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ML
2002
ACM
141views Machine Learning» more  ML 2002»
15 years 6 months ago
On the Existence of Linear Weak Learners and Applications to Boosting
We consider the existence of a linear weak learner for boosting algorithms. A weak learner for binary classification problems is required to achieve a weighted empirical error on t...
Shie Mannor, Ron Meir
FAST
2009
15 years 4 months ago
DIADS: Addressing the "My-Problem-or-Yours" Syndrome with Integrated SAN and Database Diagnosis
We present DIADS, an integrated DIAgnosis tool for Databases and Storage area networks (SANs). Existing diagnosis tools in this domain have a database-only (e.g., [11]) or SAN-onl...
Shivnath Babu, Nedyalko Borisov, Sandeep Uttamchan...
ICMLA
2009
15 years 4 months ago
A Syllable-Level Probabilistic Framework for Bird Species Identification
In this paper, we present new probabilistic models for identifying bird species from audio recordings. We introduce the independent syllable model and consider two ways of aggregat...
Balaji Lakshminarayanan, Raviv Raich, Xiaoli Fern
COLT
2010
Springer
15 years 4 months ago
Nonparametric Bandits with Covariates
We consider a bandit problem which involves sequential sampling from two populations (arms). Each arm produces a noisy reward realization which depends on an observable random cov...
Philippe Rigollet, Assaf Zeevi
ML
2010
ACM
138views Machine Learning» more  ML 2010»
15 years 1 months ago
Mining adversarial patterns via regularized loss minimization
Traditional classification methods assume that the training and the test data arise from the same underlying distribution. However, in several adversarial settings, the test set is...
Wei Liu, Sanjay Chawla