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» On the Relative Sizes of Learnable Sets
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STOC
2000
ACM
174views Algorithms» more  STOC 2000»
13 years 11 months ago
Noise-tolerant learning, the parity problem, and the statistical query model
We describe a slightly subexponential time algorithm for learning parity functions in the presence of random classification noise, a problem closely related to several cryptograph...
Avrim Blum, Adam Kalai, Hal Wasserman
CIE
2011
Springer
12 years 7 months ago
Automatic Learners with Feedback Queries
Automatic classes are classes of languages for which a finite automaton can decide whether a given element is in a set given by its index. The present work studies the learnabilit...
John Case, Sanjay Jain, Yuh Shin Ong, Pavel Semukh...
FOCS
2008
IEEE
14 years 1 months ago
What Can We Learn Privately?
Learning problems form an important category of computational tasks that generalizes many of the computations researchers apply to large real-life data sets. We ask: what concept ...
Shiva Prasad Kasiviswanathan, Homin K. Lee, Kobbi ...
APPROX
2010
Springer
168views Algorithms» more  APPROX 2010»
13 years 9 months ago
Differential Privacy and the Fat-Shattering Dimension of Linear Queries
In this paper, we consider the task of answering linear queries under the constraint of differential privacy. This is a general and well-studied class of queries that captures oth...
Aaron Roth
ALGORITHMICA
2006
161views more  ALGORITHMICA 2006»
13 years 7 months ago
The Expected Size of the Rule k Dominating Set
Dai, Li, and Wu proposed Rule k, a localized approximation algorithm that attempts to find a small connected dominating set in a graph. In this paper we consider the "average...
Jennie C. Hansen, Eric Schmutz, Li Sheng