 years 10 months ago
Instrumenting where it hurts: an automatic concurrent debugging technique
As concurrent and distributive applications are becoming more common and debugging such applications is very difficult, practical tools for automatic debugging of concurrent appl...
Rachel Tzoref, Shmuel Ur, Elad Yom-Tov
BMCBI
2010
102views more  BMCBI 2010»
13 years 8 months ago
Peptide binding predictions for HLA DR, DP and DQ molecules
Background: MHC class II binding predictions are widely used to identify epitope candidates in infectious agents, allergens, cancer and autoantigens. The vast majority of predicti...
Peng Wang, John Sidney, Yohan Kim, Alessandro Sett...
CORR
2004
Springer
103views Education» more  CORR 2004»
13 years 8 months ago
Online convex optimization in the bandit setting: gradient descent without a gradient
We study a general online convex optimization problem. We have a convex set S and an unknown sequence of cost functions c1, c2, . . . , and in each period, we choose a feasible po...
Abraham Flaxman, Adam Tauman Kalai, H. Brendan McM...
KDD
2010
ACM
272views Data Mining» more  KDD 2010»
13 years 7 months ago
Scalable similarity search with optimized kernel hashing
Scalable similarity search is the core of many large scale learning or data mining applications. Recently, many research results demonstrate that one promising approach is creatin...
Junfeng He, Wei Liu, Shih-Fu Chang
ICDE
2010
IEEE
263views Database» more  ICDE 2010»
14 years 8 months ago
Managing Uncertainty of XML Schema Matching
Abstract-- Despite of advances in machine learning technologies, a schema matching result between two database schemas (e.g., those derived from COMA++) is likely to be imprecise. ...
Reynold Cheng, Jian Gong, David W. Cheung