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» Learning the Structure of Linear Latent Variable Models
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NIPS
1998
13 years 10 months ago
Learning from Dyadic Data
Dyadic data refers to a domain with two nite sets of objects in which observations are made for dyads, i.e., pairs with one element from either set. This type of data arises natur...
Thomas Hofmann, Jan Puzicha, Michael I. Jordan
ICML
2008
IEEE
14 years 9 months ago
Bolasso: model consistent Lasso estimation through the bootstrap
We consider the least-square linear regression problem with regularization by the 1-norm, a problem usually referred to as the Lasso. In this paper, we present a detailed asymptot...
Francis R. Bach
ICCV
2011
IEEE
12 years 9 months ago
Discriminative Figure-Centric Models for Joint Action Localization and Recognition
In this paper we develop an algorithm for action recognition and localization in videos. The algorithm uses a figurecentric visual word representation. Different from previous ap...
Tian Lan, Yang Wang, Greg Mori
JMLR
2010
192views more  JMLR 2010»
13 years 3 months ago
Inducing Tree-Substitution Grammars
Inducing a grammar from text has proven to be a notoriously challenging learning task despite decades of research. The primary reason for its difficulty is that in order to induce...
Trevor Cohn, Phil Blunsom, Sharon Goldwater
JMLR
2008
144views more  JMLR 2008»
13 years 8 months ago
Search for Additive Nonlinear Time Series Causal Models
Pointwise consistent, feasible procedures for estimating contemporaneous linear causal structure from time series data have been developed using multiple conditional independence ...
Tianjiao Chu, Clark Glymour