no code implementations • 28 Jun 2016 • Bo Tang, Haibo He
A Relative Density-based Outlier Score (RDOS) is introduced to measure the local outlierness of objects, in which the density distribution at the location of an object is estimated with a local KDE method based on extended nearest neighbors of the object.
no code implementations • 21 Jun 2016 • Bo Tang, Paul M. Baggenstoss, Haibo He
The recognition diversity indicates that a hybrid combination of the proposed generative classifier and the discriminative classifier could further improve the classification performance.
no code implementations • 20 Jun 2016 • Bo Tang, Haibo He
In this paper, we present a new wrapper feature selection approach based on Jensen-Shannon (JS) divergence, termed feature selection with maximum JS-divergence (FSMJ), for text categorization.
no code implementations • 11 May 2016 • Bo Tang, Steven Kay, Haibo He, Paul M. Baggenstoss
In this letter, we present a novel exponentially embedded families (EEF) based classification method, in which the probability density function (PDF) on raw data is estimated from the PDF on features.
no code implementations • 9 Feb 2016 • Bo Tang, Steven Kay, Haibo He
Based on the JMH-divergence, we develop two efficient feature selection methods, termed maximum discrimination ($MD$) and $MD-\chi^2$ methods, for text categorization.
no code implementations • 19 Sep 2014 • Jin Xu, Haibo He, Hong Man
The classification accuracy and reconstruction error are used to evaluate the proposed dictionary learning method.
no code implementations • 28 Oct 2018 • Hao-Hsuan Chang, Hao Song, Yang Yi, Jianzhong Zhang, Haibo He, Lingjia Liu
To be specific, we apply the powerful machine learning tool, deep reinforcement learning (DRL), for SUs to learn "appropriate" spectrum access strategies in a distributed fashion assuming NO knowledge of the underlying system statistics.
no code implementations • 22 Dec 2018 • Hong Huang, Guangyao Shi, Haibo He, Yule Duan, Fulin Luo
However, a major challenge of GE is how to choose proper neighbors for graph construction and explore the spatial information of HSI data.
no code implementations • 8 Apr 2019 • Jia Liu, Maoguo Gong, Haibo He
In this paper, we propose a nucleus neural network (NNN) and corresponding connecting architecture learning method.
no code implementations • 15 Oct 2020 • Hepeng Li, Haibo He
By making a series of approximations to the consensus optimization model, we propose a decentralized MARL algorithm, which we call multi-agent TRPO (MATRPO).
no code implementations • 3 Dec 2021 • Hepeng Li, Nicholas Clavette, Haibo He
We present an analytical policy update rule that is independent of parametric function approximators.