Search Results for author: Yue Wang

Found 170 papers, 62 papers with code

基于词信息嵌入的汉语构词结构识别研究(Chinese Word-Formation Prediction based on Representations of Word-Related Features)

no code implementations CCL 2021 Hua Zheng, Yaqi Yan, Yue Wang, Damai Dai, Yang Liu

“作为一种意合型语言, 汉语中的构词结构刻画了构词成分之间的组合关系, 是认知、理解词义的关键。在中文信息处理领域, 此前的构词结构识别工作大多沿用句法层面的粗粒度标签, 且主要基于上下文等词间信息建模, 忽略了语素义、词义等词内信息对构词结构识别的作用。本文采用语言学视域下的构词结构标签体系, 构建汉语构词结构及相关信息数据集, 提出了一种基于Bi-LSTM和Self-attention的模型, 以此来探究词内、词间等多方面信息对构词结构识别的潜在影响和能达到的性能。实验取得了良好的预测效果, 准确率77. 87%, F1值78. 36%;同时, 对比测试揭示, 词内的语素义信息对构词结构识别具有显著的贡献, 而词间的上下文信息贡献较弱且带有较强的不稳定性。该预测方法与数据集, 将为中文信息处理的多种任务, 如语素和词结构分析、词义识别与生成、语言文字研究与词典编纂等提供新的观点和方案。”

Predicting Stock Price Movement after Disclosure of Corporate Annual Reports: A Case Study of 2021 China CSI 300 Stocks

no code implementations25 Jun 2022 Fengyu Han, Yue Wang

We conclude that according to the financial indicators based on the just-released annual report of the company, the predictability of the stock price movement on the second day after disclosure is weak, with maximum accuracy about 59. 6% and maximum precision about 0. 56 on our test set by the random forest classifier, and the stock filtering does not improve the performance.

Stock Price Prediction

Deep Random Vortex Method for Simulation and Inference of Navier-Stokes Equations

no code implementations20 Jun 2022 Rui Zhang, Peiyan Hu, Qi Meng, Yue Wang, Rongchan Zhu, Bingguang Chen, Zhi-Ming Ma, Tie-Yan Liu

To this end, we propose the \emph{Deep Random Vortex Method} (DRVM), which combines the neural network with a random vortex dynamics system equivalent to the Navier-Stokes equation.

VectorMapNet: End-to-end Vectorized HD Map Learning

no code implementations17 Jun 2022 Yicheng Liu, Yue Wang, Yilun Wang, Hang Zhao

Autonomous driving systems require a good understanding of surrounding environments, including moving obstacles and static High-Definition (HD) semantic maps.

Autonomous Driving

Collaborative Knowledge Graph Fusion by Exploiting the Open Corpus

no code implementations15 Jun 2022 Yue Wang, Yao Wan, Lu Bai, Lixin Cui, Zhuo Xu, Ming Li, Philip S. Yu, Edwin R Hancock

To alleviate the challenges of building Knowledge Graphs (KG) from scratch, a more general task is to enrich a KG using triples from an open corpus, where the obtained triples contain noisy entities and relations.

Event Extraction Knowledge Graphs

MBGDT:Robust Mini-Batch Gradient Descent

2 code implementations14 Jun 2022 Hanming Wang, Haozheng Luo, Yue Wang

In high dimensions, most machine learning method perform fragile even there are a little outliers.

RoSGAS: Adaptive Social Bot Detection with Reinforced Self-Supervised GNN Architecture Search

no code implementations14 Jun 2022 Yingguang Yang, Renyu Yang, Yangyang Li, Kai Cui, Zhiqin Yang, Yue Wang, Jie Xu, Haiyong Xie

More specifically, we consider the social bot detection problem as a user-centric subgraph embedding and classification task.

Self-Supervised Learning

DPCN++: Differentiable Phase Correlation Network for Versatile Pose Registration

no code implementations12 Jun 2022 Zexi Chen, Yiyi Liao, Haozhe Du, Haodong Zhang, Xuecheng Xu, Haojian Lu, Rong Xiong, Yue Wang

Next, the rotation, scale, and translation are independently and efficiently estimated in the spectrum step-by-step using the DPC solver.


Policy Gradient Method For Robust Reinforcement Learning

no code implementations15 May 2022 Yue Wang, Shaofeng Zou

We further develop a smoothed robust policy gradient method and show that to achieve an $\epsilon$-global optimum, the complexity is $\mathcal O(\epsilon^{-3})$.


Learning A Simulation-based Visual Policy for Real-world Peg In Unseen Holes

1 code implementation9 May 2022 Liang Xie, Hongxiang Yu, Kechun Xu, Tong Yang, Minhang Wang, Haojian Lu, Rong Xiong, Yue Wang

This paper proposes a learning-based visual peg-in-hole that enables training with several shapes in simulation, and adapting to arbitrary unseen shapes in real world with minimal sim-to-real cost.

TomoSAR-ALISTA: Efficient TomoSAR Imaging via Deep Unfolded Network

no code implementations5 May 2022 Muhan Wang, Zhe Zhang, Yue Wang, Silin Gao, Xiaolan Qiu

Synthetic aperture radar (SAR) tomography (TomoSAR) has attracted remarkable interest for its ability in achieving three-dimensional reconstruction along the elevation direction from multiple observations.

3D Reconstruction Super-Resolution

MUTR3D: A Multi-camera Tracking Framework via 3D-to-2D Queries

1 code implementation2 May 2022 Tianyuan Zhang, Xuanyao Chen, Yue Wang, Yilun Wang, Hang Zhao

In contrast to prior works, MUTR3D does not explicitly rely on the spatial and appearance similarity of objects.

Autonomous Driving Depth Estimation

Neural Operator with Regularity Structure for Modeling Dynamics Driven by SPDEs

1 code implementation13 Apr 2022 Peiyan Hu, Qi Meng, Bingguang Chen, Shiqi Gong, Yue Wang, Wei Chen, Rongchan Zhu, Zhi-Ming Ma, Tie-Yan Liu

Stochastic partial differential equations (SPDEs) are significant tools for modeling dynamics in many areas including atmospheric sciences and physics.

Blind Orthogonal Least Squares based Compressive Spectrum Sensing

no code implementations11 Apr 2022 Liyang Lu, Wenbo Xu, Yue Wang, Siye Wang

Compressive spectrum sensing (CSS) has been widely studied in wideband cognitive radios, benefiting from the reduction of sampling rate via compressive sensing (CS) technology.

Compressive Sensing

Accurate Portraits of Scientific Resources and Knowledge Service Components

no code implementations11 Apr 2022 Yue Wang, Zhe Xue, Ang Li

With the advent of the cloud computing era, the cost of creating, capturing and managing information has gradually decreased.

A Visual Navigation Perspective for Category-Level Object Pose Estimation

no code implementations25 Mar 2022 Jiaxin Guo, Fangxun Zhong, Rong Xiong, Yunhui Liu, Yue Wang, Yiyi Liao

In this paper, we take a deeper look at the inference of analysis-by-synthesis from the perspective of visual navigation, and investigate what is a good navigation policy for this specific task.

Imitation Learning Pose Estimation +1

Academic Resource Text Level Multi-label Classification based on Attention

no code implementations21 Mar 2022 Yue Wang, Yawen Li, Ang Li

We propose an attention-based hierarchical multi-label classification algorithm of academic texts (AHMCA) by integrating features such as text, keywords, and hierarchical structure, the academic documents are classified into the most relevant categories.

Document Embedding Hierarchical Multi-label Classification +1

FUTR3D: A Unified Sensor Fusion Framework for 3D Detection

no code implementations20 Mar 2022 Xuanyao Chen, Tianyuan Zhang, Yue Wang, Yilun Wang, Hang Zhao

Sensor fusion is an essential topic in many perception systems, such as autonomous driving and robotics.

Autonomous Driving

PiDAn: A Coherence Optimization Approach for Backdoor Attack Detection and Mitigation in Deep Neural Networks

no code implementations17 Mar 2022 Yue Wang, Wenqing Li, Esha Sarkar, Muhammad Shafique, Michail Maniatakos, Saif Eddin Jabari

Based on our theoretical analysis and experimental results, we demonstrate the effectiveness of PiDAn in defending against backdoor attacks that use different settings of poisoned samples on GTSRB and ILSVRC2012 datasets.

Anomaly Detection Backdoor Attack

CtlGAN: Few-shot Artistic Portraits Generation with Contrastive Transfer Learning

no code implementations16 Mar 2022 Yue Wang, Ran Yi, Ying Tai, Chengjie Wang, Lizhuang Ma

We propose a new encoder which embeds real faces into Z+ space and proposes a dual-path training strategy to better cope with the adapted decoder and eliminate the artifacts.

Computer Vision Image-to-Image Translation +1

Translation Invariant Global Estimation of Heading Angle Using Sinogram of LiDAR Point Cloud

no code implementations2 Mar 2022 Xiaqing Ding, Xuecheng Xu, Sha Lu, Yanmei Jiao, Mengwen Tan, Rong Xiong, Huanjun Deng, Mingyang Li, Yue Wang

Global point cloud registration is an essential module for localization, of which the main difficulty exists in estimating the rotation globally without initial value.

Point Cloud Registration Translation

Writing Style Aware Document-level Event Extraction

no code implementations10 Jan 2022 Zhuo Xu, Yue Wang, Lu Bai, Lixin Cui

This verifies the writing style contains valuable information that could improve the performance of the event extraction task.

Document-level Event Extraction Event Extraction +1

Inference on autoregulation in gene expression

no code implementations10 Jan 2022 Yue Wang, Siqi He

We generalize these results to all types of autoregulations by two propositions on discrete-state continuous-time Markov chains.

Robust factored principal component analysis for matrix-valued outlier accommodation and detection

no code implementations13 Dec 2021 Xuan Ma, Jianhua Zhao, Yue Wang

To solve the robustness problem suffered by FPCA and make it applicable to matrix data, in this paper we propose a robust extension of FPCA (RFPCA), which is built upon a $t$-type distribution called matrix-variate $t$ distribution.

Dimensionality Reduction Outlier Detection

Auto-Tag: Tagging-Data-By-Example in Data Lakes

no code implementations11 Dec 2021 Yeye He, Jie Song, Yue Wang, Surajit Chaudhuri, Vishal Anil, Blake Lassiter, Yaron Goland, Gaurav Malhotra

As data lakes become increasingly popular in large enterprises today, there is a growing need to tag or classify data assets (e. g., files and databases) in data lakes with additional metadata (e. g., semantic column-types), as the inferred metadata can enable a range of downstream applications like data governance (e. g., GDPR compliance), and dataset search.


Transformer-based Network for RGB-D Saliency Detection

no code implementations1 Dec 2021 Yue Wang, Xu Jia, Lu Zhang, Yuke Li, James Elder, Huchuan Lu

TFFM conducts a sufficient feature fusion by integrating features from multiple scales and two modalities over all positions simultaneously.

Saliency Detection

Weakly Supervised Prototype Topic Model with Discriminative Seed Words: Modifying the Category Prior by Self-exploring Supervised Signals

no code implementations20 Nov 2021 Bing Wang, Yue Wang, Ximing Li, Jihong Ouyang

The recent generative dataless methods construct document-specific category priors by using seed word occurrences only, however, such category priors often contain very limited and even noisy supervised signals.

Text Classification

EventNarrative: A large-scale Event-centric Dataset for Knowledge Graph-to-Text Generation

no code implementations30 Oct 2021 Anthony Colas, Ali Sadeghian, Yue Wang, Daisy Zhe Wang

We also evaluate two types of baseline on EventNarrative: a graph-to-text specific model and two state-of-the-art language models, which previous work has shown to be adaptable to the knowledge graph-to-text domain.

Knowledge Graphs Text Generation

BEV-SGD: Best Effort Voting SGD for Analog Aggregation Based Federated Learning against Byzantine Attackers

no code implementations18 Oct 2021 Xin Fan, Yue Wang, Yan Huo, Zhi Tian

As a promising distributed learning technology, analog aggregation based federated learning over the air (FLOA) provides high communication efficiency and privacy provisioning under the edge computing paradigm.

Edge-computing Federated Learning

Revisiting Latent-Space Interpolation via a Quantitative Evaluation Framework

1 code implementation13 Oct 2021 Lu Mi, Tianxing He, Core Francisco Park, Hao Wang, Yue Wang, Nir Shavit

In this work, we show how data labeled with semantically continuous attributes can be utilized to conduct a quantitative evaluation of latent-space interpolation algorithms, for variational autoencoders.

Object DGCNN: 3D Object Detection using Dynamic Graphs

1 code implementation NeurIPS 2021 Yue Wang, Justin Solomon

Our method models 3D object detection as message passing on a dynamic graph, generalizing the DGCNN framework to predict a set of objects.

2D object detection 3D Object Detection +3

DETR3D: 3D Object Detection from Multi-view Images via 3D-to-2D Queries

1 code implementation13 Oct 2021 Yue Wang, Vitor Guizilini, Tianyuan Zhang, Yilun Wang, Hang Zhao, Justin Solomon

This top-down approach outperforms its bottom-up counterpart in which object bounding box prediction follows per-pixel depth estimation, since it does not suffer from the compounding error introduced by a depth prediction model.

3D Object Detection Autonomous Driving +2

Machine Translation Verbosity Control for Automatic Dubbing

no code implementations8 Oct 2021 Surafel M. Lakew, Marcello Federico, Yue Wang, Cuong Hoang, Yogesh Virkar, Roberto Barra-Chicote, Robert Enyedi

Automatic dubbing aims at seamlessly replacing the speech in a video document with synthetic speech in a different language.

Machine Translation Translation

Are BERT Families Zero-Shot Learners? A Study on Their Potential and Limitations

no code implementations29 Sep 2021 Yue Wang, Lijun Wu, Xiaobo Liang, Juntao Li, Min Zhang

Starting from the resurgence of deep learning, language models (LMs) have never been so popular.

Online Robust Reinforcement Learning with Model Uncertainty

no code implementations NeurIPS 2021 Yue Wang, Shaofeng Zou

In this paper, we focus on model-free robust RL, where the uncertainty set is defined to be centering at a misspecified MDP that generates a single sample trajectory sequentially and is assumed to be unknown.

Q-Learning reinforcement-learning

Learning Stereopsis from Geometric Synthesis for 6D Object Pose Estimation

no code implementations25 Sep 2021 Jun Wu, Lilu Liu, Yue Wang, Rong Xiong

Current monocular-based 6D object pose estimation methods generally achieve less competitive results than RGBD-based methods, mostly due to the lack of 3D information.

6D Pose Estimation using RGB

Fully Differentiable and Interpretable Model for VIO with 4 Trainable Parameters

no code implementations25 Sep 2021 Zexi Chen, Haozhe Du, Yiyi Liao, Yue Wang, Rong Xiong

In this paper, we propose a fully differentiable, interpretable, and lightweight monocular VIO model that contains only 4 trainable parameters.

Autonomous Driving Pose Estimation

Domain Generalization for Vision-based Driving Trajectory Generation

1 code implementation22 Sep 2021 Yunkai Wang, Dongkun Zhang, Yuxiang Cui, Zexi Chen, Wei Jing, Junbo Chen, Rong Xiong, Yue Wang

In this paper, we propose a domain generalization method for vision-based driving trajectory generation for autonomous vehicles in urban environments, which can be seen as a solution to extend the Invariant Risk Minimization (IRM) method in complex problems.

Autonomous Vehicles Domain Generalization

CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation

1 code implementation EMNLP 2021 Yue Wang, Weishi Wang, Shafiq Joty, Steven C. H. Hoi

We present CodeT5, a unified pre-trained encoder-decoder Transformer model that better leverages the code semantics conveyed from the developer-assigned identifiers.

Clone Detection Code Generation +5

A framework for massive scale personalized promotion

no code implementations27 Aug 2021 Yitao Shen, Yue Wang, Xingyu Lu, Feng Qi, Jia Yan, Yixiang Mu, Yao Yang, Yifan Peng, Jinjie Gu

In order to do effective optimization in the second stage, counterfactual prediction and noise-reduction are essential for the first stage.

Inference on the structure of gene regulatory networks

no code implementations27 Jul 2021 Yue Wang, Zikun Wang

For scenarios that have not been covered in literature, if the structure can be inferred, we propose new mathematical inference methods and evaluate them on simulated data.

HDMapNet: An Online HD Map Construction and Evaluation Framework

2 code implementations13 Jul 2021 Qi Li, Yue Wang, Yilun Wang, Hang Zhao

By introducing the method and metrics, we invite the community to study this novel map learning problem.

Autonomous Driving

Improving Multi-Modal Learning with Uni-Modal Teachers

no code implementations21 Jun 2021 Chenzhuang Du, Tingle Li, Yichen Liu, Zixin Wen, Tianyu Hua, Yue Wang, Hang Zhao

We name this problem Modality Failure, and hypothesize that the imbalance of modalities and the implicit bias of common objectives in fusion method prevent encoders of each modality from sufficient feature learning.

Semantic Segmentation

Improved Radar Localization on Lidar Maps Using Shared Embedding

no code implementations18 Jun 2021 Huan Yin, Yue Wang, Rong Xiong

We present a heterogeneous localization framework for solving radar global localization and pose tracking on pre-built lidar maps.

Pose Tracking

Incorporating NODE with Pre-trained Neural Differential Operator for Learning Dynamics

no code implementations8 Jun 2021 Shiqi Gong, Qi Meng, Yue Wang, Lijun Wu, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu

In this paper, to reduce the reliance on the numerical solver, we propose to enhance the supervised signal in the training of NODE.

Feature-based Style Randomization for Domain Generalization

no code implementations6 Jun 2021 Yue Wang, Lei Qi, Yinghuan Shi, Yang Gao

As a recent noticeable topic, domain generalization (DG) aims to first learn a generic model on multiple source domains and then directly generalize to an arbitrary unseen target domain without any additional adaption.

Data Augmentation Domain Generalization

Towards Modeling the Style of Translators in Neural Machine Translation

no code implementations NAACL 2021 Yue Wang, Cuong Hoang, Marcello Federico

We show that our style-augmented translation models are able to capture the style variations of translators and to generate translations with different styles on new data.

Machine Translation Translation

Deep Multi-agent Reinforcement Learning for Highway On-Ramp Merging in Mixed Traffic

2 code implementations12 May 2021 Dong Chen, Zhaojian Li, Mohammad Hajidavalloo, Kaian Chen, Yongqiang Wang, Longsheng Jiang, Yue Wang

On-ramp merging is a challenging task for autonomous vehicles (AVs), especially in mixed traffic where AVs coexist with human-driven vehicles (HDVs).

Autonomous Vehicles Multi-agent Reinforcement Learning +1

On Feature Decorrelation in Self-Supervised Learning

1 code implementation ICCV 2021 Tianyu Hua, Wenxiao Wang, Zihui Xue, Sucheng Ren, Yue Wang, Hang Zhao

In self-supervised representation learning, a common idea behind most of the state-of-the-art approaches is to enforce the robustness of the representations to predefined augmentations.

Representation Learning Self-Supervised Learning

Joint Optimization of Communications and Federated Learning Over the Air

no code implementations8 Apr 2021 Xin Fan, Yue Wang, Yan Huo, Zhi Tian

Federated learning (FL) is an attractive paradigm for making use of rich distributed data while protecting data privacy.

Federated Learning

Non-Asymptotic Analysis for Two Time-scale TDC with General Smooth Function Approximation

no code implementations NeurIPS 2021 Yue Wang, Shaofeng Zou, Yi Zhou

Temporal-difference learning with gradient correction (TDC) is a two time-scale algorithm for policy evaluation in reinforcement learning.


1-Bit Compressive Sensing for Efficient Federated Learning Over the Air

no code implementations30 Mar 2021 Xin Fan, Yue Wang, Yan Huo, Zhi Tian

For distributed learning among collaborative users, this paper develops and analyzes a communication-efficient scheme for federated learning (FL) over the air, which incorporates 1-bit compressive sensing (CS) into analog aggregation transmissions.

Compressive Sensing Dimensionality Reduction +2

HW-NAS-Bench:Hardware-Aware Neural Architecture Search Benchmark

1 code implementation19 Mar 2021 Chaojian Li, Zhongzhi Yu, Yonggan Fu, Yongan Zhang, Yang Zhao, Haoran You, Qixuan Yu, Yue Wang, Yingyan Lin

To design HW-NAS-Bench, we carefully collected the measured/estimated hardware performance of all the networks in the search spaces of both NAS-Bench-201 and FBNet, on six hardware devices that fall into three categories (i. e., commercial edge devices, FPGA, and ASIC).

Neural Architecture Search

Efficient learning of goal-oriented push-grasping synergy in clutter

1 code implementation9 Mar 2021 Kechun Xu, Hongxiang Yu, Qianen Lai, Yue Wang, Rong Xiong

In this paper, a goal-conditioned hierarchical reinforcement learning formulation with high sample efficiency is proposed to learn a push-grasping policy for grasping a specific object in clutter.

Hierarchical Reinforcement Learning Robotics

Learn to Differ: Sim2Real Small Defection Segmentation Network

no code implementations7 Mar 2021 Zexi Chen, Zheyuan Huang, Yunkai Wang, Xuecheng Xu, Yue Wang, Rong Xiong

In this paper, we propose the network SSDS that learns a way of distinguishing small defections between two images regardless of the context, so that the network can be trained once for all.

Collaborative Recognition of Feasible Region with Aerial and Ground Robots through DPCN

no code implementations1 Mar 2021 Yunshuang Li, Zheyuan Huang, Zexi Chen, Yue Wang, Rong Xiong

Taking the aerial robots' advantages of having large scale variance of view points of the same route which the ground robots is on, the collaboration work provides global information of road segmentation for the ground robot, thus enabling it to obtain feasible region and adjust its pose ahead of time.

Using Prior Knowledge to Guide BERT's Attention in Semantic Textual Matching Tasks

1 code implementation22 Feb 2021 Tingyu Xia, Yue Wang, Yuan Tian, Yi Chang

We study the problem of incorporating prior knowledge into a deep Transformer-based model, i. e., Bidirectional Encoder Representations from Transformers (BERT), to enhance its performance on semantic textual matching tasks.

Radar-to-Lidar: Heterogeneous Place Recognition via Joint Learning

1 code implementation30 Jan 2021 Huan Yin, Xuecheng Xu, Yue Wang, Rong Xiong

Place recognition is critical for both offline mapping and online localization.

SmartDeal: Re-Modeling Deep Network Weights for Efficient Inference and Training

1 code implementation4 Jan 2021 Xiaohan Chen, Yang Zhao, Yue Wang, Pengfei Xu, Haoran You, Chaojian Li, Yonggan Fu, Yingyan Lin, Zhangyang Wang

Results show that: 1) applied to inference, SD achieves up to 2. 44x energy efficiency as evaluated via real hardware implementations; 2) applied to training, SD leads to 10. 56x and 4. 48x reduction in the storage and training energy, with negligible accuracy loss compared to state-of-the-art training baselines.

SACoD: Sensor Algorithm Co-Design Towards Efficient CNN-powered Intelligent PhlatCam

1 code implementation ICCV 2021 Yonggan Fu, Yang Zhang, Yue Wang, Zhihan Lu, Vivek Boominathan, Ashok Veeraraghavan, Yingyan Lin

PhlatCam, with its form factor potentially reduced by orders of magnitude, has emerged as a promising solution to the first aforementioned challenge, while the second one remains a bottleneck.

Model Compression Neural Architecture Search

HW-NAS-Bench: Hardware-Aware Neural Architecture Search Benchmark

no code implementations ICLR 2021 Chaojian Li, Zhongzhi Yu, Yonggan Fu, Yongan Zhang, Yang Zhao, Haoran You, Qixuan Yu, Yue Wang, Cong Hao, Yingyan Lin

To design HW-NAS-Bench, we carefully collected the measured/estimated hardware performance (e. g., energy cost and latency) of all the networks in the search space of both NAS-Bench-201 and FBNet, considering six hardware devices that fall into three categories (i. e., commercial edge devices, FPGA, and ASIC).

Neural Architecture Search

FracTrain: Fractionally Squeezing Bit Savings Both Temporally and Spatially for Efficient DNN Training

1 code implementation NeurIPS 2020 Yonggan Fu, Haoran You, Yang Zhao, Yue Wang, Chaojian Li, Kailash Gopalakrishnan, Zhangyang Wang, Yingyan Lin

Recent breakthroughs in deep neural networks (DNNs) have fueled a tremendous demand for intelligent edge devices featuring on-site learning, while the practical realization of such systems remains a challenge due to the limited resources available at the edge and the required massive training costs for state-of-the-art (SOTA) DNNs.


3D Point-to-Keypoint Voting Network for 6D Pose Estimation

no code implementations22 Dec 2020 Weitong Hua, Jiaxin Guo, Yue Wang, Rong Xiong

In this paper, we propose a framework for 6D pose estimation from RGB-D data based on spatial structure characteristics of 3D keypoints.

6D Pose Estimation Computer Vision

CORAL: Colored structural representation for bi-modal place recognition

no code implementations22 Nov 2020 Yiyuan Pan, Xuecheng Xu, Weijie Li, Yunxiang Cui, Yue Wang, Rong Xiong

In this way, we fuse the structural features and visual features in the consistent bird-eye view frame, yielding a semantic representation, namely CORAL.

Cross-Media Keyphrase Prediction: A Unified Framework with Multi-Modality Multi-Head Attention and Image Wordings

1 code implementation EMNLP 2020 Yue Wang, Jing Li, Michael R. Lyu, Irwin King

Further analyses show that our multi-head attention is able to attend information from various aspects and boost classification or generation in diverse scenarios.

Self-supervised Representation Learning for Evolutionary Neural Architecture Search

1 code implementation31 Oct 2020 Chen Wei, Yiping Tang, Chuang Niu, Haihong Hu, Yue Wang, Jimin Liang

To enhance the predictive performance of neural predictors, we devise two self-supervised learning methods from different perspectives to pre-train the architecture embedding part of neural predictors to generate a meaningful representation of neural architectures.

Contrastive Learning Neural Architecture Search +2

PREGAN: Pose Randomization and Estimation for Weakly Paired Image Style Translation

1 code implementation31 Oct 2020 Zexi Chen, Jiaxin Guo, Xuecheng Xu, Yunkai Wang, Yue Wang, Rong Xiong

Utilizing the trained model under different conditions without data annotation is attractive for robot applications.

object-detection Object Detection +2

Improving the generalization of network based relative pose regression: dimension reduction as a regularizer

no code implementations24 Oct 2020 Xiaqing Ding, Yue Wang, Li Tang, Yanmei Jiao, Rong Xiong

Through experiments on real world RGBD datasets we validate the effectiveness of our design in terms of improving both generalization performance and robustness towards viewpoint change, and also show the potential of regression based visual localization networks towards challenging occasions that are difficult for geometry based visual localization methods.

3D Reconstruction Dimensionality Reduction +2

DiSCO: Differentiable Scan Context with Orientation

1 code implementation21 Oct 2020 Xuecheng Xu, Huan Yin, Zexi Chen, Yue Wang, Rong Xiong

In this paper, we propose a LiDAR-based place recognition method, named Differentiable Scan Context with Orientation (DiSCO), which simultaneously finds the scan at a similar place and estimates their relative orientation.

Pose Estimation Robot Navigation

Imitation Learning of Hierarchical Driving Model: from Continuous Intention to Continuous Trajectory

2 code implementations20 Oct 2020 Yunkai Wang, Dongkun Zhang, Jingke Wang, Zexi Chen, Yue Wang, Rong Xiong

One of the challenges to reduce the gap between the machine and the human level driving is how to endow the system with the learning capacity to deal with the coupled complexity of environments, intentions, and dynamics.


Cross-Supervised Joint-Event-Extraction with Heterogeneous Information Networks

no code implementations13 Oct 2020 Yue Wang, Zhuo Xu, Lu Bai, Yao Wan, Lixin Cui, Qian Zhao, Edwin R. Hancock, Philip S. Yu

To verify the effectiveness of our proposed method, we conduct extensive experiments on four real-world datasets as well as compare our method with state-of-the-art methods.

Event Extraction Natural Language Processing +1

Inference on tissue transplantation experiments

no code implementations6 Oct 2020 Yue Wang, Boyu Zhang, Jérémie Kropp, Nadya Morozova

This method can provide the most probable results of a group of experiments or the probability of a specific result for each experiment.

Multi-Frame to Single-Frame: Knowledge Distillation for 3D Object Detection

no code implementations24 Sep 2020 Yue Wang, Alireza Fathi, Jiajun Wu, Thomas Funkhouser, Justin Solomon

A common dilemma in 3D object detection for autonomous driving is that high-quality, dense point clouds are only available during training, but not testing.

3D Object Detection Autonomous Driving +2

RaLL: End-to-end Radar Localization on Lidar Map Using Differentiable Measurement Model

1 code implementation15 Sep 2020 Huan Yin, Runjian Chen, Yue Wang, Rong Xiong

In this paper, we propose an end-to-end deep learning framework for Radar Localization on Lidar Map (RaLL) to bridge the gap, which not only achieves the robust radar localization but also exploits the mature lidar mapping technique, thus reducing the cost of radar mapping.

Multimodal Joint Attribute Prediction and Value Extraction for E-commerce Product

2 code implementations EMNLP 2020 Tiangang Zhu, Yue Wang, Haoran Li, Youzheng Wu, Xiaodong He, Bo-Wen Zhou

We annotate a multimodal product attribute value dataset that contains 87, 194 instances, and the experimental results on this dataset demonstrate that explicitly modeling the relationship between attributes and values facilitates our method to establish the correspondence between them, and selectively utilizing visual product information is necessary for the task.

Attribute Value Extraction

Synergistic saliency and depth prediction for RGB-D saliency detection

no code implementations3 Jul 2020 Yue Wang, Yuke Li, James H. Elder, Huchuan Lu, Runmin Wu, Lu Zhang

Evaluation on seven RGB-D datasets demonstrates that even without saliency ground truth for RGB-D datasets and using only the RGB data of RGB-D datasets at inference, our semi-supervised system performs favorable against state-of-the-art fully-supervised RGB-D saliency detection methods that use saliency ground truth for RGB-D datasets at training and depth data at inference on two largest testing datasets.

Depth Estimation Saliency Detection

Finite-sample Analysis of Greedy-GQ with Linear Function Approximation under Markovian Noise

no code implementations20 May 2020 Yue Wang, Shaofeng Zou

Greedy-GQ is an off-policy two timescale algorithm for optimal control in reinforcement learning.


Learning hierarchical behavior and motion planning for autonomous driving

no code implementations8 May 2020 Jingke Wang, Yue Wang, Dongkun Zhang, Yezhou Yang, Rong Xiong

To improve the tactical decision-making for learning-based driving solution, we introduce hierarchical behavior and motion planning (HBMP) to explicitly model the behavior in learning-based solution.

Autonomous Driving Decision Making +1

SmartExchange: Trading Higher-cost Memory Storage/Access for Lower-cost Computation

no code implementations7 May 2020 Yang Zhao, Xiaohan Chen, Yue Wang, Chaojian Li, Haoran You, Yonggan Fu, Yuan Xie, Zhangyang Wang, Yingyan Lin

We present SmartExchange, an algorithm-hardware co-design framework to trade higher-cost memory storage/access for lower-cost computation, for energy-efficient inference of deep neural networks (DNNs).

Model Compression Quantization

Drawing Early-Bird Tickets: Toward More Efficient Training of Deep Networks

1 code implementation ICLR 2020 Haoran You, Chaojian Li, Pengfei Xu, Yonggan Fu, Yue Wang, Xiaohan Chen, Richard G. Baraniuk, Zhangyang Wang, Yingyan Lin

Finally, we leverage the existence of EB tickets and the proposed mask distance to develop efficient training methods, which are achieved by first identifying EB tickets via low-cost schemes, and then continuing to train merely the EB tickets towards the target accuracy.

VD-BERT: A Unified Vision and Dialog Transformer with BERT

1 code implementation EMNLP 2020 Yue Wang, Shafiq Joty, Michael R. Lyu, Irwin King, Caiming Xiong, Steven C. H. Hoi

By contrast, in this work, we propose VD-BERT, a simple yet effective framework of unified vision-dialog Transformer that leverages the pretrained BERT language models for Visual Dialog tasks.

Answer Generation Visual Dialog

Direct Speech-to-image Translation

1 code implementation7 Apr 2020 Jiguo Li, Xinfeng Zhang, Chuanmin Jia, Jizheng Xu, Li Zhang, Yue Wang, Siwei Ma, Wen Gao

In this paper, we attempt to translate the speech signals into the image signals without the transcription stage.

Multimedia Sound Audio and Speech Processing

Learning to fool the speaker recognition

1 code implementation7 Apr 2020 Jiguo Li, Xinfeng Zhang, Jizheng Xu, Li Zhang, Yue Wang, Siwei Ma, Wen Gao

Due to the widespread deployment of fingerprint/face/speaker recognition systems, attacking deep learning based biometric systems has drawn more and more attention.

Audio and Speech Processing Cryptography and Security Sound

Universal Adversarial Perturbations Generative Network for Speaker Recognition

1 code implementation7 Apr 2020 Jiguo Li, Xinfeng Zhang, Chuanmin Jia, Jizheng Xu, Li Zhang, Yue Wang, Siwei Ma, Wen Gao

Attacking deep learning based biometric systems has drawn more and more attention with the wide deployment of fingerprint/face/speaker recognition systems, given the fact that the neural networks are vulnerable to the adversarial examples, which have been intentionally perturbed to remain almost imperceptible for human.

Speaker Recognition

NPENAS: Neural Predictor Guided Evolution for Neural Architecture Search

1 code implementation28 Mar 2020 Chen Wei, Chuang Niu, Yiping Tang, Yue Wang, Haihong Hu, Jimin Liang

In this paper, we propose a neural predictor guided evolutionary algorithm to enhance the exploration ability of EA for NAS (NPENAS) and design two kinds of neural predictors.

Neural Architecture Search

Rethinking Few-Shot Image Classification: a Good Embedding Is All You Need?

3 code implementations ECCV 2020 Yonglong Tian, Yue Wang, Dilip Krishnan, Joshua B. Tenenbaum, Phillip Isola

The focus of recent meta-learning research has been on the development of learning algorithms that can quickly adapt to test time tasks with limited data and low computational cost.

Few-Shot Image Classification General Classification

A New MRAM-based Process In-Memory Accelerator for Efficient Neural Network Training with Floating Point Precision

no code implementations2 Mar 2020 Hongjie Wang, Yang Zhao, Chaojian Li, Yue Wang, Yingyan Lin

The excellent performance of modern deep neural networks (DNNs) comes at an often prohibitive training cost, limiting the rapid development of DNN innovations and raising various environmental concerns.

DNN-Chip Predictor: An Analytical Performance Predictor for DNN Accelerators with Various Dataflows and Hardware Architectures

no code implementations26 Feb 2020 Yang Zhao, Chaojian Li, Yue Wang, Pengfei Xu, Yongan Zhang, Yingyan Lin

The recent breakthroughs in deep neural networks (DNNs) have spurred a tremendously increased demand for DNN accelerators.

When Relation Networks meet GANs: Relation GANs with Triplet Loss

1 code implementation24 Feb 2020 Runmin Wu, Kunyao Zhang, Lijun Wang, Yue Wang, Pingping Zhang, Huchuan Lu, Yizhou Yu

Though recent research has achieved remarkable progress in generating realistic images with generative adversarial networks (GANs), the lack of training stability is still a lingering concern of most GANs, especially on high-resolution inputs and complex datasets.

Conditional Image Generation Translation

COKE: Communication-Censored Decentralized Kernel Learning

no code implementations28 Jan 2020 Ping Xu, Yue Wang, Xiang Chen, Zhi Tian

This paper studies the decentralized optimization and learning problem where multiple interconnected agents aim to learn an optimal decision function defined over a reproducing kernel Hilbert space by jointly minimizing a global objective function, with access to their own locally observed dataset.

AutoDNNchip: An Automated DNN Chip Predictor and Builder for Both FPGAs and ASICs

1 code implementation6 Jan 2020 Pengfei Xu, Xiaofan Zhang, Cong Hao, Yang Zhao, Yongan Zhang, Yue Wang, Chaojian Li, Zetong Guan, Deming Chen, Yingyan Lin

Specifically, AutoDNNchip consists of two integrated enablers: (1) a Chip Predictor, built on top of a graph-based accelerator representation, which can accurately and efficiently predict a DNN accelerator's energy, throughput, and area based on the DNN model parameters, hardware configuration, technology-based IPs, and platform constraints; and (2) a Chip Builder, which can automatically explore the design space of DNN chips (including IP selection, block configuration, resource balancing, etc.

Fractional Skipping: Towards Finer-Grained Dynamic CNN Inference

1 code implementation3 Jan 2020 Jianghao Shen, Yonggan Fu, Yue Wang, Pengfei Xu, Zhangyang Wang, Yingyan Lin

The core idea of DFS is to hypothesize layer-wise quantization (to different bitwidths) as intermediate "soft" choices to be made between fully utilizing and skipping a layer.


Reducing Selection Bias in Counterfactual Reasoning for Individual Treatment Effects Estimation

no code implementations19 Dec 2019 Zichen Zhang, Qingfeng Lan, Lei Ding, Yue Wang, Negar Hassanpour, Russell Greiner

We learn two groups of latent random variables, where one group corresponds to variables that only cause selection bias, and the other group is relevant for outcome prediction.

Selection bias

Weakly-Supervised Road Affordances Inference and Learning in Scenes without Traffic Signs

1 code implementation27 Nov 2019 Huifang Ma, Yue Wang, Rong Xiong, Sarath Kodagoda, Qianhui Luo

Road attributes understanding is extensively researched to support vehicle's action for autonomous driving, whereas current works mainly focus on urban road nets and rely much on traffic signs.


Generative Temporal Link Prediction via Self-tokenized Sequence Modeling

no code implementations26 Nov 2019 Yue Wang, Chenwei Zhang, Shen Wang, Philip S. Yu, Lu Bai, Lixin Cui, Guandong Xu

We formalize networks with evolving structures as temporal networks and propose a generative link prediction model, Generative Link Sequence Modeling (GLSM), to predict future links for temporal networks.

Link Prediction

E2-Train: Training State-of-the-art CNNs with Over 80% Energy Savings

no code implementations NeurIPS 2019 Yue Wang, Ziyu Jiang, Xiaohan Chen, Pengfei Xu, Yang Zhao, Yingyan Lin, Zhangyang Wang

Extensive simulations and ablation studies, with real energy measurements from an FPGA board, confirm the superiority of our proposed strategies and demonstrate remarkable energy savings for training.

PRNet: Self-Supervised Learning for Partial-to-Partial Registration

3 code implementations NeurIPS 2019 Yue Wang, Justin M. Solomon

We present a simple, flexible, and general framework titled Partial Registration Network (PRNet), for partial-to-partial point cloud registration.

Point Cloud Registration Self-Supervised Learning

Entropic Dynamic Time Warping Kernels for Co-evolving Financial Time Series Analysis

no code implementations21 Oct 2019 Lu Bai, Lixin Cui, Lixiang Xu, Yue Wang, Zhihong Zhang, Edwin R. Hancock

With the dominant entropy time series for each pair of financial networks to hand, we develop a similarity measure based on the classical dynamic time warping framework, for analyzing the financial time-varying networks.

Dynamic Time Warping Time Series +1

Representation Learning of EHR Data via Graph-Based Medical Entity Embedding

no code implementations7 Oct 2019 Tong Wu, Yunlong Wang, Yue Wang, Emily Zhao, Yilian Yuan, Zhi Yang

Automatic representation learning of key entities in electronic health record (EHR) data is a critical step for healthcare informatics that turns heterogeneous medical records into structured and actionable information.

Graph Embedding

Drawing Early-Bird Tickets: Towards More Efficient Training of Deep Networks

1 code implementation26 Sep 2019 Haoran You, Chaojian Li, Pengfei Xu, Yonggan Fu, Yue Wang, Xiaohan Chen, Richard G. Baraniuk, Zhangyang Wang, Yingyan Lin

In this paper, we discover for the first time that the winning tickets can be identified at the very early training stage, which we term as early-bird (EB) tickets, via low-cost training schemes (e. g., early stopping and low-precision training) at large learning rates.

Enhancing Model Interpretability and Accuracy for Disease Progression Prediction via Phenotype-Based Patient Similarity Learning

no code implementations26 Sep 2019 Yue Wang, Tong Wu, Yunlong Wang, Gao Wang

Models have been proposed to extract temporal patterns from longitudinal electronic health records (EHR) for clinical predictive models.

Path Space for Recurrent Neural Networks with ReLU Activations

no code implementations25 Sep 2019 Yue Wang, Qi Meng, Wei Chen, YuTing Liu, Zhi-Ming Ma, Tie-Yan Liu

Optimization algorithms like stochastic gradient descent that optimize the neural networks in the vector space of weights, which are not positively scale-invariant.

Respect Your Emotion: Human-Multi-Robot Teaming based on Regret Decision Model

no code implementations18 Sep 2019 Longsheng Jiang, Yue Wang

This work studies the human-like characteristics brought by regret emotion in one-human-multi-robot teaming for the application of domain search.

Decision Making

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking

no code implementations13 Aug 2019 Yue Wang, Yao Wan, Chenwei Zhang, Lixin Cui, Lu Bai, Philip S. Yu

During the iterations, our model updates the parallel policies and the corresponding scenario-based regrets for agents simultaneously.

Decision Making Multi-agent Reinforcement Learning +1

EmotionX-HSU: Adopting Pre-trained BERT for Emotion Classification

no code implementations23 Jul 2019 Linkai Luo, Yue Wang

This paper describes our approach to the EmotionX-2019, the shared task of SocialNLP 2019.

Classification Emotion Classification +1

Dual Dynamic Inference: Enabling More Efficient, Adaptive and Controllable Deep Inference

no code implementations10 Jul 2019 Yue Wang, Jianghao Shen, Ting-Kuei Hu, Pengfei Xu, Tan Nguyen, Richard Baraniuk, Zhangyang Wang, Yingyan Lin

State-of-the-art convolutional neural networks (CNNs) yield record-breaking predictive performance, yet at the cost of high-energy-consumption inference, that prohibits their widely deployments in resource-constrained Internet of Things (IoT) applications.

Topic-Aware Neural Keyphrase Generation for Social Media Language

2 code implementations ACL 2019 Yue Wang, Jing Li, Hou Pong Chan, Irwin King, Michael R. Lyu, Shuming Shi

Further discussions show that our model learns meaningful topics, which interprets its superiority in social media keyphrase generation.

Keyphrase Generation

Towards navigation without precise localization: Weakly supervised learning of goal-directed navigation cost map

1 code implementation6 Jun 2019 Huifang Ma, Yue Wang, Li Tang, Sarath Kodagoda, Rong Xiong

Autonomous navigation based on precise localization has been widely developed in both academic research and practical applications.


LambdaOpt: Learn to Regularize Recommender Models in Finer Levels

1 code implementation28 May 2019 Yihong Chen, Bei Chen, Xiangnan He, Chen Gao, Yong Li, Jian-Guang Lou, Yue Wang

We show how to employ LambdaOpt on matrix factorization, a classical model that is representative of a large family of recommender models.

Hyperparameter Optimization Recommendation Systems

Fourier-based Rotation-invariant Feature Boosting: An Efficient Framework for Geospatial Object Detection

no code implementations27 May 2019 Xin Wu, Danfeng Hong, Jocelyn Chanussot, Yang Xu, Ran Tao, Yue Wang

To this end, we propose a novel and efficient framework for geospatial object detection in this letter, called Fourier-based rotation-invariant feature boosting (FRIFB).

object-detection Object Detection

Microblog Hashtag Generation via Encoding Conversation Contexts

1 code implementation NAACL 2019 Yue Wang, Jing Li, Irwin King, Michael R. Lyu, Shuming Shi

Automatic hashtag annotation plays an important role in content understanding for microblog posts.

Topic Models

Deep Closest Point: Learning Representations for Point Cloud Registration

4 code implementations ICCV 2019 Yue Wang, Justin M. Solomon

To address local optima and other difficulties in the ICP pipeline, we propose a learning-based method, titled Deep Closest Point (DCP), inspired by recent techniques in computer vision and natural language processing.

Computer Vision Natural Language Processing +1

A Medical Literature Search System for Identifying Effective Treatments in Precision Medicine

no code implementations16 Apr 2019 Jiaming Qu, Yue Wang

We then improve precision by promoting treatment-related publications to the top using a machine learning reranker trained on 2017 Text Retrieval Conference Precision Medicine (PM) track corpus.

Fused Lasso for Feature Selection using Structural Information

no code implementations26 Feb 2019 Lu Bai, Lixin Cui, Yue Wang, Philip S. Yu, Edwin R. Hancock

To overcome these issues, we propose a new feature selection method using structural correlation between pairwise samples.

feature selection Time Series +1

An Adaptive Deep Learning Algorithm Based Autoencoder for Interference Channels

no code implementations18 Feb 2019 Dehao Wu, Maziar Nekovee, Yue Wang

Based on a characterization of a k-user Gaussian interference channel, where the interferences are classified as different levels from weak to very strong interferences based on a coupling parameter {\alpha}, a DL neural network (NN) based autoencoder is designed to train the data set and decode the received signals.

EnergyNet: Energy-Efficient Dynamic Inference

no code implementations NIPS Workshop CDNNRIA 2018 Yue Wang, Tan Nguyen, Yang Zhao, Zhangyang Wang, Yingyan Lin, Richard Baraniuk

The prohibitive energy cost of running high-performance Convolutional Neural Networks (CNNs) has been limiting their deployment on resource-constrained platforms including mobile and wearable devices.

A Human-Computer Interface Design for Quantitative Measure of Regret Theory

1 code implementation30 Sep 2018 Longsheng Jiang, Yue Wang

The key of obtaining a quantitative model of regret theory is to measure the preference in humans' mind when they choose among a set of options.

Human-Computer Interaction

Target Transfer Q-Learning and Its Convergence Analysis

no code implementations21 Sep 2018 Yue Wang, Qi Meng, Wei Cheng, Yuting Liug, Zhi-Ming Ma, Tie-Yan Liu

In this paper, we propose to transfer the Q-function learned in the source task to the target of the Q-learning in the new task when certain safe conditions are satisfied.

Q-Learning Transfer Learning

Identifying The Most Informative Features Using A Structurally Interacting Elastic Net

no code implementations8 Sep 2018 Lixin Cui, Lu Bai, Zhihong Zhang, Yue Wang, Edwin R. Hancock

With the feature graphs to hand, we propose a new information theoretic criterion to measure the joint relevance of different pairwise feature combinations with respect to the target feature graph representation.

feature selection

Trust-based Multi-Robot Symbolic Motion Planning with a Human-in-the-Loop

1 code implementation15 Aug 2018 Yue Wang, Laura R. Humphrey, Zhanrui Liao, Huanfei Zheng

In this paper, distributed symbolic motion planning for multi-robot systems is developed to address scalability.


Deep k-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions

1 code implementation ICML 2018 Junru Wu, Yue Wang, Zhen-Yu Wu, Zhangyang Wang, Ashok Veeraraghavan, Yingyan Lin

The current trend of pushing CNNs deeper with convolutions has created a pressing demand to achieve higher compression gains on CNNs where convolutions dominate the computation and parameter amount (e. g., GoogLeNet, ResNet and Wide ResNet).

Deep $k$-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions

1 code implementation24 Jun 2018 Junru Wu, Yue Wang, Zhen-Yu Wu, Zhangyang Wang, Ashok Veeraraghavan, Yingyan Lin

The current trend of pushing CNNs deeper with convolutions has created a pressing demand to achieve higher compression gains on CNNs where convolutions dominate the computation and parameter amount (e. g., GoogLeNet, ResNet and Wide ResNet).

Learning-to-Ask: Knowledge Acquisition via 20 Questions

no code implementations22 Jun 2018 Yihong Chen, Bei Chen, Xuguang Duan, Jian-Guang Lou, Yue Wang, Wenwu Zhu, Yong Cao

Almost all the knowledge empowered applications rely upon accurate knowledge, which has to be either collected manually with high cost, or extracted automatically with unignorable errors.

Im2Avatar: Colorful 3D Reconstruction from a Single Image

1 code implementation17 Apr 2018 Yongbin Sun, Ziwei Liu, Yue Wang, Sanjay E. Sarma

In this work, we study a new problem, that is, simultaneously recovering 3D shape and surface color from a single image, namely "colorful 3D reconstruction".

3D Reconstruction

Differentially Private Confidence Intervals for Empirical Risk Minimization

no code implementations11 Apr 2018 Yue Wang, Daniel Kifer, Jaewoo Lee

The process of data mining with differential privacy produces results that are affected by two types of noise: sampling noise due to data collection and privacy noise that is designed to prevent the reconstruction of sensitive information.

Bounded Policy Synthesis for POMDPs with Safe-Reachability Objectives

no code implementations29 Jan 2018 Yue Wang, Swarat Chaudhuri, Lydia E. Kavraki

In this work, we study POMDPs with safe-reachability objectives, which require that with a probability above some threshold, a goal state is eventually reached while keeping the probability of visiting unsafe states below some threshold.

Dynamic Graph CNN for Learning on Point Clouds

14 code implementations24 Jan 2018 Yue Wang, Yongbin Sun, Ziwei Liu, Sanjay E. Sarma, Michael M. Bronstein, Justin M. Solomon

Point clouds provide a flexible geometric representation suitable for countless applications in computer graphics; they also comprise the raw output of most 3D data acquisition devices.

3D Part Segmentation 3D Point Cloud Classification +2

LocNet: Global localization in 3D point clouds for mobile vehicles

1 code implementation6 Dec 2017 Huan Yin, Li Tang, Xiaqing Ding, Yue Wang, Rong Xiong

Global localization in 3D point clouds is a challenging problem of estimating the pose of vehicles without any prior knowledge.

Pose Estimation Representation Learning

Code Completion with Neural Attention and Pointer Networks

1 code implementation27 Nov 2017 Jian Li, Yue Wang, Michael R. Lyu, Irwin King

Intelligent code completion has become an essential research task to accelerate modern software development.

Code Completion

3D-SSD: Learning Hierarchical Features from RGB-D Images for Amodal 3D Object Detection

no code implementations1 Nov 2017 Qianhui Luo, Huifang Ma, Yue Wang, Li Tang, Rong Xiong

This paper aims at developing a faster and a more accurate solution to the amodal 3D object detection problem for indoor scenes.

3D Object Detection object-detection

Convergence Analysis of Distributed Stochastic Gradient Descent with Shuffling

no code implementations29 Sep 2017 Qi Meng, Wei Chen, Yue Wang, Zhi-Ming Ma, Tie-Yan Liu

First, we give a mathematical formulation for the practical data processing procedure in distributed machine learning, which we call data partition with global/local shuffling.

End-to-end Learning for Short Text Expansion

no code implementations30 Aug 2017 Jian Tang, Yue Wang, Kai Zheng, Qiaozhu Mei

A novel deep memory network is proposed to automatically find relevant information from a collection of longer documents and reformulate the short text through a gating mechanism.

Recommendation Systems Text Classification

Maximum Volume Inscribed Ellipsoid: A New Simplex-Structured Matrix Factorization Framework via Facet Enumeration and Convex Optimization

no code implementations9 Aug 2017 Chia-Hsiang Lin, Ruiyuan Wu, Wing-Kin Ma, Chong-Yung Chi, Yue Wang

This maximum volume inscribed ellipsoid (MVIE) idea has not been attempted in prior literature, and we show a sufficient condition under which the MVIE framework guarantees exact recovery of the factors.

Hyperspectral Unmixing

Graphical Time Warping for Joint Alignment of Multiple Curves

no code implementations NeurIPS 2016 Yizhi Wang, David J. Miller, Kira Poskanzer, Yue Wang, Lin Tian, Guoqiang Yu

We name the proposed approach graphical time warping (GTW), emphasizing the graphical nature of the solution and that the dependency structure of the warping functions can be represented by a graph.

Dynamic Time Warping Time Series +1

Parse Geometry from a Line: Monocular Depth Estimation with Partial Laser Observation

4 code implementations17 Oct 2016 Yiyi Liao, Lichao Huang, Yue Wang, Sarath Kodagoda, Yinan Yu, Yong liu

Many standard robotic platforms are equipped with at least a fixed 2D laser range finder and a monocular camera.

Depth Completion

Generalization Error Bounds for Optimization Algorithms via Stability

no code implementations27 Sep 2016 Qi Meng, Yue Wang, Wei Chen, Taifeng Wang, Zhi-Ming Ma, Tie-Yan Liu

Many machine learning tasks can be formulated as Regularized Empirical Risk Minimization (R-ERM), and solved by optimization algorithms such as gradient descent (GD), stochastic gradient descent (SGD), and stochastic variance reduction (SVRG).

Understand Scene Categories by Objects: A Semantic Regularized Scene Classifier Using Convolutional Neural Networks

no code implementations22 Sep 2015 Yiyi Liao, Sarath Kodagoda, Yue Wang, Lei Shi, Yong liu

As scene images have larger diversity than the iconic object images, it is more challenging for deep learning methods to automatically learn features from scene images with less samples.

Classification General Classification +3

Place classification with a graph regularized deep neural network model

no code implementations12 Jun 2015 Yiyi Liao, Sarath Kodagoda, Yue Wang, Lei Shi, Yong liu

Furthermore, results show that the features automatically learned from the raw input range data can achieve competitive results to the features constructed based on statistical and geometrical information.

Classification General Classification

Algorithms for determining transposons in gene sequences

1 code implementation8 Jun 2015 Yue Wang

Thus for different individuals of the same species, the orders of genes might be different.

A feasible roadmap for developing volumetric probability atlas of localized prostate cancer

no code implementations15 Sep 2014 Liang Zhao, Jianhua Xuan, Yue Wang

A statistical volumetric model, showing the probability map of localized prostate cancer within the host anatomical structure, has been developed from 90 optically-imaged surgical specimens.

Convex Analysis of Mixtures for Separating Non-negative Well-grounded Sources

no code implementations28 Jun 2014 Yitan Zhu, Niya Wang, David J. Miller, Yue Wang

We prove a sufficient and necessary condition for identifying the mixing matrix through edge detection, which also serves as the foundation for CAM to be applied not only to the exact-determined and over-determined cases, but also to the under-determined case.

Edge Detection

Image Representation Learning Using Graph Regularized Auto-Encoders

no code implementations3 Dec 2013 Yiyi Liao, Yue Wang, Yong liu

We consider the problem of image representation for the tasks of unsupervised learning and semi-supervised learning.

Image Clustering Representation Learning

A feasible roadmap for unsupervised deconvolution of two-source mixed gene expressions

no code implementations25 Oct 2013 Niya Wang, Eric P. Hoffman, Robert Clarke, Zhen Zhang, David M. Herrington, Ie-Ming Shih, Douglas A. Levine, Guoqiang Yu, Jianhua Xuan, Yue Wang

Tissue heterogeneity is a major confounding factor in studying individual populations that cannot be resolved directly by global profiling.

Unsupervised deconvolution of dynamic imaging reveals intratumor vascular heterogeneity

no code implementations14 Jun 2013 Li Chen, Peter L . Choyke, Niya Wang, Robert Clarke, Zaver M. Bhujwalla, Elizabeth M. C. Hillman, Yue Wang

Intratumor heterogeneity is often manifested by vascular compartments with distinct pharmacokinetics that cannot be resolved directly by in vivo dynamic imaging.

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