Search Results for author: Jie Wang

Found 95 papers, 21 papers with code

A Multi-modal one-class generative adversarial network for anomaly detection in manufacturing

no code implementations ICLR 2019 Shuhui Qu, Janghwan Lee, Wei Xiong, Wonhyouk Jang, Jie Wang

Since the generated samples simulate the low density area for each modal, the discriminator could directly detect anomalies from normal data.

Anomaly Detection

Downstream Transformer Generation of Question-Answer Pairs with Preprocessing and Postprocessing Pipelines

1 code implementation15 May 2022 Cheng Zhang, Hao Zhang, Jie Wang

We present a system called TP3 to perform a downstream task of transformers on generating question-answer pairs (QAPs) from a given article.

A Manifold Two-Sample Test Study: Integral Probability Metric with Neural Networks

no code implementations4 May 2022 Jie Wang, Minshuo Chen, Tuo Zhao, Wenjing Liao, Yao Xie

Based on the approximation theory of neural networks, we show that the neural network IPM test has the type-II risk in the order of $n^{-(s+\beta)/d}$, which is in the same order of the type-II risk as the H\"older IPM test.

C3-STISR: Scene Text Image Super-resolution with Triple Clues

1 code implementation29 Apr 2022 Minyi Zhao, Miao Wang, Fan Bai, Bingjia Li, Jie Wang, Shuigeng Zhou

In this paper, we present a novel method C3-STISR that jointly exploits the recognizer's feedback, visual and linguistical information as clues to guide super-resolution.

Image Super-Resolution Language Modelling

Duality-Induced Regularizer for Semantic Matching Knowledge Graph Embeddings

no code implementations24 Mar 2022 Jie Wang, Zhanqiu Zhang, Zhihao Shi, Jianyu Cai, Shuiwang Ji, Feng Wu

Semantic matching models -- which assume that entities with similar semantics have similar embeddings -- have shown great power in knowledge graph embeddings (KGE).

Entity Embeddings Knowledge Graph Embeddings +1

Contextual Networks and Unsupervised Ranking of Sentences

no code implementations9 Mar 2022 Hao Zhang, You Zhou, Jie Wang

We construct a contextual network to represent a document with syntactic and semantic relations between word-sentence pairs, based on which we devise an unsupervised algorithm called CNATAR (Contextual Network And Text Analysis Rank) to score sentences, and rank them through a bi-objective 0-1 knapsack maximization problem over topic analysis and sentence scores.

Boilerplate Detection via Semantic Classification of TextBlocks

no code implementations9 Mar 2022 Hao Zhang, Jie Wang

We present a hierarchical neural network model called SemText to detect HTML boilerplate based on a novel semantic representation of HTML tags, class names, and text blocks.

Classification

A Survey of Neural Trojan Attacks and Defenses in Deep Learning

no code implementations15 Feb 2022 Jie Wang, Ghulam Mubashar Hassan, Naveed Akhtar

It provides a comprehensible gateway to the broader community to understand the recent developments in Neural Trojans.

The xmuspeech system for multi-channel multi-party meeting transcription challenge

no code implementations11 Feb 2022 Jie Wang, Yuji Liu, Binling Wang, Yiming Zhi, Song Li1, Shipeng Xia, Jiayang Zhang, Lin Li1, Qingyang Hong, Feng Tong

By performing DMSNet based OSD module, the DER of cluster-based diarization system decrease significantly form 13. 44% to 7. 63%.

Speaker Diarization

A Data-Driven Approach to Robust Hypothesis Testing Using Sinkhorn Uncertainty Sets

no code implementations9 Feb 2022 Jie Wang, Yao Xie

Hypothesis testing for small-sample scenarios is a practically important problem.

Rethinking Graph Convolutional Networks in Knowledge Graph Completion

1 code implementation8 Feb 2022 Zhanqiu Zhang, Jie Wang, Jieping Ye, Feng Wu

Surprisingly, we observe from experiments that the graph structure modeling in GCNs does not have a significant impact on the performance of KGC models, which is in contrast to the common belief.

Entity Embeddings Knowledge Graph Completion +1

Fooling the Eyes of Autonomous Vehicles: Robust Physical Adversarial Examples Against Traffic Sign Recognition Systems

no code implementations17 Jan 2022 Wei Jia, Zhaojun Lu, Haichun Zhang, Zhenglin Liu, Jie Wang, Gang Qu

From the view of object detectors, the traffic sign`s position and quality of the video are continuously changing, rendering the digital AEs ineffective in the physical world.

Traffic Sign Recognition

Learning to Reformulate for Linear Programming

no code implementations17 Jan 2022 Xijun Li, Qingyu Qu, Fangzhou Zhu, Jia Zeng, Mingxuan Yuan, Kun Mao, Jie Wang

In the past decades, a serial of traditional operation research algorithms have been proposed to obtain the optimum of a given LP in a fewer solving time.

Learning Robust Policy against Disturbance in Transition Dynamics via State-Conservative Policy Optimization

no code implementations20 Dec 2021 Yufei Kuang, Miao Lu, Jie Wang, Qi Zhou, Bin Li, Houqiang Li

Many existing algorithms learn robust policies by modeling the disturbance and applying it to source environments during training, which usually requires prior knowledge about the disturbance and control of simulators.

PAPooling: Graph-based Position Adaptive Aggregation of Local Geometry in Point Clouds

no code implementations28 Nov 2021 Jie Wang, Jianan Li, Lihe Ding, Ying Wang, Tingfa Xu

Fine-grained geometry, captured by aggregation of point features in local regions, is crucial for object recognition and scene understanding in point clouds.

3D Shape Classification graph construction +3

Jointly Learning Agent and Lane Information for Multimodal Trajectory Prediction

no code implementations26 Nov 2021 Jie Wang, Caili Guo, Minan Guo, Jiujiu Chen

JAL-MTP use a Social to Lane (S2L) module to jointly represent the static lane and the dynamic motion of the neighboring agents as instance-level lane, a Recurrent Lane Attention (RLA) mechanism for utilizing the instance-level lanes to predict the map-adaptive future trajectories and two selectors to identify the typical and reasonable trajectories.

Autonomous Vehicles Trajectory Prediction

ConE: Cone Embeddings for Multi-Hop Reasoning over Knowledge Graphs

1 code implementation NeurIPS 2021 Zhanqiu Zhang, Jie Wang, Jiajun Chen, Shuiwang Ji, Feng Wu

To address this challenge, we propose a novel query embedding model, namely Cone Embeddings (ConE), which is the first geometry-based QE model that can handle all the FOL operations, including conjunction, disjunction, and negation.

Knowledge Graphs

FlowX: Towards Explainable Graph Neural Networks via Message Flows

no code implementations29 Sep 2021 Shurui Gui, Hao Yuan, Jie Wang, Qicheng Lao, Kang Li, Shuiwang Ji

We investigate the explainability of graph neural networks (GNNs) as a step towards elucidating their working mechanisms.

Multi-Modal Multi-Instance Learning for Retinal Disease Recognition

no code implementations25 Sep 2021 Xirong Li, Yang Zhou, Jie Wang, Hailan Lin, Jianchun Zhao, Dayong Ding, Weihong Yu, Youxin Chen

We propose in this paper Multi-Modal Multi-Instance Learning (MM-MIL) for selectively fusing CFP and OCT modalities.

Sinkhorn Distributionally Robust Optimization

no code implementations24 Sep 2021 Jie Wang, Rui Gao, Yao Xie

We study distributionally robust optimization with Sinkorn distance -- a variant of Wasserstein distance based on entropic regularization.

XMUSPEECH System for VoxCeleb Speaker Recognition Challenge 2021

no code implementations6 Sep 2021 Jie Wang, Fuchuang Tong, Zhicong Chen, Lin Li, Qingyang Hong, Haodong Zhou

This paper describes the XMUSPEECH speaker recognition and diarisation systems for the VoxCeleb Speaker Recognition Challenge 2021.

Speaker Recognition

A 60-GHz Radar Sensor for Micron-Scale Motion Detection

no code implementations23 Jul 2021 Marcel Balle, Chengkai Zhu, Bin Zhang, Jie Wang, Lixin Ran

A compact, continuous-wave, mmWave radar sensor is developed for non-contact detection of micron-scale motions.

Motion Detection

Technical Report of Team GraphMIRAcles in the WikiKG90M-LSC Track of OGB-LSC @ KDD Cup 2021

no code implementations12 Jul 2021 Jianyu Cai, Jiajun Chen, Taoxing Pan, Zhanqiu Zhang, Jie Wang

To address this challenge, we propose a framework that integrates three components -- a basic model ComplEx-CMRC, a rule miner AMIE 3, and an inference model to predict missing links.

Knowledge Distillation Knowledge Graphs +1

Learning to Optimize Industry-Scale Dynamic Pickup and Delivery Problems

no code implementations27 May 2021 Xijun Li, Weilin Luo, Mingxuan Yuan, Jun Wang, Jiawen Lu, Jie Wang, Jinhu Lu, Jia Zeng

Our method is entirely data driven and thus adaptive, i. e., the relational representation of adjacent vehicles can be learned and corrected by ST-DDGN from data periodically.

Graph Embedding

Unsupervised Domain Expansion for Visual Categorization

1 code implementation1 Apr 2021 Jie Wang, Kaibin Tian, Dayong Ding, Gang Yang, Xirong Li

In this paper we extend UDA by proposing a new task called unsupervised domain expansion (UDE), which aims to adapt a deep model for the target domain with its unlabeled data, meanwhile maintaining the model's performance on the source domain.

Knowledge Distillation Unsupervised Domain Adaptation +1

Transformer Meets Tracker: Exploiting Temporal Context for Robust Visual Tracking

1 code implementation CVPR 2021 Ning Wang, Wengang Zhou, Jie Wang, Houqaing Li

In video object tracking, there exist rich temporal contexts among successive frames, which have been largely overlooked in existing trackers.

Frame Video Object Tracking +2

Topology-Aware Correlations Between Relations for Inductive Link Prediction in Knowledge Graphs

1 code implementation5 Mar 2021 Jiajun Chen, Huarui He, Feng Wu, Jie Wang

TACT is inspired by the observation that the semantic correlation between two relations is highly correlated to their topological structure in knowledge graphs.

Inductive Link Prediction Knowledge Graphs

Analysing Wideband Absorbance Immittance in Normal and Ears with Otitis Media with Effusion Using Machine Learning

no code implementations4 Mar 2021 Emad M. Grais, Xiaoya Wang, Jie Wang, Fei Zhao, Wen Jiang, Yuexin Cai, Lifang Zhang, Qingwen Lin, Haidi Yang

Wideband Absorbance Immittance (WAI) has been available for more than a decade, however its clinical use still faces the challenges of limited understanding and poor interpretation of WAI results.

On Explainability of Graph Neural Networks via Subgraph Explorations

1 code implementation9 Feb 2021 Hao Yuan, Haiyang Yu, Jie Wang, Kang Li, Shuiwang Ji

To make the tree search more effective, we propose to use Shapley values as a measure of subgraph importance, which can also capture the interactions among different subgraphs.

Adversarially learning disentangled speech representations for robust multi-factor voice conversion

no code implementations30 Jan 2021 Jie Wang, Jingbei Li, Xintao Zhao, Zhiyong Wu, Shiyin Kang, Helen Meng

To increase the robustness of highly controllable style transfer on multiple factors in VC, we propose a disentangled speech representation learning framework based on adversarial learning.

Representation Learning Style Transfer +1

UNIT: Unifying Tensorized Instruction Compilation

no code implementations21 Jan 2021 Jian Weng, Animesh Jain, Jie Wang, Leyuan Wang, Yida Wang, Tony Nowatzki

However, it is hard to leverage mixed precision without hardware support because of the overhead of data casting.

Attention-Guided Black-box Adversarial Attacks with Large-Scale Multiobjective Evolutionary Optimization

no code implementations ICML Workshop AML 2021 Jie Wang, Zhaoxia Yin, Jing Jiang, Yang Du

In this paper, we propose an attention-guided black-box adversarial attack based on the large-scale multiobjective evolutionary optimization, termed as LMOA.

Adversarial Attack

PICA: A Pixel Correlation-based Attentional Black-box Adversarial Attack

no code implementations19 Jan 2021 Jie Wang, Zhaoxia Yin, Jin Tang, Jing Jiang, Bin Luo

The studies on black-box adversarial attacks have become increasingly prevalent due to the intractable acquisition of the structural knowledge of deep neural networks (DNNs).

Adversarial Attack

The simpler the better: vanilla sgd revisited

no code implementations1 Jan 2021 Yueyao Yu, Jie Wang, Wenye Li, Yin Zhang

The stochastic gradient descent (SGD) method, first proposed in 1950's, has been the foundation for deep-neural-network (DNN) training with numerous enhancements including adding a momentum or adaptively selecting learning rates, or using both strategies and more.

Image Classification Speech Recognition

Topological charge engineering in lasing bound states in continuum

no code implementations31 Dec 2020 Sughra Mohamed, Jie Wang, Heikki Rekola, Janne Heikkinen, Benjamin Asamoah, Lei Shi, Tommi K. Hakala

We experimentally analyze all four observed lasing BICs by imaging their far-field polarization vortices and their associated topological charges.

Optics

Deep Deterministic Policy Gradient for Relay Selection and Power Allocation in Cooperative Communication Network

no code implementations11 Dec 2020 Yuanzhe Geng, Erwu Liu, Rui Wang, Yiming Liu, Jie Wang, Gang Shen, Zhao Dong

Perfect channel state information (CSI) is usually required when considering relay selection and power allocation in cooperative communication.

Information Theory Systems and Control Systems and Control Information Theory

Promoting Stochasticity for Expressive Policies via a Simple and Efficient Regularization Method

no code implementations NeurIPS 2020 Qi Zhou, Yufei Kuang, Zherui Qiu, Houqiang Li, Jie Wang

However, in continuous action spaces, integrating entropy regularization with expressive policies is challenging and usually requires complex inference procedures.

Continuous Control reinforcement-learning

Fast Hybrid Cascade for Voxel-based 3D Object Classification

1 code implementation9 Nov 2020 Hui Cao, Jie Wang, Yuqi Liu, Siyu Zhang, Shen Cai

We then propose a fast fully connected and convolution hybrid cascade network for voxel-based 3D object classification.

3D Object Classification Classification +1

Reliable Off-policy Evaluation for Reinforcement Learning

no code implementations8 Nov 2020 Jie Wang, Rui Gao, Hongyuan Zha

In a sequential decision-making problem, off-policy evaluation estimates the expected cumulative reward of a target policy using logged trajectory data generated from a different behavior policy, without execution of the target policy.

Decision Making reinforcement-learning

Extracting Body Text from Academic PDF Documents for Text Mining

no code implementations23 Oct 2020 Changfeng Yu, Cheng Zhang, Jie Wang

Accurate extraction of body text from PDF-formatted academic documents is essential in text-mining applications for deeper semantic understandings.

Generating Adequate Distractors for Multiple-Choice Questions

no code implementations23 Oct 2020 Cheng Zhang, Yicheng Sun, Hejia Chen, Jie Wang

This paper presents a novel approach to automatic generation of adequate distractors for a given question-answer pair (QAP) generated from a given article to form an adequate multiple-choice question (MCQ).

Multiple-choice Part-Of-Speech Tagging +2

Two-sample Test using Projected Wasserstein Distance: Breaking the Curse of Dimensionality

no code implementations22 Oct 2020 Jie Wang, Rui Gao, Yao Xie

We develop a projected Wasserstein distance for the two-sample test, a fundamental problem in statistics and machine learning: given two sets of samples, to determine whether they are from the same distribution.

Line Graph Neural Networks for Link Prediction

1 code implementation20 Oct 2020 Lei Cai, Jundong Li, Jie Wang, Shuiwang Ji

In this formalism, a link prediction problem is converted to a graph classification task.

Classification General Classification +3

When HLS Meets FPGA HBM: Benchmarking and Bandwidth Optimization

1 code implementation12 Oct 2020 Young-kyu Choi, Yuze Chi, Jie Wang, Licheng Guo, Jason Cong

With the recent release of High Bandwidth Memory (HBM) based FPGA boards, developers can now exploit unprecedented external memory bandwidth.

Hardware Architecture

Meta Sequence Learning for Generating Adequate Question-Answer Pairs

no code implementations4 Oct 2020 Cheng Zhang, Jie Wang

Creating multiple-choice questions to assess reading comprehension of a given article involves generating question-answer pairs (QAPs) on the main points of the document.

Multiple-choice Named Entity Recognition +3

An Intuitive Tutorial to Gaussian Processes Regression

2 code implementations22 Sep 2020 Jie Wang

This tutorial aims to provide an intuitive understanding of the Gaussian processes regression.

GPR

Variational Representations and Neural Network Estimation of Rényi Divergences

no code implementations7 Jul 2020 Jeremiah Birrell, Paul Dupuis, Markos A. Katsoulakis, Luc Rey-Bellet, Jie Wang

We further show that this R\'enyi variational formula holds over a range of function spaces; this leads to a formula for the optimizer under very weak assumptions and is also key in our development of a consistency theory for R\'enyi divergence estimators.

Review of Text Style Transfer Based on Deep Learning

no code implementations6 May 2020 Xiang-Yang Li, Guo Pu, Keyu Ming, Pu Li, Jie Wang, Yuxuan Wang

In the traditional text style transfer model, the text style is generally relied on by experts knowledge and hand-designed rules, but with the application of deep learning in the field of natural language processing, the text style transfer method based on deep learning Started to be heavily researched.

Style Transfer Text Style Transfer

An Unsupervised Semantic Sentence Ranking Scheme for Text Documents

no code implementations28 Apr 2020 Hao Zhang, Jie Wang

It applies two variants of article-structure-biased PageRank to score phrases and words on the first graph and sentences on the second graph.

Chordal-TSSOS: a moment-SOS hierarchy that exploits term sparsity with chordal extension

1 code implementation4 Mar 2020 Jie Wang, Victor Magron, Jean-Bernard Lasserre

The novelty and distinguishing feature of such relaxations is to obtain quasi block-diagonal matrices obtained in an iterative procedure that performs chordal extension of certain adjacency graphs.

Optimization and Control 14P10, 90C25, 12D15, 12Y05

Baryon acoustic oscillations reconstruction using convolutional neural networks

no code implementations24 Feb 2020 Tian-Xiang Mao, Jie Wang, Baojiu Li, Yan-Chuan Cai, Bridget Falck, Mark Neyrinck, Alex Szalay

We propose a new scheme to reconstruct the baryon acoustic oscillations (BAO) signal, which contains key cosmological information, based on deep convolutional neural networks (CNN).

TSSOS: A Moment-SOS hierarchy that exploits term sparsity

3 code implementations18 Dec 2019 Jie Wang, Victor Magron, Jean-Bernard Lasserre

This paper is concerned with polynomial optimization problems.

Optimization and Control

Deep Model-Based Reinforcement Learning via Estimated Uncertainty and Conservative Policy Optimization

1 code implementation28 Nov 2019 Qi Zhou, Houqiang Li, Jie Wang

In this paper, We propose a Policy Optimization method with Model-Based Uncertainty (POMBU)---a novel model-based approach---that can effectively improve the asymptotic performance using the uncertainty in Q-values.

Model-based Reinforcement Learning reinforcement-learning

D-SPIDER-SFO: A Decentralized Optimization Algorithm with Faster Convergence Rate for Nonconvex Problems

no code implementations28 Nov 2019 Taoxing Pan, Jun Liu, Jie Wang

To the best of our knowledge, D-SPIDER-SFO achieves the state-of-the-art performance for solving nonconvex optimization problems on decentralized networks in terms of the computational cost.

Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction

6 code implementations21 Nov 2019 Zhanqiu Zhang, Jianyu Cai, Yongdong Zhang, Jie Wang

HAKE is inspired by the fact that concentric circles in the polar coordinate system can naturally reflect the hierarchy.

Knowledge Graph Completion Knowledge Graph Embedding +2

Reversible Adversarial Attack based on Reversible Image Transformation

no code implementations6 Nov 2019 Zhaoxia Yin, Hua Wang, Li Chen, Jie Wang, Weiming Zhang

In order to prevent illegal or unauthorized access of image data such as human faces and ensure legitimate users can use authorization-protected data, reversible adversarial attack technique is rise.

Adversarial Attack Image Restoration

Generating an Overview Report over Many Documents

no code implementations17 Aug 2019 Jingwen Wang, Hao Zhang, Cheng Zhang, Wenjing Yang, Liqun Shao, Jie Wang

To overcome this obstacle, we present NDORGS (Numerous Documents' Overview Report Generation Scheme) that integrates text filtering, keyword scoring, single-document summarization (SDS), topic modeling, MDS, and title generation to generate a coherent, well-structured ORPT.

Decision Making Document Summarization +1

Analyzing Linguistic Complexity and Scientific Impact

no code implementations27 Jul 2019 Chao Lu, Yi Bu, Xianlei Dong, Jie Wang, Ying Ding, Vincent Larivière, Cassidy R. Sugimoto, Logan Paul, Chengzhi Zhang

In this context, scientific writing increasingly plays an important role in scholars' scientific careers.

Cross-Platform Modeling of Users' Behavior on Social Media

no code implementations23 Jun 2019 Haiqian Gu, Jie Wang, Ziwen Wang, Bojin Zhuang, Wenhao Bian, Fei Su

Structured and unstructured data of same users shared by NetEase Music and Sina Weibo have been collected for cross-platform analysis of correlations between music preference and other users' characteristics.

A Hierarchical Attention Based Seq2seq Model for Chinese Lyrics Generation

no code implementations15 Jun 2019 Haoshen Fan, Jie Wang, Bojin Zhuang, Shaojun Wang, Jing Xiao

In this paper, we comprehensively study on context-aware generation of Chinese song lyrics.

A Syllable-Structured, Contextually-Based Conditionally Generation of Chinese Lyrics

no code implementations15 Jun 2019 Xu Lu, Jie Wang, Bojin Zhuang, Shaojun Wang, Jing Xiao

This paper presents a novel, syllable-structured Chinese lyrics generation model given a piece of original melody.

Automatic Acrostic Couplet Generation with Three-Stage Neural Network Pipelines

no code implementations15 Jun 2019 Haoshen Fan, Jie Wang, Bojin Zhuang, Shaojun Wang, Jing Xiao

In this paper, we comprehensively study on automatic generation of acrostic couplet with the first characters defined by users.

Re-Ranking

Deep learning based mood tagging for Chinese song lyrics

no code implementations23 May 2019 Jie Wang, Yilin Yang

Nowadays, listening music has been and will always be an indispensable part of our daily life.

Information Retrieval Recommendation Systems +1

Theme-aware generation model for chinese lyrics

no code implementations23 May 2019 Jie Wang, Xinyan Zhao

With rapid development of neural networks, deep-learning has been extended to various natural language generation fields, such as machine translation, dialogue generation and even literature creation.

Dialogue Generation Machine Translation +1

SvTPM: A Secure and Efficient vTPM in the Cloud

1 code implementation21 May 2019 Juan Wang, Chengyang Fan, Jie Wang, Yueqiang Cheng, Yinqian Zhang, Wenhui Zhang, Peng Liu, Hongxin Hu

In this paper, we present SvTPM, a secure and efficient software-based vTPM implementation based on hardware-rooted Trusted Execution Environment (TEE), providing a whole life cycle protection of vTPMs in the cloud.

Cryptography and Security

An Efficient Pre-processing Method to Eliminate Adversarial Effects

no code implementations15 May 2019 Hua Wang, Jie Wang, Zhaoxia Yin

Deep Neural Networks (DNNs) are vulnerable to adversarial examples generated by imposing subtle perturbations to inputs that lead a model to predict incorrect outputs.

General Classification Image Classification +1

Multi-Agent Deep Reinforcement Learning for Large-scale Traffic Signal Control

1 code implementation11 Mar 2019 Tianshu Chu, Jie Wang, Lara Codecà, Zhaojian Li

Reinforcement learning (RL) is a promising data-driven approach for adaptive traffic signal control (ATSC) in complex urban traffic networks, and deep neural networks further enhance its learning power.

Q-Learning reinforcement-learning

Mexican Hat Wavelet Kernel ELM for Multiclass Classification

no code implementations20 Feb 2019 Jie Wang, Yi-Fan Song, Tian-Lei Ma

Kernel extreme learning machine (KELM) is a novel feedforward neural network, which is widely used in classification problems.

Classification General Classification

Semantic WordRank: Generating Finer Single-Document Summarizations

no code implementations12 Sep 2018 Hao Zhang, Jie Wang

We present Semantic WordRank (SWR), an unsupervised method for generating an extractive summary of a single document.

Examining Scientific Writing Styles from the Perspective of Linguistic Complexity

no code implementations22 Jul 2018 Chao Lu, Yi Bu, Jie Wang, Ying Ding, Vetle Torvik, Matthew Schnaars, Chengzhi Zhang

The observations suggest marginal differences between groups in syntactical and lexical complexity.

Efficient and Effective Single-Document Summarizations and A Word-Embedding Measurement of Quality

no code implementations1 Oct 2017 Liqun Shao, Hao Zhang, Ming Jia, Jie Wang

We show that the orderings of the ROUGE and WESM scores of our algorithms are highly comparable, suggesting that WESM may serve as a viable alternative for measuring the quality of a summary.

Keyword Extraction

DTATG: An Automatic Title Generator based on Dependency Trees

no code implementations1 Oct 2017 Liqun Shao, Jie Wang

We study automatic title generation for a given block of text and present a method called DTATG to generate titles.

Probabilistic graphical model based approach for water mapping using GaoFen-2 (GF-2) high resolution imagery and Landsat 8 time series

no code implementations22 Dec 2016 Luyan Ji, Jie Wang, Xiurui Geng, Peng Gong

Difficulties of water mapping on high resolution data includes: 1) misclassification between water and shadows or other low-reflectance ground objects, which is mostly caused by the spectral similarity within the given band range; 2) small water bodies with size smaller than the spatial resolution of MS image.

Time Series

A probabilistic graphical model approach in 30 m land cover mapping with multiple data sources

no code implementations11 Dec 2016 Jie Wang, Luyan Ji, Xiaomeng Huang, Haohuan Fu, Shiming Xu, Cong-Cong Li

Conditional probability distributions were computed based on data quality and reliability by using information selectively.

Time Series

Large-scale Collaborative Imaging Genetics Studies of Risk Genetic Factors for Alzheimer's Disease Across Multiple Institutions

no code implementations19 Aug 2016 Qingyang Li, Tao Yang, Liang Zhan, Derrek Paul Hibar, Neda Jahanshad, Yalin Wang, Jieping Ye, Paul M. Thompson, Jie Wang

To the best of our knowledge, this is the first successful run of the computationally intensive model selection procedure to learn a consistent model across different institutions without compromising their privacy while ranking the SNPs that may collectively affect AD.

Model Selection

Scaling Up Sparse Support Vector Machines by Simultaneous Feature and Sample Reduction

1 code implementation ICML 2017 Weizhong Zhang, Bin Hong, Wei Liu, Jieping Ye, Deng Cai, Xiaofei He, Jie Wang

By noting that sparse SVMs induce sparsities in both feature and sample spaces, we propose a novel approach, which is based on accurate estimations of the primal and dual optima of sparse SVMs, to simultaneously identify the inactive features and samples that are guaranteed to be irrelevant to the outputs.

Multi-Layer Feature Reduction for Tree Structured Group Lasso via Hierarchical Projection

no code implementations NeurIPS 2015 Jie Wang, Jieping Ye

By a novel hierarchical projection algorithm, MLFre is able to test the nodes independently from any of their ancestor nodes.

Safe Screening for Multi-Task Feature Learning with Multiple Data Matrices

no code implementations15 May 2015 Jie Wang, Jieping Ye

One of the appealing features of DPC is that: it is safe in the sense that the detected inactive features are guaranteed to have zero coefficients in the solution vectors across all tasks.

Two-Layer Feature Reduction for Sparse-Group Lasso via Decomposition of Convex Sets

no code implementations NeurIPS 2014 Jie Wang, Jieping Ye

Sparse-Group Lasso (SGL) has been shown to be a powerful regression technique for simultaneously discovering group and within-group sparse patterns by using a combination of the $\ell_1$ and $\ell_2$ norms.

Scaling SVM and Least Absolute Deviations via Exact Data Reduction

no code implementations25 Oct 2013 Jie Wang, Peter Wonka, Jieping Ye

Some appealing features of our screening method are: (1) DVI is safe in the sense that the vectors discarded by DVI are guaranteed to be non-support vectors; (2) the data set needs to be scanned only once to run the screening, whose computational cost is negligible compared to that of solving the SVM problem; (3) DVI is independent of the solvers and can be integrated with any existing efficient solvers.

Safe Screening With Variational Inequalities and Its Application to LASSO

no code implementations29 Jul 2013 Jun Liu, Zheng Zhao, Jie Wang, Jieping Ye

Safe screening is gaining increasing attention since 1) solving sparse learning formulations usually has a high computational cost especially when the number of features is large and 2) one needs to try several regularization parameters to select a suitable model.

Sparse Learning

Efficient Mixed-Norm Regularization: Algorithms and Safe Screening Methods

no code implementations16 Jul 2013 Jie Wang, Jun Liu, Jieping Ye

One key building block of the proposed algorithm is the l1q-regularized Euclidean projection (EP_1q).

Sparse Learning

A Safe Screening Rule for Sparse Logistic Regression

no code implementations NeurIPS 2014 Jie Wang, Jiayu Zhou, Jun Liu, Peter Wonka, Jieping Ye

The l1-regularized logistic regression (or sparse logistic regression) is a widely used method for simultaneous classification and feature selection.

Lasso Screening Rules via Dual Polytope Projection

no code implementations NeurIPS 2013 Jie Wang, Peter Wonka, Jieping Ye

To improve the efficiency of solving large-scale Lasso problems, El Ghaoui and his colleagues have proposed the SAFE rules which are able to quickly identify the inactive predictors, i. e., predictors that have $0$ components in the solution vector.

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