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» On the Relative Sizes of Learnable Sets
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STOC
2000
ACM
174views Algorithms» more  STOC 2000»
15 years 4 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
13 years 12 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
15 years 6 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»
15 years 1 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»
14 years 12 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