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CVPR
2008
IEEE
14 years 7 months ago
Least squares congealing for unsupervised alignment of images
In this paper, we present an approach we refer to as "least squares congealing" which provides a solution to the problem of aligning an ensemble of images in an unsuperv...
Mark Cox, Sridha Sridharan, Simon Lucey, Jeffrey F...
ICML
1999
IEEE
14 years 5 months ago
Least-Squares Temporal Difference Learning
Excerpted from: Boyan, Justin. Learning Evaluation Functions for Global Optimization. Ph.D. thesis, Carnegie Mellon University, August 1998. (Available as Technical Report CMU-CS-...
Justin A. Boyan
CLUSTER
2006
IEEE
13 years 11 months ago
A Parallel Algorithm for the Solution of the Deconvolution Problem on Heterogeneous Networks
In this work we present a parallel algorithm for the solution of a least squares problem with structured matrices. This problem arises in many applications mainly related to digit...
Pedro Alonso, Antonio M. Vidal, Alexey L. Lastovet...
JMLR
2010
121views more  JMLR 2010»
12 years 11 months ago
Sparse Semi-supervised Learning Using Conjugate Functions
In this paper, we propose a general framework for sparse semi-supervised learning, which concerns using a small portion of unlabeled data and a few labeled data to represent targe...
Shiliang Sun, John Shawe-Taylor
SAC
2009
ACM
13 years 11 months ago
Online annotation and prediction for regime switching data streams
Regime switching models, in which the state of the world is locally stationary, are a useful abstraction for many continuous valued data streams. In this paper we develop an onlin...
Gordon J. Ross, Dimitris K. Tasoulis, Niall M. Ada...