Ke Wang

Computer Assisted Translation with Neural Quality Estimation and Automatic Post-Editing

With the advent of neural machine translation, there has been a marked s...
09/19/2020 ∙ by Ke Wang, et al. ∙ 6 ∙ share

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Approaches, Challenges, and Applications for Deep Visual Odometry: Toward to Complicated and Emerging Areas

Visual odometry (VO) is a prevalent way to deal with the relative locali...
09/06/2020 ∙ by Ke Wang, et al. ∙ 4 ∙ share

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Statistical inference for principal components of spiked covariance matrices

In this paper, we study the asymptotic behavior of the extreme eigenvalu...
08/27/2020 ∙ by Zhigang Bao, et al. ∙ 0 ∙ share

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Revisiting Adversarially Learned Injection Attacks Against Recommender Systems

Recommender systems play an important role in modern information and e-c...
08/11/2020 ∙ by Jiaxi Tang, et al. ∙ 10 ∙ share

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A Design of Cooperative Overtaking Based on Complex Lane Detection and Collision Risk Estimation

Cooperative overtaking is believed to have the capability of improving r...
08/11/2020 ∙ by Junlan Chen, et al. ∙ 0 ∙ share

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CG-SENSE revisited: Results from the first ISMRM reproducibility challenge

Purpose: The aim of this work is to shed light on the issue of reproduci...
08/10/2020 ∙ by Oliver Maier, et al. ∙ 0 ∙ share

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A feature-supervised generative adversarial network for environmental monitoring during hazy days

The adverse haze weather condition has brought considerable difficulties...
08/05/2020 ∙ by Ke Wang, et al. ∙ 18 ∙ share

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The Adaptability and Challenges of Autonomous Vehicles to Pedestrians in Urban China

China is the world's largest automotive market and is ambitious for auto...
07/27/2020 ∙ by Ke Wang, et al. ∙ 0 ∙ share

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Time-aware Graph Embedding: A temporal smoothness and task-oriented approach

Knowledge graph embedding, which aims to learn the low-dimensional repre...
07/22/2020 ∙ by Yonghui Xu, et al. ∙ 1 ∙ share

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Asynchronous Real-Time Optimization of Footstep Placement and Timing in Bipedal Walking Robots

Online footstep planning is essential for bipedal walking robots to be a...
07/01/2020 ∙ by Digby Chappell, et al. ∙ 0 ∙ share

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Relative Pose Estimation for Stereo Rolling Shutter Cameras

In this paper, we present a novel linear algorithm to estimate the 6 DoF...
06/14/2020 ∙ by Ke Wang, et al. ∙ 0 ∙ share

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Learning Semantic Program Embeddings with Graph Interval Neural Network

Learning distributed representations of source code has been a challengi...
05/18/2020 ∙ by Yu Wang, et al. ∙ 0 ∙ share

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Learning Semantic Program Embeddings with GraphInterval Neural Network

Learning distributed representations of source code has been a challengi...
05/18/2020 ∙ by Yu Wang, et al. ∙ 0 ∙ share

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Robust Visual Object Tracking with Two-Stream Residual Convolutional Networks

The current deep learning based visual tracking approaches have been ver...
05/13/2020 ∙ by Ning Zhang, et al. ∙ 11 ∙ share

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CF2-Net: Coarse-to-Fine Fusion Convolutional Network for Breast Ultrasound Image Segmentation

Breast ultrasound (BUS) image segmentation plays a crucial role in a com...
03/23/2020 ∙ by Zhenyuan Ning, et al. ∙ 6 ∙ share

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IStego100K: Large-scale Image Steganalysis Dataset

In order to promote the rapid development of image steganalysis technolo...
11/13/2019 ∙ by Zhongliang Yang, et al. ∙ 0 ∙ share

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FlowNorm: A Learning-based Method for Increasing Convergence Range of Direct Alignment

Many approaches have been proposed to estimate camera poses by directly ...
10/16/2019 ∙ by Ke Wang, et al. ∙ 0 ∙ share

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AI Benchmark: All About Deep Learning on Smartphones in 2019

The performance of mobile AI accelerators has been evolving rapidly in t...
10/15/2019 ∙ by Andrey Ignatov, et al. ∙ 0 ∙ share

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SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference

We present a modern scalable reinforcement learning agent called SEED (S...
10/15/2019 ∙ by Lasse Espeholt, et al. ∙ 0 ∙ share

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Differentially Private Survival Function Estimation

Survival function estimation is used in many disciplines, but it is most...
10/04/2019 ∙ by Lovedeep Gondara, et al. ∙ 0 ∙ share

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Testing Neural Program Analyzers

Deep neural networks have been increasingly used in software engineering...
08/25/2019 ∙ by Md Rafiqul Islam Rabin, et al. ∙ 0 ∙ share

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Testing Neural Programs

Deep neural networks have been increasingly used in software engineering...
08/25/2019 ∙ by Md Rafiqul Islam Rabin, et al. ∙ 0 ∙ share

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Principal components of spiked covariance matrices in the supercritical regime

In this paper, we study the asymptotic behavior of the extreme eigenvalu...
07/29/2019 ∙ by Zhigang Bao, et al. ∙ 0 ∙ share

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Learning a Static Bug Finder from Data

Static analysis is an effective technique to catch bugs early when they ...
07/12/2019 ∙ by Yu Wang, et al. ∙ 0 ∙ share

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Learning Blended, Precise Semantic Program Embeddings

Learning neural program embeddings is key to utilizing deep neural netwo...
07/03/2019 ∙ by Ke Wang, et al. ∙ 0 ∙ share

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A Hybrid Approach for Learning Program Representations

Learning neural program embedding is the key to utilizing deep neural ne...
07/03/2019 ∙ by Ke Wang, et al. ∙ 0 ∙ share

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TS-RNN: Text Steganalysis Based on Recurrent Neural Networks

With the rapid development of natural language processing technologies, ...
05/30/2019 ∙ by Zhongliang Yang, et al. ∙ 0 ∙ share

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Controllable Unsupervised Text Attribute Transfer via Editing Entangled Latent Representation

Unsupervised text attribute transfer automatically transforms a text to ...
05/30/2019 ∙ by Ke Wang, et al. ∙ 0 ∙ share

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COSET: A Benchmark for Evaluating Neural Program Embeddings

Neural program embedding can be helpful in analyzing large software, a t...
05/27/2019 ∙ by Ke Wang, et al. ∙ 0 ∙ share

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Learning Scalable and Precise Representation of Program Semantics

Neural program embedding has shown potential in aiding the analysis of l...
05/13/2019 ∙ by Ke Wang, et al. ∙ 0 ∙ share

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Machine Learning for Classification of Protein Helix Capping Motifs

The biological function of a protein stems from its 3-dimensional struct...
05/01/2019 ∙ by Sean Mullane, et al. ∙ 0 ∙ share

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Reduce Transmission Delay for Cache-Aided Two-Layer Network

In this paper, we consider a two-layer caching-aided network, where a si...
01/10/2019 ∙ by Ke Wang, et al. ∙ 0 ∙ share

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Enhanced Expressive Power and Fast Training of Neural Networks by Random Projections

Random projections are able to perform dimension reduction efficiently f...
11/22/2018 ∙ by Jian-Feng Cai, et al. ∙ 0 ∙ share

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AI Benchmark: Running Deep Neural Networks on Android Smartphones

Over the last years, the computational power of mobile devices such as s...
10/02/2018 ∙ by Andrey Ignatov, et al. ∙ 14 ∙ share

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Singular vector and singular subspace distribution for the matrix denoising model

In this paper, we study the matrix denosing model Y=S+X, where S is a lo...
09/27/2018 ∙ by Zhigang Bao, et al. ∙ 0 ∙ share

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Ranking Distillation: Learning Compact Ranking Models With High Performance for Recommender System

We propose a novel way to train ranking models, such as recommender syst...
09/19/2018 ∙ by Jiaxi Tang, et al. ∙ 0 ∙ share

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Personalized Top-N Sequential Recommendation via Convolutional Sequence Embedding

Top-N sequential recommendation models each user as a sequence of items ...
09/19/2018 ∙ by Jiaxi Tang, et al. ∙ 0 ∙ share

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Reconstruction and Registration of Large-Scale Medical Scene Using Point Clouds Data from Different Modalities

Sensing the medical scenario can ensure the safety during the surgical o...
09/05/2018 ∙ by Ke Wang, et al. ∙ 0 ∙ share

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Empirical Evaluation of Speaker Adaptation on DNN based Acoustic Model

Speaker adaptation aims to estimate a speaker specific acoustic model fr...
03/27/2018 ∙ by Ke Wang, et al. ∙ 0 ∙ share

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Investigating Generative Adversarial Networks based Speech Dereverberation for Robust Speech Recognition

We investigate the use of generative adversarial networks (GANs) in spee...
03/27/2018 ∙ by Ke Wang, et al. ∙ 0 ∙ share

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Random perturbation and matrix sparsification and completion

We discuss general perturbation inequalities when the perturbation is ra...
03/02/2018 ∙ by Sean O'Rourke, et al. ∙ 0 ∙ share

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Recovering Loss to Followup Information Using Denoising Autoencoders

Loss to followup is a significant issue in healthcare and has serious co...
02/12/2018 ∙ by Lovedeep Gondara, et al. ∙ 0 ∙ share

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The Capacity on Degraded Relay Broadcast Channel

The relay broadcast channel (RBC) is considered, in which a transmitter ...
01/03/2018 ∙ by Ke Wang, et al. ∙ 0 ∙ share

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Dynamic Neural Program Embedding for Program Repair

Neural program embeddings have shown much promise recently for a variety...
11/20/2017 ∙ by Ke Wang, et al. ∙ 0 ∙ share

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Interactive, Intelligent Tutoring for Auxiliary Constructions in Geometry Proofs

Geometry theorem proving forms a major and challenging component in the ...
11/20/2017 ∙ by Ke Wang, et al. ∙ 0 ∙ share

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Data-Driven Feedback Generation for Introductory Programming Exercises

This paper introduces the "Search, Align, and Repair" data-driven progra...
11/20/2017 ∙ by Ke Wang, et al. ∙ 0 ∙ share

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Constructing Top-k Routes with Personalized Submodular Maximization of POI Features

We consider a practical top-k route problem: given a collection of point...
10/10/2017 ∙ by Hongwei Liang, et al. ∙ 0 ∙ share

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Multiple Imputation Using Deep Denoising Autoencoders

Missing data is a well-recognized problem impacting all domains. State-o...
05/08/2017 ∙ by Lovedeep Gondara, et al. ∙ 0 ∙ share

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Detailed Garment Recovery from a Single-View Image

Most recent garment capturing techniques rely on acquiring multiple view...
08/03/2016 ∙ by Shan Yang, et al. ∙ 0 ∙ share

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Domain Transfer Multi-Instance Dictionary Learning

In this paper, we invest the domain transfer learning problem with multi...
05/26/2016 ∙ by Ke Wang, et al. ∙ 0 ∙ share

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Ke Wang

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