[PDF] Top 20 Learning Latent Tree Graphical Models

... of learning a latent tree graphical model where samples are available only from a subset of ...for learning minimal latent trees, that is, trees without any redundant hidden ... See full document

... Discussion Perhaps the most intriguing question here is why semi-supervised learning could im- prove semantic parsing performance. While the underlying theoretical exposition still remains an active research ... See full document

... diately intelligible at the semantic level and corre- spond closely to the lexical-semantic classes found in Levin (1993). For example, clusters 1, 6, and 14 include member verbs of Levin’s SAY, PEER and AMUSE classes, ... See full document

... using graphical models instead of recursive ...existing latent tree-based models treat all in- put words equally as leaf nodes and ignore the fact that dif- ferent words make varying ... See full document

... in graphical models is often solved via message-passing algo- rithms, such as the junction-tree algorithm or loopy ...many models have maximal cliques that are larger than their constituent ... See full document

... robust learning scheme that knows when to activate what feature is ...feature learning subtasks (Haghighi et ...joint learning has demonstrated that such an approach can suffer from cascaded errors ... See full document

... theoretical models from the literature and to the out- puts of four state-of-the-art learning ...for learning MIM models, we did not use it for the other data ...for learning HLC ... See full document

... The learning curves are showed on Fig- ure 3. We present the models with 10, 20, 50, 100, 200, 500, and 1000 ...ity models were not possible to create because of the very high computational ... See full document

... other latent tree ...single tree is selected during forward evaluation, but the train- ing signal can still propagate to every path during ... See full document

... B AGEL uses a stack-based semantic representa- tion to constrain the sequence of semantic con- cepts to be searched. This representation can be seen as a linearised semantic tree similar to the one previously used ... See full document

... The ListOps dataset probes the syntax learning ability of latent tree models (Nangia and Bow- man, 2018). It is designed to have a single cor- rect parsing strategy that a model must learn in ... See full document

... Bayesian learning (Wallace, 1990; Hinton and van Camp, 1993; Neal and Hinton, 1999; Waterhouse et ...Bayesian learning was first employed in supervised problems (Wallace, 1990; Hinton and van Camp, 1993; ... See full document

... Latent tree learning models learn to parse a sentence without syntactic supervision, and use that parse to build the sentence representa- ...such models has shown that, while they ... See full document

... If the topic-based representations of documents are to be used for document clustering or classi- fication, providing z-labels for words can be seen as similar to semi-supervised learning with labeled features ... See full document

... unsupervised learning prob- lems and their subsequent PAC-Bayesian analysis can also be applied to weighted graph clustering (and, consequently, to pairwise clustering, which can be regarded as clustering of a ... See full document

... generative models used in practice are very simplistic models of the underlying phenomena; for example, the syntactic struc- ture of language or the language translation ...the latent variables, ... See full document

... α-stable graphical (α-SG) models, a class of multivariate stable densities that can also be represented as Bayesian networks whose edges encode linear dependencies between random ...based learning ... See full document

... independent of all other edges. We propose a general framework to accommodate more realistic networks with hub nodes, using a convex formulation that involves a row-column overlap norm penalty. We apply this general ... See full document

... In this chapter, we show how a decomposable triangulated graph can be transformed into a junction tree such that max-propagation developed for graphical models can be used to the labelin[r] ... See full document

... The three articles cited above are similar to our method in that they use decision-theoretic models to examine a strategic problem from the perspective of each opponent. Our research differs in that we seek a Nash ... See full document