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Logistic Regression and Boosting for Labeled Bags of Instances
TLDR
In this paper we upgrade linear logistic regression and boosting to multi-instance data, where each example consists of a labeled bag of instances. Expand
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Kernel-Based Least Squares Policy Iteration for Reinforcement Learning
TLDR
We present a kernel-based least squares policy iteration (KLSPI) algorithm for reinforcement learning (RL) in large or continuous state spaces, which can be used to realize adaptive feedback control of uncertain dynamic systems. Expand
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Mining top-K covering rule groups for gene expression data
TLDR
In this paper, we propose a novel algorithm to discover the top-k covering rule groups for each row of gene expression profiles. Expand
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Beyond random walk and metropolis-hastings samplers: why you should not backtrack for unbiased graph sampling
TLDR
In this paper, we propose non-backtracking random walk with re-weighting (NBRW-rw) and MH algorithm with delayed acceptance (MHDA) which are theoretically guaranteed to achieve, at almost no additional cost, not only unbiased graph sampling but also higher efficiency (smaller asymptotic variance of the resulting unbiased estimators) than the SRW and the MH algorithm, respectively. Expand
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A Secure and Efficient Authentication and Key Agreement Scheme Based on ECC for Telecare Medicine Information Systems
TLDR
In this paper, based on the elliptic curve cryptography, we propose a secure and efficient two-factor mutual authentication and key agreement scheme to reduce the computational cost in the telecare medicine information system. Expand
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FARMER: finding interesting rule groups in microarray datasets
TLDR
In this paper, we describe a new algorithm called FARMER that is specially designed to discover association rules from microarray datasets. Expand
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Multi-view learning overview: Recent progress and new challenges
TLDR
It provides comprehensive introduction for the recent developments of multi-view learning methods on the basis of coherence with early methods.It attempts to identify promising venues and point out some specific challenges. Expand
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An Adaptive Network Intrusion Detection Method Based on PCA and Support Vector Machines
TLDR
This paper proposes a novel adaptive intrusion detection method based on principal component analysis (PCA) and support vector machines (SVMs). Expand
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CURLER: finding and visualizing nonlinear correlation clusters
TLDR
In this paper, we present an algorithm for finding and visualizing nonlinear correlation clusters in the subspace of high-dimensional databases that captures both spatial proximity and cluster orientation when judging similarity between clusters. Expand
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Multimodal Gesture Recognition Based on the ResC3D Network
TLDR
We propose a multimodal gesture recognition method based on a ResC3D network, which leverages the advantages of both residual and C3D model, and a weighted frame unification scheme for blending features. Expand
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