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JMLR
2010
112views more  JMLR 2010»
15 years 1 months ago
Reduced-Rank Hidden Markov Models
Hsu et al. (2009) recently proposed an efficient, accurate spectral learning algorithm for Hidden Markov Models (HMMs). In this paper we relax their assumptions and prove a tighte...
Sajid M. Siddiqi, Byron Boots, Geoffrey J. Gordon
JMLR
2010
149views more  JMLR 2010»
15 years 1 months ago
Learning Bayesian Network Structure using LP Relaxations
We propose to solve the combinatorial problem of finding the highest scoring Bayesian network structure from data. This structure learning problem can be viewed as an inference pr...
Tommi Jaakkola, David Sontag, Amir Globerson, Mari...
JMLR
2010
161views more  JMLR 2010»
15 years 1 months ago
Empirical Bernstein Boosting
Concentration inequalities that incorporate variance information (such as Bernstein's or Bennett's inequality) are often significantly tighter than counterparts (such as...
Pannagadatta K. Shivaswamy, Tony Jebara
JMLR
2010
101views more  JMLR 2010»
15 years 1 months ago
Efficient Reductions for Imitation Learning
Imitation Learning, while applied successfully on many large real-world problems, is typically addressed as a standard supervised learning problem, where it is assumed the trainin...
Stéphane Ross, Drew Bagnell
JMLR
2010
129views more  JMLR 2010»
15 years 1 months ago
Learning Polyhedral Classifiers Using Logistic Function
In this paper we propose a new algorithm for learning polyhedral classifiers. In contrast to existing methods for learning polyhedral classifier which solve a constrained optimiza...
Naresh Manwani, P. S. Sastry
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