63 citations · 116 across the 10 of their papers we have counts for
10 papers
Spatial Location Constraint Prototype Loss for Open Set Recognition
Ziheng Xia, Ganggang Dong, Penghui Wang +1
One of the challenges in pattern recognition is open set recognition. Compared with closed set recognition, open set recognition needs to reduce not only the empirical risk, but al…
Adversarial Motorial Prototype Framework for Open Set Recognition
Ziheng Xia, Penghui Wang, Ganggang Dong +1
Open set recognition is designed to identify known classes and to reject unknown classes simultaneously. Specifically, identifying known classes and rejecting unknown classes corre…
Variational Temporal Deep Generative Model for Radar HRRP Target Recognition
Dandan Guo, Bo Chen, Wenchao Chen +3
We develop a recurrent gamma belief network (rGBN) for radar automatic target recognition (RATR) based on high-resolution range profile (HRRP), which characterizes the temporal dep…
Deep Autoencoding Topic Model with Scalable Hybrid Bayesian Inference
Hao Zhang, Bo Chen, Yulai Cong +3
To build a flexible and interpretable model for document analysis, we develop deep autoencoding topic model (DATM) that uses a hierarchy of gamma distributions to construct its mul…
Radar Accurate Localization of UAV Swarms Based on Range Super-Resolution Method
Tianyuan Yang, Jibin Zheng, Tao Su +1
In radar accurate localization of unmanned aerial vehicle (UAV) swarms, the high density, similar motion parameters, small radar cross-section (RCS), strong noise and far range put…
New subspace minimization conjugate gradient methods based on regularization model for unconstrained optimization
Ting Zhao, Hongwei Liu, Zexian Liu
In this paper, two new subspace minimization conjugate gradient methods based on regularization models are proposed, where a special scaled norm in regularization model…
An Improved Gradient Method with Approximately Optimal Stepsize Based on Conic model for Unconstrained Optimization
Zexian Liu, Hongwei Liu
A new type of stepsize, which was recently introduced by Liu and Liu (Optimization, 67(3), 427-440, 2018), is called approximately optimal stepsize and is quit efficient for gradie…
Optimal Estimation of Sensor Biases for Asynchronous Multi-Sensor Data Fusion
Wenqiang Pu, Ya-Feng Liu, Junkun Yan +2
An important step in a multi-sensor surveillance system is to estimate sensor biases from their noisy asynchronous measurements. This estimation problem is computationally challeng…
Deep Latent Dirichlet Allocation with Topic-Layer-Adaptive Stochastic Gradient Riemannian MCMC
Yulai Cong, Bo Chen, Hongwei Liu +1
It is challenging to develop stochastic gradient based scalable inference for deep discrete latent variable models (LVMs), due to the difficulties in not only computing the gradien…
An Efficient Inexact Newton-CG Algorithm for the Smallest Enclosing Ball Problem of Large Dimensions
Ya-Feng Liu, Rui Diao, Feng Ye +1
In this paper, we consider the problem of computing the smallest enclosing ball (SEB) of a set of balls in where the product is large. We first approximate…