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ICML
2007
IEEE
10 years 6 months ago
Spectral feature selection for supervised and unsupervised learning
Feature selection aims to reduce dimensionality for building comprehensible learning models with good generalization performance. Feature selection algorithms are largely studied ...
Zheng Zhao, Huan Liu
ICML
2007
IEEE
10 years 6 months ago
Map building without localization by dimensionality reduction techniques
This paper proposes a new map building framework for mobile robot named Localization-Free Mapping by Dimensionality Reduction (LFMDR). In this framework, the robot map building is...
Takehisa Yairi
ICML
2007
IEEE
10 years 6 months ago
Self-taught learning: transfer learning from unlabeled data
We present a new machine learning framework called "self-taught learning" for using unlabeled data in supervised classification tasks. We do not assume that the unlabele...
Rajat Raina, Alexis Battle, Honglak Lee, Benjamin ...
ICML
2007
IEEE
10 years 6 months ago
A recursive method for discriminative mixture learning
We consider the problem of learning density mixture models for classification. Traditional learning of mixtures for density estimation focuses on models that correctly represent t...
Minyoung Kim, Vladimir Pavlovic
ICML
2007
IEEE
10 years 6 months ago
Supervised clustering of streaming data for email batch detection
We address the problem of detecting batches of emails that have been created according to the same template. This problem is motivated by the desire to filter spam more effectivel...
Peter Haider, Ulf Brefeld, Tobias Scheffer
ICML
2007
IEEE
10 years 6 months ago
The rendezvous algorithm: multiclass semi-supervised learning with Markov random walks
We consider the problem of multiclass classification where both labeled and unlabeled data points are given. We introduce and demonstrate a new approach for estimating a distribut...
Arik Azran
ICML
2007
IEEE
10 years 6 months ago
A bound on the label complexity of agnostic active learning
We study the label complexity of pool-based active learning in the agnostic PAC model. Specifically, we derive general bounds on the number of label requests made by the A2 algori...
Steve Hanneke
ICML
2007
IEEE
10 years 6 months ago
Simpler core vector machines with enclosing balls
The core vector machine (CVM) is a recent approach for scaling up kernel methods based on the notion of minimum enclosing ball (MEB). Though conceptually simple, an efficient impl...
András Kocsor, Ivor W. Tsang, James T. Kwok
ICML
2007
IEEE
10 years 6 months ago
Focused crawling with scalable ordinal regression solvers
In this paper we propose a novel, scalable, clustering based Ordinal Regression formulation, which is an instance of a Second Order Cone Program (SOCP) with one Second Order Cone ...
Rashmin Babaria, J. Saketha Nath, S. Krishnan, K. ...
ICML
2007
IEEE
10 years 6 months ago
Quadratically gated mixture of experts for incomplete data classification
We introduce quadratically gated mixture of experts (QGME), a statistical model for multi-class nonlinear classification. The QGME is formulated in the setting of incomplete data,...
Xuejun Liao, Hui Li, Lawrence Carin
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