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CORR
2011
Springer
193views Education» more  CORR 2011»
13 years 15 days ago
The Rate of Convergence of AdaBoost
The AdaBoost algorithm was designed to combine many “weak” hypotheses that perform slightly better than random guessing into a “strong” hypothesis that has very low error....
Indraneel Mukherjee, Cynthia Rudin, Robert E. Scha...
PODC
2011
ACM
12 years 11 months ago
MIS on trees
A maximal independent set on a graph is an inclusion-maximal set of mutually non-adjacent nodes. This basic symmetry breaking structure is vital for many distributed algorithms, w...
Christoph Lenzen, Roger Wattenhofer
IVC
2008
141views more  IVC 2008»
13 years 8 months ago
Segmentation of color images via reversible jump MCMC sampling
Reversible jump Markov chain Monte Carlo (RJMCMC) is a recent method which makes it possible to construct reversible Markov chain samplers that jump between parameter subspaces of...
Zoltan Kato
AAAI
2011
12 years 8 months ago
Quantity Makes Quality: Learning with Partial Views
In many real world applications, the number of examples to learn from is plentiful, but we can only obtain limited information on each individual example. We study the possibiliti...
Nicolò Cesa-Bianchi, Shai Shalev-Shwartz, O...
IACR
2011
92views more  IACR 2011»
12 years 8 months ago
From Non-Adaptive to Adaptive Pseudorandom Functions
Unlike the standard notion of pseudorandom functions (PRF), a non-adaptive PRF is only required to be indistinguishable from random in the eyes of a non-adaptive distinguisher (i....
Iftach Haitner, Itay Berman