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ICML
2005
IEEE
14 years 8 months ago
Active learning for Hidden Markov Models: objective functions and algorithms
Hidden Markov Models (HMMs) model sequential data in many fields such as text/speech processing and biosignal analysis. Active learning algorithms learn faster and/or better by cl...
Brigham Anderson, Andrew Moore
MOC
2002
131views more  MOC 2002»
13 years 7 months ago
Some baby-step giant-step algorithms for the low hamming weight discrete logarithm problem
In this paper, we present several baby-step giant-step algorithms for the low hamming weight discrete logarithm problem. In this version of the discrete log problem, we are require...
Douglas R. Stinson
SIGMOD
2010
ACM
154views Database» more  SIGMOD 2010»
13 years 7 months ago
Unbiased estimation of size and other aggregates over hidden web databases
Many websites provide restrictive form-like interfaces which allow users to execute search queries on the underlying hidden databases. In this paper, we consider the problem of es...
Arjun Dasgupta, Xin Jin, Bradley Jewell, Nan Zhang...
ICML
2008
IEEE
14 years 8 months ago
Beam sampling for the infinite hidden Markov model
The infinite hidden Markov model is a nonparametric extension of the widely used hidden Markov model. Our paper introduces a new inference algorithm for the infinite Hidden Markov...
Jurgen Van Gael, Yunus Saatci, Yee Whye Teh, Zoubi...
FOCS
2002
IEEE
14 years 18 days ago
Learning a Hidden Matching
We consider the problem of learning a matching (i.e., a graph in which all vertices have degree 0 or 1) in a model where the only allowed operation is to query whether a set of ve...
Noga Alon, Richard Beigel, Simon Kasif, Steven Rud...