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ICML
2000
IEEE
16 years 7 months ago
Maximum Entropy Markov Models for Information Extraction and Segmentation
Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech t...
Andrew McCallum, Dayne Freitag, Fernando C. N. Per...
COLT
2007
Springer
16 years 20 days ago
Online Learning with Prior Knowledge
The standard so-called experts algorithms are methods for utilizing a given set of “experts” to make good choices in a sequential decision-making problem. In the standard setti...
Elad Hazan, Nimrod Megiddo
ICCAD
1997
IEEE
126views Hardware» more  ICCAD 1997»
15 years 10 months ago
An output encoding problem and a solution technique
We present a new output encoding problem as follows: Given a specification table, such as a truth table or a finite state machine state table, where some of the outputs are specif...
Subhasish Mitra, LaNae J. Avra, Edward J. McCluske...
COLT
1995
Springer
15 years 10 months ago
Exactly Learning Automata with Small Cover Time
We present algorithms for exactly learning unknown environments that can be described by deterministic nite automata. The learner performs a walk on the target automaton, where at...
Dana Ron, Ronitt Rubinfeld
ENTCS
2007
174views more  ENTCS 2007»
15 years 6 months ago
Quantum Patterns and Types for Entanglement and Separability
As a first step toward a notion of quantum data structures, we introduce a typing system for reflecting entanglement and separability. This is presented in the context of classi...
Simon Perdrix