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NAACL
2003
15 years 5 months ago
Sentence Level Discourse Parsing using Syntactic and Lexical Information
We introduce two probabilistic models that can be used to identify elementary discourse units and build sentence-level discourse parse trees. The models use syntactic and lexical ...
Radu Soricut, Daniel Marcu
128
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NIPS
2003
15 years 5 months ago
Approximability of Probability Distributions
We consider the question of how well a given distribution can be approximated with probabilistic graphical models. We introduce a new parameter, effective treewidth, that captures...
Alina Beygelzimer, Irina Rish
112
Voted
NIPS
2003
15 years 5 months ago
Online Learning of Non-stationary Sequences
We consider an online learning scenario in which the learner can make predictions on the basis of a fixed set of experts. We derive upper and lower relative loss bounds for a cla...
Claire Monteleoni, Tommi Jaakkola
NIPS
2003
15 years 5 months ago
Learning a Distance Metric from Relative Comparisons
This paper presents a method for learning a distance metric from relative comparison such as “A is closer to B than A is to C”. Taking a Support Vector Machine (SVM) approach,...
Matthew Schultz, Thorsten Joachims
NIPS
2003
15 years 5 months ago
Learning a World Model and Planning with a Self-Organizing, Dynamic Neural System
We present a connectionist architecture that can learn a model of the relations between perceptions and actions and use this model for behavior planning. State representations are...
Marc Toussaint