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Local features are not lonely – Laplacian sparse coding for image classification
TLDR
We propose to use histogram intersection based kNN method to construct a Laplacian matrix, which can well characterize the similarity of local features. Expand
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Deep Convolutional Neural Network Based Regression Approach for Estimation of Remaining Useful Life
TLDR
A novel deep Convolutional Neural Network (CNN) based regression approach for estimating the RUL is proposed in this paper. Expand
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Online AUC Maximization
TLDR
We address this challenge by exploiting the reservoir sampling technique, and present two algorithms for online AUC maximization with theoretic performance guarantee. Expand
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Neighborhood Regularized Logistic Matrix Factorization for Drug-Target Interaction Prediction
TLDR
We propose a novel drug-target interaction prediction algorithm, namely neighborhood regularized logistic matrix factorization (NRLMF). Expand
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Online Feature Selection and Its Applications
TLDR
We investigate the problem of online feature selection (OFS) in which an online learner is only allowed to maintain a classifier involved only a small and fixed number of features. Expand
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Stochastic Optimization with Importance Sampling for Regularized Loss Minimization
TLDR
Uniform sampling of training data has been commonly used in traditional stochastic optimization algorithms such as Proximal Stochastic Mirror Descent (prox-SMD) and prox-SDCA. Expand
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PAMR: Passive aggressive mean reversion strategy for portfolio selection
TLDR
This article proposes a novel online portfolio selection strategy named “Passive Aggressive Mean Reversion” (PAMR). Expand
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Large Scale Online Kernel Learning
TLDR
We present a new framework for large scale online kernel learning, making kernel methods efficient and scalable for large-scale online learning applications. Expand
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Stochastic Optimization with Importance Sampling
TLDR
In this paper we study stochastic optimization with importance sampling, which improves the convergence rate for prox-SGD and prox-SDCA. Expand
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LIBOL: a library for online learning algorithms
TLDR
LIBOL is an open-source library for large-scale online learning, which consists of a large family of efficient and scalable state-of-the-art online learning algorithms for largescale online classification tasks. Expand
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