Results 1  10
of
144,778
Maxmargin Markov networks
, 2003
"... In typical classification tasks, we seek a function which assigns a label to a single object. Kernelbased approaches, such as support vector machines (SVMs), which maximize the margin of confidence of the classifier, are the method of choice for many such tasks. Their popularity stems both from the ..."
Abstract

Cited by 594 (15 self)
 Add to MetaCart
In typical classification tasks, we seek a function which assigns a label to a single object. Kernelbased approaches, such as support vector machines (SVMs), which maximize the margin of confidence of the classifier, are the method of choice for many such tasks. Their popularity stems both from
Maxmargin parsing
 In Proceedings of EMNLP
, 2004
"... We present a novel discriminative approach to parsing inspired by the largemargin criterion underlying support vector machines. Our formulation uses a factorization analogous to the standard dynamic programs for parsing. In particular, it allows one to efficiently learn a model which discriminates ..."
Abstract

Cited by 158 (24 self)
 Add to MetaCart
We present a novel discriminative approach to parsing inspired by the largemargin criterion underlying support vector machines. Our formulation uses a factorization analogous to the standard dynamic programs for parsing. In particular, it allows one to efficiently learn a model which discriminates
Large Scale MaxMargin MultiLabel Classification with Priors
"... We propose a maxmargin formulation for the multilabel classification problem where the goal is to tag a data point with a set of prespecified labels. Given a set of L labels, a data point can be tagged with any of the 2 L possible subsets. The main challenge therefore lies in optimising over this ..."
Abstract

Cited by 40 (2 self)
 Add to MetaCart
We propose a maxmargin formulation for the multilabel classification problem where the goal is to tag a data point with a set of prespecified labels. Given a set of L labels, a data point can be tagged with any of the 2 L possible subsets. The main challenge therefore lies in optimising over
Efficient MaxMargin MultiLabel Classification with . . .
 MACH LEARN
"... The goal in multilabel classification is to tag a data point with the subset of relevant labels from a prespecified set. Given a set of L labels, a data point can be tagged with any of the 2 L possible subsets. The main challenge therefore lies in optimisingover thisexponentially largelabel space ..."
Abstract

Cited by 1 (0 self)
 Add to MetaCart
be significantly different fromthose onthe testset. We propose a maxmargin formulation where we model prior label correlations but do not incorporate pairwise label interaction terms in the prediction function. We show that the problem complexity can be reduced from exponential to linear while modelling dense
MaxMargin Ratio Machine
"... In this paper, we investigate the problem of exploiting global information to improve the performance of SVMs on large scale classification problems. We first present a unified general framework for the existing minmax machine methods in terms of withinclass dispersions and betweenclass dispersi ..."
Abstract
 Add to MetaCart
class dispersions. By defining a new withinclass dispersion measure, we then propose a novel maxmargin ratio machine (MMRM) method that can be formulated as a linear programming problem with scalability for large data sets. Kernels can be easily incorporated into our method to address nonlinear classification
MaxMargin Markov Networks
"... Abstract In typical classification tasks, we seek a function which assigns a label to a single object. Kernelbased approaches, such as support vector machines (SVMs), ..."
Abstract
 Add to MetaCart
Abstract In typical classification tasks, we seek a function which assigns a label to a single object. Kernelbased approaches, such as support vector machines (SVMs),
MaxMargin Additive Classifiers for Detection
 ICCV
"... We present methods for training high quality object detectors very quickly. The core contribution is a pair of fast training algorithms for piecewise linear classifiers, which can approximate arbitrary additive models. The classifiers are trained in a maxmargin framework and significantly outperfo ..."
Abstract

Cited by 60 (5 self)
 Add to MetaCart
We present methods for training high quality object detectors very quickly. The core contribution is a pair of fast training algorithms for piecewise linear classifiers, which can approximate arbitrary additive models. The classifiers are trained in a maxmargin framework and significantly
Efficient MaxMargin MultiLabel Classification with Applications to ZeroShot Learning
 MACH LEARN
, 2010
"... The goal in multilabel classification is to tag a data point with the subset of relevant labels from a prespecified set. Given a set of L labels, a data point can be tagged with any of the 2 L possible subsets. The main challenge therefore lies in optimising over this exponentially large label spa ..."
Abstract

Cited by 12 (2 self)
 Add to MetaCart
be significantly different from those on the test set. We propose a maxmargin formulation where we model prior label correlations but do not incorporate pairwise label interaction terms in the prediction function. We show that the problem complexity can be reduced from exponential to linear while modelling dense
Maxmargin classification of incomplete data
 Advances in Neural Information Processing Systems 19
, 2007
"... We consider the problem of learning classifiers for structurally incomplete data, where some objects have a subset of features inherently absent due to complex relationships between the features. The common approach for handling missing features is to begin with a preprocessing phase that completes ..."
Abstract

Cited by 11 (0 self)
 Add to MetaCart
the missing features, and then use a standard classification procedure. In this paper we show how incomplete data can be classified directly without any completion of the missing features using a maxmargin learning framework. We formulate this task using a geometricallyinspired objective, and discuss two
Results 1  10
of
144,778