Spare Projections with Pairwise Constraints
نویسندگان
چکیده
منابع مشابه
Robust Locality Preserving Projections with Pairwise Constraints
Dimensionality reduction is one of the key processes of high dimensional data analysis, including machine learning and pattern recognition. Constrained Locality Preserving Projections (CLPP) is a variant of Locality Preserving Projections (LPP) plus with pairwise constraints and constraints propagation. Like LPP, however, CLPP is still sensitive to noise and parameters. To overcome these proble...
متن کاملL1 Projections with Box Constraints
We study the L1 minimization problem with additional box constraints. We motivate the problem with two different views of optimality considerations. We look into imposing such constraints in projected gradient techniques and propose a worst case linear time algorithm to perform such projections. We demonstrate the merits and effectiveness of our algorithms on synthetic as well as real experiments.
متن کاملBayesian Active Clustering with Pairwise Constraints
Clustering can be improved with pairwise constraints that specify similarities between pairs of instances. However, randomly selecting constraints could lead to the waste of labeling effort, or even degrade the clustering performance. Consequently, how to actively select effective pairwise constraints to improve clustering becomes an important problem, which is the focus of this paper. In this ...
متن کاملClustering-driven Deep Embedding with Pairwise Constraints
Recently, there has been increasing interest to leverage the competence of neural networks to analyze data. In particular, new clustering methods that employ deep embeddings have been presented. In this paper, we depart from centroid-based models and suggest a new framework, called Clustering-driven deep embedding with PAirwise Constraints (CPAC), for non-parametric clustering using a neural ne...
متن کاملDiscriminative Dictionary Learning with Pairwise Constraints
In computer vision problems such as pair matching, only binary information ‘same’ or ‘different’ label for pairs of images is given during training. This is in contrast to classification problems, where the category labels of training images are provided. We propose a unified discriminative dictionary learning approach for both pair matching and multiclass classification tasks. More specificall...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Procedia Engineering
سال: 2012
ISSN: 1877-7058
DOI: 10.1016/j.proeng.2012.01.084