Search Results for author: Liang Sun

Found 26 papers, 4 papers with code

Uncertainty-Aware Task Allocation for Distributed Autonomous Robots

no code implementations21 Jul 2021 Liang Sun, Leonardo Escamilla

This paper addresses task-allocation problems with uncertainty in situational awareness for distributed autonomous robots (DARs).

Two-Stage Framework for Seasonal Time Series Forecasting

no code implementations3 Mar 2021 Qingyang Xu, Qingsong Wen, Liang Sun

By incorporating the learned long-range structure, the second stage can enhance the prediction accuracy in the forecast horizon.

Time Series Time Series Forecasting

Text-Embedded Bilinear Model for Fine-Grained Visual Recognition

no code implementations12 Oct 2020 Liang Sun, Xiang Guan, Yang Yang, Lei Zhang

Specially, we first conduct a text-embedded network to embed text feature into the discriminative image feature learning to get a embedded feature.

Fine-Grained Image Recognition Fine-Grained Visual Recognition +1

An Explainable 3D Residual Self-Attention Deep Neural Network FOR Joint Atrophy Localization and Alzheimer's Disease Diagnosis using Structural MRI

no code implementations10 Aug 2020 Xin Zhang, Liangxiu Han, Wenyong Zhu, Liang Sun, Daoqiang Zhang

Different from the existing approaches, the novelty of our approach is three-fold: 1) A Residual Self-Attention Deep Neural Network has been proposed to capture local, global and spatial information of MR images to improve diagnostic performance; 2) An explanation method using Gradient-based Localization Class Activation mapping (Grad-CAM) has been introduced to improve the explainable of the proposed method; 3) This work has provided a full end-to-end learning solution for automated disease diagnosis.


RobustPeriod: Time-Frequency Mining for Robust Multiple Periodicity Detection

1 code implementation21 Feb 2020 Qingsong Wen, Kai He, Liang Sun, Yingying Zhang, Min Ke, Huan Xu

Periodicity detection is a crucial step in time series tasks, including monitoring and forecasting of metrics in many areas, such as IoT applications and self-driving database management system.

Anomaly Detection Time Series +1

Exploring Overall Contextual Information for Image Captioning in Human-Like Cognitive Style

no code implementations ICCV 2019 Hongwei Ge, Zehang Yan, Kai Zhang, Mingde Zhao, Liang Sun

In the training process, the forward and backward LSTMs encode the succeeding and preceding words into their respective hidden states by simultaneously constructing the whole sentence in a complementary manner.

Image Captioning

Robust Gaussian Process Regression for Real-Time High Precision GPS Signal Enhancement

no code implementations3 Jun 2019 Ming Lin, Xiaomin Song, Qi Qian, Hao Li, Liang Sun, Shenghuo Zhu, Rong Jin

We validate the superiority of the proposed method in our real-time high precision positioning system against several popular state-of-the-art robust regression methods.

Multimodal Semantic Attention Network for Video Captioning

no code implementations8 May 2019 Liang Sun, Bing Li, Chunfeng Yuan, Zheng-Jun Zha, Weiming Hu

Inspired by the fact that different modalities in videos carry complementary information, we propose a Multimodal Semantic Attention Network(MSAN), which is a new encoder-decoder framework incorporating multimodal semantic attributes for video captioning.

General Classification Multi-Label Classification +1

RobustSTL: A Robust Seasonal-Trend Decomposition Algorithm for Long Time Series

1 code implementation5 Dec 2018 Qingsong Wen, Jingkun Gao, Xiaomin Song, Liang Sun, Huan Xu, Shenghuo Zhu

Based on the extracted trend, we apply the the non-local seasonal filtering to extract the seasonality component.

Anomaly Detection Time Series

Cross-Technology Communications for Heterogeneous IoT Devices Through Artificial Doppler Shifts

no code implementations27 Nov 2018 Wei Wang, Shiyue He, Liang Sun, Tao Jiang, Qian Zhang

To this end, we propose DopplerFi, a communication framework that enables a two-way communication channel between BLE and Wi-Fi by injecting artificial Doppler shifts, which can be decoded by sensing the patterns in the Gaussian frequency shift keying (GFSK) demodulator and Channel State Information (CSI).

Networking and Internet Architecture

A Many-Objective Evolutionary Algorithm With Two Interacting Processes: Cascade Clustering and Reference Point Incremental Learning

no code implementations3 Mar 2018 Hongwei Ge, Mingde Zhao, Liang Sun, Zhen Wang, Guozhen Tan, Qiang Zhang, C. L. Philip Chen

This paper proposes a many-objective optimization algorithm with two interacting processes: cascade clustering and reference point incremental learning (CLIA).

Incremental Learning

Fill it up: Exploiting partial dependency annotations in a minimum spanning tree parser

no code implementations26 Nov 2016 Liang Sun, Jason Mielens, Jason Baldridge

Unsupervised models of dependency parsing typically require large amounts of clean, unlabeled data plus gold-standard part-of-speech tags.

Dependency Parsing

Expectation-maximization for logistic regression

no code implementations31 May 2013 James G. Scott, Liang Sun

We present a family of expectation-maximization (EM) algorithms for binary and negative-binomial logistic regression, drawing a sharp connection with the variational-Bayes algorithm of Jaakkola and Jordan (2000).

Projection onto A Nonnegative Max-Heap

no code implementations NeurIPS 2011 Jun Liu, Liang Sun, Jieping Ye

In this paper, we show that such Euclidean projection problem admits an analytical solution and we develop a top-down algorithm where the key operation is to find the so-called \emph{maximal root-tree} of the subtree rooted at each node.

Learning Brain Connectivity of Alzheimer's Disease from Neuroimaging Data

no code implementations NeurIPS 2009 Shuai Huang, Jing Li, Liang Sun, Jun Liu, Teresa Wu, Kewei Chen, Adam Fleisher, Eric Reiman, Jieping Ye

Recent advances in neuroimaging techniques provide great potentials for effective diagnosis of Alzheimer’s disease (AD), the most common form of dementia.

Efficient Recovery of Jointly Sparse Vectors

no code implementations NeurIPS 2009 Liang Sun, Jun Liu, Jianhui Chen, Jieping Ye

MMV is an extension of the single measurement vector (SMV) model employed in standard compressive sensing (CS).

Compressive Sensing

Multi-label Multiple Kernel Learning

no code implementations NeurIPS 2008 Shuiwang Ji, Liang Sun, Rong Jin, Jieping Ye

We present a multi-label multiple kernel learning (MKL) formulation, in which the data are embedded into a low-dimensional space directed by the instance-label correlations encoded into a hypergraph.

Cannot find the paper you are looking for? You can Submit a new open access paper.