distance metric learning
Hamming Distance Metric Learning
... One problem with such loss functions is that finding a suitable threshold ρ with cross-validation is slow. Furthermore, for many problems one cares more about the relative magnitudes of pairwise distances than their ...
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Distance metric learning : a two-phase approach
... Abstract. Distance metric learning has been successfully incorporated in many machine learning ...than learning a full Mahalanobis matrix in one phase as is commonly ...
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Distance Metric Learning for Aspect Phrase Grouping
... We studied distance metric learning for aspect phrase grouping, exploring a novel deep neural network framework. By leveraging semantic relations between aspect phrase and their contexts, our ...
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Semi-supervised distance metric learning for collaborative image retrieval
... semi-supervised distance metric learning scheme for collaborative image retrieval, in which real log data of user relevance feedback were analyzed to discover useful information and infer optimal ...
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Online multimodal distance metric learning with application to image retrieval
... on distance metric learning (DML) for improving similarity search in multimedia in- formation retrieval ...linear distance function on the input feature space, in which the assumption of ...
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Semi-supervised distance metric learning for collaborative image retrieval
... semi-supervised distance metric learning scheme for collaborative image retrieval, in which real log data of user relevance feedback were analyzed to discover useful information and infer optimal ...
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Distance Metric Learning for Large Margin Nearest Neighbor Classification
... Mahalanobis distance metric for kNN ...by learning a linear transformation of the input space that precedes kNN classification using Euclidean ...of distance metric learning as a ...
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Multiple Kernel Learning via Distance Metric Learning for Interactive Image Retrieval
... the distance metrics are learnt from a fixed training set and applied universally ignoring the locations of a sample in the base feature ...localised learning may be advantageous over global learning ...
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Online multi-modal distance metric learning with application to image retrieval
... or learning effective distance/similarity measures based on some extracted low-level ...machine learning techniques to automatically combine multiple types of diverse features and their respective ...
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Semi-supervised distance metric learning for collaborative image retrieval and clustering
... semi-supervised distance metric learning for solving collaborative image retrieval and clustering, where the real log data of user relevance feed- back are analyzed to discover useful information and ...
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Weakly Supervised Scene Parsing with Point-Based Distance Metric Learning
... Point-based Distance Metric Learning (PDML) in this ...simple distance metric loss, which collaborates with the point-wise cross-entropy loss to opti- mize the deep neural ...
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Online multi-modal distance metric learning with application to image retrieval
... or learning effective distance/similarity measures based on some extracted low-level ...machine learning techniques to automatically combine multiple types of diverse features and their respective ...
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Bayesian distance metric learning and its application in automatic speaker recognition systems
... Bayesian distance metric learning on the short2-short3 condition of the NIST 2008 SRE ...Bayesian distance metric learning algorithm is referred to as \Bayes dml, cosine score ...
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Bayesian distance metric learning and its application in automatic speaker recognition systems
... Bayesian distance metric learning on the short2-short3 condition of the NIST 2008 SRE ...Bayesian distance metric learning algorithm is referred to as \Bayes dml, cosine score ...
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Person Re Identification Over Camera Gridsby Multi Task Distance Metric Learning
... a distance metric learning or learning-to rank ...learned distance or likeness measure between the query image and each candidate image is totaled in order to govern which pair is the ...
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Semi Supervised Nonlinear Distance Metric Learning Via Random Forest and Relative Similarity Algorithm
... to distance metric learning. Metric learning is the task of learning a distance function over ...machine learning method is implemented by using Semi-Supervised ...
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A Boosting Framework for Visuality-Preserving Distance Metric Learning and Its Application to Medical Image Retrieval
... for distance metric learning typically address only one goal without consideration of the ...Hence, learning a distance metric that preserves both visual resemblance and semantic ...
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Distance Metric Learning with Eigenvalue Optimization
... to learning a Mahalanobis metric for k-nearest neigh- bor (k-NN) ...to metric learning for semi-supervised k-means ...to metric learning, we will develop novel approximate ...
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Distance metric learning for medical image registration
... f : R d → R n such that for all points x, y the following holds: (1 − )||x − y|| 2 ≤ ||f (x) − f (y)|| 2 ≤ (1 + )||x + y|| 2 . (4.9) Dimensionality reductions may be a fundamental step in medical image registration. ...
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Distance Metric Learning for Conditional Anomaly Detection
... the distance metric that lets us iden- tify examples in the dataset that are most critical for de- tecting the ...study metric learning ...our metric learning methods show an ...
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