Search Results for author: Shuai Wang

Found 154 papers, 44 papers with code

Automatic recognition of abdominal lymph nodes from clinical text

1 code implementation EMNLP (ClinicalNLP) 2020 Yifan Peng, SungWon Lee, Daniel C. Elton, Thomas Shen, Yu-Xing Tang, Qingyu Chen, Shuai Wang, Yingying Zhu, Ronald Summers, Zhiyong Lu

We then introduce an end-to-end approach based on the combination of rules and transformer-based methods to detect these abdominal lymph node mentions and classify their types from the MRI radiology reports.

Accurate Segmentation of Optic Disc And Cup from Multiple Pseudo-labels by Noise-Aware Learning

1 code implementation30 Nov 2023 Tengjin Weng, Yang shen, Zhidong Zhao, Zhiming Cheng, Shuai Wang

The training framework of the MPNN is constructed by a teacher-student architecture to learn segmentation from clean pixels and noisy pixels.

Denoising Segmentation

PMP-Swin: Multi-Scale Patch Message Passing Swin Transformer for Retinal Disease Classification

no code implementations20 Nov 2023 Zhihan Yang, Zhiming Cheng, Tengjin Weng, Shucheng He, Yaqi Wang, Xin Ye, Shuai Wang

Specifically, we design a Patch Message Passing (PMP) module based on the Message Passing mechanism to establish global interaction for pathological semantic features and to exploit the subtle differences further between different diseases.

Multi-class Classification

FDNet: Feature Decoupled Segmentation Network for Tooth CBCT Image

no code implementations11 Nov 2023 Xiang Feng, Chengkai Wang, Chengyu Wu, Yunxiang Li, Yongbo He, Shuai Wang, Yaiqi Wang

Precise Tooth Cone Beam Computed Tomography (CBCT) image segmentation is crucial for orthodontic treatment planning.

Image Segmentation Segmentation +1

Privacy-preserving Federated Primal-dual Learning for Non-convex and Non-smooth Problems with Model Sparsification

no code implementations30 Oct 2023 Yiwei Li, Chien-Wei Huang, Shuai Wang, Chong-Yung Chi, Tony Q. S. Quek

Federated learning (FL) has been recognized as a rapidly growing research area, where the model is trained over massively distributed clients under the orchestration of a parameter server (PS) without sharing clients' data.

Federated Learning Privacy Preserving

SparseByteNN: A Novel Mobile Inference Acceleration Framework Based on Fine-Grained Group Sparsity

no code implementations30 Oct 2023 Haitao Xu, Songwei Liu, Yuyang Xu, Shuai Wang, Jiashi Li, Chenqian Yan, Liangqiang Li, Lean Fu, Xin Pan, Fangmin Chen

Our framework consists of two parts: (a) A fine-grained kernel sparsity schema with a sparsity granularity between structured pruning and unstructured pruning.

Network Pruning

PC-bzip2: a phase-space continuity enhanced lossless compression algorithm for light field microscopy data

no code implementations14 Oct 2023 Changqing Su, Zihan Lin, You Zhou, Shuai Wang, Yuhan Gao, Chenggang Yan, Bo Xiong

Moreover, by introducing the temporal continuity, our method shows the superior compression ratio on time series data of zebrafish blood vessels.

Benchmarking and Explaining Large Language Model-based Code Generation: A Causality-Centric Approach

1 code implementation10 Oct 2023 Zhenlan Ji, Pingchuan Ma, Zongjie Li, Shuai Wang

We illustrate the insights that our framework can provide by studying over 3 popular LLMs with over 12 prompt adjustment strategies.

Benchmarking Code Generation +2

Split and Merge: Aligning Position Biases in Large Language Model based Evaluators

no code implementations29 Sep 2023 Zongjie Li, Chaozheng Wang, Pingchuan Ma, Daoyuan Wu, Shuai Wang, Cuiyun Gao, Yang Liu

Specifically, PORTIA splits the answers into multiple segments, aligns similar content across candidate answers, and then merges them back into a single prompt for evaluation by LLMs.

Language Modelling Large Language Model

Biomedical Image Splicing Detection using Uncertainty-Guided Refinement

no code implementations28 Sep 2023 Xun Lin, Wenzhong Tang, Shuai Wang, Zitong Yu, Yizhong Liu, Haoran Wang, Ying Fu, Alex Kot

Besides, we construct a dataset for Biomedical image Splicing (BioSp) detection, which consists of 1, 290 spliced images.

Image Forensics Image Manipulation

AutoPrep: An Automatic Preprocessing Framework for In-the-Wild Speech Data

no code implementations25 Sep 2023 Jianwei Yu, Hangting Chen, Yanyao Bian, Xiang Li, Yi Luo, Jinchuan Tian, Mengyang Liu, Jiayi Jiang, Shuai Wang

To address this issue, we introduce an automatic in-the-wild speech data preprocessing framework (AutoPrep) in this paper, which is designed to enhance speech quality, generate speaker labels, and produce transcriptions automatically.

Automatic Speech Recognition Speech Enhancement +3

Multiple Satellites Collaboration for Joint Code-aided CFOs and CPOs Estimation

no code implementations22 Sep 2023 Pingyue Yue, Yixuan Li, Yue Li, Rui Zhang, Shuai Wang, Jianping An

Low Earth Orbit (LEO) satellites are being extensively researched in the development of secure Internet of Remote Things (IoRT).

Leveraging In-the-Wild Data for Effective Self-Supervised Pretraining in Speaker Recognition

1 code implementation21 Sep 2023 Shuai Wang, Qibing Bai, Qi Liu, Jianwei Yu, Zhengyang Chen, Bing Han, Yanmin Qian, Haizhou Li

Current speaker recognition systems primarily rely on supervised approaches, constrained by the scale of labeled datasets.

Speaker Recognition

Active Learning for Multilingual Fingerspelling Corpora

no code implementations21 Sep 2023 Shuai Wang, Eric Nalisnick

We apply active learning to help with data scarcity problems in sign languages.

Active Learning

Agents: An Open-source Framework for Autonomous Language Agents

1 code implementation14 Sep 2023 Wangchunshu Zhou, Yuchen Eleanor Jiang, Long Li, Jialong Wu, Tiannan Wang, Shi Qiu, Jintian Zhang, Jing Chen, Ruipu Wu, Shuai Wang, Shiding Zhu, Jiyu Chen, Wentao Zhang, Ningyu Zhang, Huajun Chen, Peng Cui, Mrinmaya Sachan

Recent advances on large language models (LLMs) enable researchers and developers to build autonomous language agents that can automatically solve various tasks and interact with environments, humans, and other agents using natural language interfaces.

Unveiling Single-Bit-Flip Attacks on DNN Executables

no code implementations12 Sep 2023 Yanzuo Chen, Zhibo Liu, Yuanyuan Yuan, Sihang Hu, Tianxiang Li, Shuai Wang

Nevertheless, we find that DNN executables contain extensive, severe (e. g., single-bit flip), and transferrable attack surfaces that are not present in high-level DNN models and can be exploited to deplete full model intelligence and control output labels.

Generating Natural Language Queries for More Effective Systematic Review Screening Prioritisation

1 code implementation11 Sep 2023 Shuai Wang, Harrisen Scells, Martin Potthast, Bevan Koopman, Guido Zuccon

Our best approach is not only viable based on the information available at the time of screening, but also has similar effectiveness to the final title.

Natural Language Queries

Enabling Runtime Verification of Causal Discovery Algorithms with Automated Conditional Independence Reasoning (Extended Version)

no code implementations11 Sep 2023 Pingchuan Ma, Zhenlan Ji, Peisen Yao, Shuai Wang, Kui Ren

Based on the decision procedure to CIR, CICheck includes two variants: ED-CICheck and ED-CICheck, which detect erroneous CI tests (to enhance reliability) and prune excessive CI tests (to enhance privacy), respectively.

Causal Discovery

Integrated Robotics Networks with Co-optimization of Drone Placement and Air-Ground Communications

no code implementations9 Sep 2023 Menghao Hu, Tong Zhang, Shuai Wang, Guoliang Li, Yingyang Chen, Qiang Li, Gaojie Chen

Terrestrial robots, i. e., unmanned ground vehicles (UGVs), and aerial robots, i. e., unmanned aerial vehicles (UAVs), operate in separate spaces.

Parsing is All You Need for Accurate Gait Recognition in the Wild

1 code implementation31 Aug 2023 Jinkai Zheng, Xinchen Liu, Shuai Wang, Lihao Wang, Chenggang Yan, Wu Liu

Furthermore, due to the lack of suitable datasets, we build the first parsing-based dataset for gait recognition in the wild, named Gait3D-Parsing, by extending the large-scale and challenging Gait3D dataset.

Gait Recognition in the Wild Human Parsing

Least Squares Maximum and Weighted Generalization-Memorization Machines

no code implementations31 Aug 2023 Shuai Wang, Zhen Wang, Yuan-Hai Shao

Furthermore, we propose some different memory impact functions for the MIMM and WIMM.


Deep Equilibrium Object Detection

1 code implementation ICCV 2023 Shuai Wang, Yao Teng, LiMin Wang

To be more specific to object decoding, we use a two-step unrolled equilibrium equation to explicitly capture the query vector refinement.

object-detection Object Detection

Compound Attention and Neighbor Matching Network for Multi-contrast MRI Super-resolution

no code implementations5 Jul 2023 Wenxuan Chen, Sirui Wu, Shuai Wang, Zhongsen Li, Jia Yang, Huifeng Yao, Xiaolei Song

Multi-contrast magnetic resonance imaging (MRI) reflects information about human tissue from different perspectives and has many clinical applications.

Image Super-Resolution

Communication Resources Constrained Hierarchical Federated Learning for End-to-End Autonomous Driving

1 code implementation28 Jun 2023 Wei-Bin Kou, Shuai Wang, Guangxu Zhu, Bin Luo, Yingxian Chen, Derrick Wing Kwan Ng, Yik-Chung Wu

While federated learning (FL) improves the generalization of end-to-end autonomous driving by model aggregation, the conventional single-hop FL (SFL) suffers from slow convergence rate due to long-range communications among vehicles and cloud server.

Autonomous Driving Federated Learning

Wespeaker baselines for VoxSRC2023

no code implementations27 Jun 2023 Shuai Wang, Chengdong Liang, Xu Xiang, Bing Han, Zhengyang Chen, Hongji Wang, Wen Ding

This report showcases the results achieved using the wespeaker toolkit for the VoxSRC2023 Challenge.

Geometric Pooling: maintaining more useful information

no code implementations21 Jun 2023 Hao Xu, Jia Liu, Yang shen, Kenan Lou, Yanxia Bao, Ruihua Zhang, Shuyue Zhou, Hongsen Zhao, Shuai Wang

However, by analyzing the statistical characteristic of activated units after pooling, we found that a large number of units dropped by sorting pooling are negative-value units that contain useful information and can contribute considerably to the final decision.

Node Classification

Towards Practical Federated Causal Structure Learning

1 code implementation15 Jun 2023 Zhaoyu Wang, Pingchuan Ma, Shuai Wang

Federated learning can solve this problem, but existing solutions for federated causal structure learning make unrealistic assumptions about data and lack convergence guarantees.

Federated Learning

Precise and Generalized Robustness Certification for Neural Networks

1 code implementation11 Jun 2023 Yuanyuan Yuan, Shuai Wang, Zhendong Su

We identify two key properties, independence and continuity, that convert the latent space into a precise and analysis-friendly input space representation for certification.

Autonomous Driving Style Transfer

Enhancing Point Annotations with Superpixel and Confidence Learning Guided for Improving Semi-Supervised OCT Fluid Segmentation

no code implementations5 Jun 2023 Tengjin Weng, Yang shen, Kai Jin, Zhiming Cheng, Yunxiang Li, Gewen Zhang, Shuai Wang, Yaqi Wang

Specifically, we use points to annotate fluid regions in unlabeled OCT images and the Superpixel-Guided Pseudo-Label Generation (SGPLG) module generates pseudo-labels and pixel-level label trust maps from the point annotations.

Denoising Pseudo Label +1

Causality-Aided Trade-off Analysis for Machine Learning Fairness

no code implementations22 May 2023 Zhenlan Ji, Pingchuan Ma, Shuai Wang, Yanhui Li

This paper uses causality analysis as a principled method for analyzing trade-offs between fairness parameters and other crucial metrics in ML pipelines.

Causal Discovery Causal Inference +1

Taxonomy Expansion for Named Entity Recognition

no code implementations22 May 2023 Karthikeyan K, Yogarshi Vyas, Jie Ma, Giovanni Paolini, Neha Anna John, Shuai Wang, Yassine Benajiba, Vittorio Castelli, Dan Roth, Miguel Ballesteros

We experiment with 6 diverse datasets and show that PLM consistently performs better than most other approaches (0. 5 - 2. 5 F1), including in novel settings for taxonomy expansion not considered in prior work.

named-entity-recognition Named Entity Recognition +2

DualVC: Dual-mode Voice Conversion using Intra-model Knowledge Distillation and Hybrid Predictive Coding

no code implementations21 May 2023 Ziqian Ning, Yuepeng Jiang, Pengcheng Zhu, Jixun Yao, Shuai Wang, Lei Xie, Mengxiao Bi

Voice conversion is an increasingly popular technology, and the growing number of real-time applications requires models with streaming conversion capabilities.

Data Augmentation Knowledge Distillation +1

A Weak Supervision Approach for Few-Shot Aspect Based Sentiment

no code implementations19 May 2023 Robert Vacareanu, Siddharth Varia, Kishaloy Halder, Shuai Wang, Giovanni Paolini, Neha Anna John, Miguel Ballesteros, Smaranda Muresan

We explore how weak supervision on abundant unlabeled data can be leveraged to improve few-shot performance in aspect-based sentiment analysis (ABSA) tasks.

Aspect Extraction Aspect Sentiment Triplet Extraction +2

Explain Any Concept: Segment Anything Meets Concept-Based Explanation

1 code implementation NeurIPS 2023 Ao Sun, Pingchuan Ma, Yuanyuan Yuan, Shuai Wang

For computer vision tasks, mainstream pixel-based XAI methods explain DNN decisions by identifying important pixels, and emerging concept-based XAI explore forming explanations with concepts (e. g., a head in an image).

Instance Segmentation Semantic Segmentation

Adversarial Speaker Disentanglement Using Unannotated External Data for Self-supervised Representation Based Voice Conversion

no code implementations16 May 2023 Xintao Zhao, Shuai Wang, Yang Chao, Zhiyong Wu, Helen Meng

Experimental results show that our proposed method achieves comparable similarity and higher naturalness than the supervised method, which needs a huge amount of annotated corpora for training and is applicable to improve similarity for VC methods with other SSL representations as input.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +4

Towards Generalizable Medical Image Segmentation with Pixel-wise Uncertainty Estimation

no code implementations13 May 2023 Shuai Wang, Zipei Yan, Daoan Zhang, Zhongsen Li, Sirui Wu, Wenxuan Chen, Rui Li

In contrast, the IID hypothesis is not universally guaranteed in numerous real-world applications, especially in medical image analysis.

Image Segmentation Medical Image Segmentation +1

Black-box Source-free Domain Adaptation via Two-stage Knowledge Distillation

no code implementations13 May 2023 Shuai Wang, Daoan Zhang, Zipei Yan, Shitong Shao, Rui Li

In Stage \uppercase\expandafter{\romannumeral1}, we train the target model from scratch with soft pseudo-labels generated by the source model in a knowledge distillation manner.

Knowledge Distillation Source-Free Domain Adaptation +1

Meta-Reinforcement Learning Based on Self-Supervised Task Representation Learning

no code implementations29 Apr 2023 Mingyang Wang, Zhenshan Bing, Xiangtong Yao, Shuai Wang, Hang Su, Chenguang Yang, Kai Huang, Alois Knoll

On MuJoCo and Meta-World benchmarks, MoSS outperforms prior works in terms of asymptotic performance, sample efficiency (3-50x faster), adaptation efficiency, and generalization robustness on broad and diverse task distributions.

Meta Reinforcement Learning reinforcement-learning +1

DiffuseExpand: Expanding dataset for 2D medical image segmentation using diffusion models

1 code implementation26 Apr 2023 Shitong Shao, Xiaohan Yuan, Zhen Huang, Ziming Qiu, Shuai Wang, Kevin Zhou

Based on this insight, we propose an approach called DiffuseExpand for expanding datasets for 2D medical image segmentation using DPM, which first samples a variety of masks from Gaussian noise to ensure the diversity, and then synthesizes images to ensure the alignment of images and masks.

Image Generation Image Segmentation +3

Towards Open-Vocabulary Video Instance Segmentation

1 code implementation ICCV 2023 Haochen Wang, Cilin Yan, Shuai Wang, XiaoLong Jiang, Xu Tang, Yao Hu, Weidi Xie, Efstratios Gavves

Video Instance Segmentation (VIS) aims at segmenting and categorizing objects in videos from a closed set of training categories, lacking the generalization ability to handle novel categories in real-world videos.

Instance Segmentation Segmentation +2

Demonstration of InsightPilot: An LLM-Empowered Automated Data Exploration System

no code implementations2 Apr 2023 Pingchuan Ma, Rui Ding, Shuai Wang, Shi Han, Dongmei Zhang

In brief, an IQuery is an abstraction and automation of data analysis operations, which mimics the approach of data analysts and simplifies the exploration process for users.

Language Modelling Large Language Model

Feature Alignment and Uniformity for Test Time Adaptation

1 code implementation CVPR 2023 Shuai Wang, Daoan Zhang, Zipei Yan, JianGuo Zhang, Rui Li

Test time adaptation (TTA) aims to adapt deep neural networks when receiving out of distribution test domain samples.

Domain Generalization Image Segmentation +3

Prototype Knowledge Distillation for Medical Segmentation with Missing Modality

1 code implementation17 Mar 2023 Shuai Wang, Zipei Yan, Daoan Zhang, Haining Wei, Zhongsen Li, Rui Li

Specifically, our ProtoKD can not only distillate the pixel-wise knowledge of multi-modality data to single-modality data but also transfer intra-class and inter-class feature variations, such that the student model could learn more robust feature representation from the teacher model and inference with only one single modality data.

Image Segmentation Knowledge Distillation +2

Bootstrap The Original Latent: Learning a Private Model from a Black-box Model

no code implementations7 Mar 2023 Shuai Wang, Daoan Zhang, JianGuo Zhang, Weiwei Zhang, Rui Li

In this paper, considering the balance of data/model privacy of model owners and user needs, we propose a new setting called Back-Propagated Black-Box Adaptation (BPBA) for users to better train their private models via the guidance of the back-propagated results of a Black-box foundation/source model.

Can ChatGPT Write a Good Boolean Query for Systematic Review Literature Search?

no code implementations3 Feb 2023 Shuai Wang, Harrisen Scells, Bevan Koopman, Guido Zuccon

The ability of ChatGPT to follow complex instructions and generate queries with high precision makes it a valuable tool for researchers conducting systematic reviews, particularly for rapid reviews where time is a constraint and often trading-off higher precision for lower recall is acceptable.

Predictions of photophysical properties of phosphorescent platinum(II) complexes based on ensemble machine learning approach

no code implementations8 Jan 2023 Shuai Wang, ChiYung Yam, Shuguang Chen, Lihong Hu, Liping Li, Faan-Fung Hung, Jiaqi Fan, Chi-Ming Che, Guanhua Chen

Here, we develop a general protocol for accurate predictions of emission wavelength, radiative decay rate constant, and PL quantum yield for phosphorescent Pt(II) emitters based on the combination of first-principles quantum mechanical method, machine learning (ML) and experimental calibration.

Ensemble Learning

SrTR: Self-reasoning Transformer with Visual-linguistic Knowledge for Scene Graph Generation

no code implementations19 Dec 2022 Yuxiang Zhang, Zhenbo Liu, Shuai Wang

The execution efficiency of the one-stage scene graph generation approaches are quite high, which infer the effective relation between entity pairs using sparse proposal sets and a few queries.

Graph Generation Relational Reasoning +1

MeSH Suggester: A Library and System for MeSH Term Suggestion for Systematic Review Boolean Query Construction

1 code implementation18 Dec 2022 Shuai Wang, Hang Li, Guido Zuccon

One challenge to creating an effective systematic review Boolean query is the selection of effective MeSH Terms to include in the query.

Teaching What You Should Teach: A Data-Based Distillation Method

no code implementations11 Dec 2022 Shitong Shao, Huanran Chen, Zhen Huang, Linrui Gong, Shuai Wang, Xinxiao wu

To be specific, we design a neural network-based data augmentation module with priori bias, which assists in finding what meets the teacher's strengths but the student's weaknesses, by learning magnitudes and probabilities to generate suitable data samples.

Data Augmentation Knowledge Distillation +1

Knowledge-Guided Exploration in Deep Reinforcement Learning

no code implementations26 Oct 2022 Sahisnu Mazumder, Bing Liu, Shuai Wang, Yingxuan Zhu, Xiaotian Yin, Lifeng Liu, Jian Li

This paper proposes a new method to drastically speed up deep reinforcement learning (deep RL) training for problems that have the property of state-action permissibility (SAP).

reinforcement-learning Reinforcement Learning (RL)

Large-Scale Bandwidth and Power Optimization for Multi-Modal Edge Intelligence Autonomous Driving

no code implementations18 Oct 2022 Xinrao Li, Tong Zhang, Shuai Wang, Guangxu Zhu, Rui Wang, Tsung-Hui Chang

However, wireless channels between the edge server and the autonomous vehicles are time-varying due to the high-mobility of vehicles.

Autonomous Driving

Instruction Tuning for Few-Shot Aspect-Based Sentiment Analysis

1 code implementation12 Oct 2022 Siddharth Varia, Shuai Wang, Kishaloy Halder, Robert Vacareanu, Miguel Ballesteros, Yassine Benajiba, Neha Anna John, Rishita Anubhai, Smaranda Muresan, Dan Roth

Aspect-based Sentiment Analysis (ABSA) is a fine-grained sentiment analysis task which involves four elements from user-generated texts: aspect term, aspect category, opinion term, and sentiment polarity.

Aspect-Based Sentiment Analysis (ABSA) Few-Shot Learning +1

Contrastive Training Improves Zero-Shot Classification of Semi-structured Documents

no code implementations11 Oct 2022 Muhammad Khalifa, Yogarshi Vyas, Shuai Wang, Graham Horwood, Sunil Mallya, Miguel Ballesteros

The standard classification setting where categories are fixed during both training and testing falls short in dynamic environments where new document categories could potentially emerge.

Classification Document Classification +1

Decompiling x86 Deep Neural Network Executables

no code implementations3 Oct 2022 Zhibo Liu, Yuanyuan Yuan, Shuai Wang, Xiaofei Xie, Lei Ma

BTD takes DNN executables and outputs full model specifications, including types of DNN operators, network topology, dimensions, and parameters that are (nearly) identical to those of the input models.

Accelerated partial separable model using dimension-reduced optimization technique for ultra-fast cardiac MRI

no code implementations2 Oct 2022 Zhongsen Li, Aiqi Sun, Chuyu Liu, Haining Wei, Shuai Wang, Mingzhu Fu, Rui Li

The main objective of this study is to accelerate the PS model, shorten the time required for acquisition and reconstruction, and maintain good image quality simultaneously.

Dimensionality Reduction Image Reconstruction

Automated MeSH Term Suggestion for Effective Query Formulation in Systematic Reviews Literature Search

1 code implementation19 Sep 2022 Shuai Wang, Harrisen Scells, Bevan Koopman, Guido Zuccon

However, identifying the correct MeSH terms to include in a query is difficult: information experts are often unfamiliar with the MeSH database and unsure about the appropriateness of MeSH terms for a query.

Language-aware Domain Generalization Network for Cross-Scene Hyperspectral Image Classification

no code implementations6 Sep 2022 Yuxiang Zhang, Mengmeng Zhang, Wei Li, Shuai Wang, Ran Tao

Text information including extensive prior knowledge about land cover classes has been ignored in hyperspectral image classification (HSI) tasks.

Contrastive Learning Domain Generalization +1

Multi-Point Integrated Sensing and Communication: Fusion Model and Functionality Selection

no code implementations16 Aug 2022 Guoliang Li, Shuai Wang, Kejiang Ye, Miaowen Wen, Derrick Wing Kwan Ng, Marco Di Renzo

Integrated sensing and communication (ISAC) represents a paradigm shift, where previously competing wireless transmissions are jointly designed to operate in harmony via the shared use of the hardware platform for improving the spectral and energy efficiencies.

Longitudinal Prediction of Postnatal Brain Magnetic Resonance Images via a Metamorphic Generative Adversarial Network

no code implementations9 Aug 2022 Yunzhi Huang, Sahar Ahmad, Luyi Han, Shuai Wang, Zhengwang Wu, Weili Lin, Gang Li, Li Wang, Pew-Thian Yap

In this paper, we propose a deep learning framework to predict missing scans from acquired scans, catering to longitudinal infant studies.


XInsight: eXplainable Data Analysis Through The Lens of Causality

no code implementations26 Jul 2022 Pingchuan Ma, Rui Ding, Shuai Wang, Shi Han, Dongmei Zhang

XInsight is a three-module, end-to-end pipeline designed to extract causal graphs, translate causal primitives into XDA semantics, and quantify the quantitative contribution of each explanation to a data fact.

Decision Making

Cross Vision-RF Gait Re-identification with Low-cost RGB-D Cameras and mmWave Radars

no code implementations16 Jul 2022 Dongjiang Cao, Ruofeng Liu, Hao Li, Shuai Wang, Wenchao Jiang, Chris Xiaoxuan Lu

Human identification is a key requirement for many applications in everyday life, such as personalized services, automatic surveillance, continuous authentication, and contact tracing during pandemics, etc.

Metric Learning Person Re-Identification

A Framework Based on Generational and Environmental Response Strategies for Dynamic Multi-objective Optimization

no code implementations6 Jul 2022 Qingya Li, Xiangzhi Liu, Fuqiang Wang, Shuai Wang, Peng Zhang, Xiaoming Wu

In this paper, a novel framework based on generational and environmental response strategies (FGERS) is proposed, in which response strategies are run both in the environmental change stage and the environmental static stage to obtain population evolution information of those both stages.

VIP-SLAM: An Efficient Tightly-Coupled RGB-D Visual Inertial Planar SLAM

no code implementations4 Jul 2022 Danpeng Chen, Shuai Wang, Weijian Xie, Shangjin Zhai, Nan Wang, Hujun Bao, Guofeng Zhang

Even if the plane parameters are involved in the optimization, we effectively simplify the back-end map by using planar structures.

Federated Deep Learning Meets Autonomous Vehicle Perception: Design and Verification

1 code implementation3 Jun 2022 Shuai Wang, Chengyang Li, Derrick Wing Kwan Ng, Yonina C. Eldar, H. Vincent Poor, Qi Hao, Chengzhong Xu

However, it is challenging to determine the network resources and road sensor placements for multi-stage training with multi-modal datasets in multi-variant scenarios.

Federated Learning Management

Byzantine-Robust Federated Learning with Optimal Statistical Rates and Privacy Guarantees

1 code implementation24 May 2022 Banghua Zhu, Lun Wang, Qi Pang, Shuai Wang, Jiantao Jiao, Dawn Song, Michael I. Jordan

In contrast to prior work, our proposed protocols improve the dimension dependence and achieve a tight statistical rate in terms of all the parameters for strongly convex losses.

Federated Learning

To Interpolate or not to Interpolate: PRF, Dense and Sparse Retrievers

no code implementations30 Apr 2022 Hang Li, Shuai Wang, Shengyao Zhuang, Ahmed Mourad, Xueguang Ma, Jimmy Lin, Guido Zuccon

In this paper we consider the problem of combining the relevance signals from sparse and dense retrievers in the context of Pseudo Relevance Feedback (PRF).

Information Retrieval Language Modelling +1

Phase Shift Design in RIS Empowered Wireless Networks: From Optimization to AI-Based Methods

no code implementations28 Apr 2022 Zongze Li, Shuai Wang, Qingfeng Lin, Yang Li, Miaowen Wen, Yik-Chung Wu, H. Vincent Poor

Reconfigurable intelligent surfaces (RISs) have a revolutionary capability to customize the radio propagation environment for wireless networks.

Federated Stochastic Primal-dual Learning with Differential Privacy

no code implementations26 Apr 2022 Yiwei Li, Shuai Wang, Tsung-Hui Chang, Chong-Yung Chi

Specifically, we show that, by guaranteeing $(\epsilon, \delta)$-DP for each client per communication round, the proposed algorithm guarantees $(\mathcal{O}(q\epsilon \sqrt{p T}), \delta)$-DP after $T$ communication rounds while maintaining an $\mathcal{O}(1/\sqrt{pTQ})$ convergence rate for a convex and non-smooth learning problem, where $Q$ is the number of local SGD steps, $p$ is the client sampling probability, $q=\max_{i} q_i/\sqrt{1-q_i}$ and $q_i$ is the data sampling probability of each client under PCP.

Federated Learning

Accelerating Federated Edge Learning via Topology Optimization

no code implementations1 Apr 2022 Shanfeng Huang, Zezhong Zhang, Shuai Wang, Rui Wang, Kaibin Huang

In this paper, a novel topology-optimized federated edge learning (TOFEL) scheme is proposed to tackle the heterogeneity issue in federated learning and to improve the communication-and-computation efficiency.

3D Object Detection Federated Learning +3

Semantic-guided Disentangled Representation for Unsupervised Cross-modality Medical Image Segmentation

no code implementations26 Mar 2022 Shuai Wang, Rui Li

Disentangled representation is a powerful technique to tackle domain shift problem in medical image analysis in unsupervised domain adaptation setting. However, previous methods only focus on exacting domain-invariant feature and ignore whether exacted feature is meaningful for downstream tasks. We propose a novel framework, called semantic-guided disentangled representation (SGDR), an effective method to exact semantically meaningful feature for segmentation task to improve performance of cross modality medical image segmentation in unsupervised domain adaptation setting.

Image Segmentation Medical Image Segmentation +3

Plug-and-play Shape Refinement Framework for Multi-site and Lifespan Brain Skull Stripping

no code implementations8 Mar 2022 Yunxiang Li, Ruilong Dan, Shuai Wang, Yifan Cao, Xiangde Luo, Chenghao Tan, Gangyong Jia, Huiyu Zhou, You Zhang, Yaqi Wang, Li Wang

For instance, the model trained on a dataset with specific imaging parameters cannot be well applied to other datasets with different imaging parameters.

Skull Stripping Source-Free Domain Adaptation

Low Earth Orbit Satellite Security and Reliability: Issues, Solutions, and the Road Ahead

no code implementations9 Jan 2022 Pingyue Yue, Jianping An, Jiankang Zhang, Jia Ye, Gaofeng Pan, Shuai Wang, Pei Xiao, Lajos Hanzo

Low Earth Orbit (LEO) satellites undergo a period of rapid development driven by ever-increasing user demands, reduced costs, and technological progress.

ADI: Adversarial Dominating Inputs in Vertical Federated Learning Systems

1 code implementation8 Jan 2022 Qi Pang, Yuanyuan Yuan, Shuai Wang, Wenting Zheng

Vertical federated learning (VFL) system has recently become prominent as a concept to process data distributed across many individual sources without the need to centralize it.

Federated Learning Privacy Preserving

Automated Side Channel Analysis of Media Software with Manifold Learning

1 code implementation9 Dec 2021 Yuanyuan Yuan, Qi Pang, Shuai Wang

Recent advances in representation learning and perceptual learning inspired us to consider the reconstruction of media inputs from side channel traces as a cross-modality manifold learning task that can be addressed in a unified manner with an autoencoder framework trained to learn the mapping between media inputs and side channel observations.

Cloud Computing Representation Learning +1

Seed-driven Document Ranking for Systematic Reviews: A Reproducibility Study

1 code implementation8 Dec 2021 Shuai Wang, Harrisen Scells, Ahmed Mourad, Guido Zuccon

Our results also indicate that our reproduced screening prioritisation method, (1) is generalisable across datasets of similar and different topicality compared to the original implementation, (2) that when using multiple seed studies, the effectiveness of the method increases using our techniques to enable this, (3) and that the use of multiple seed studies produces more stable rankings compared to single seed studies.

Document Ranking

MDPFuzz: Testing Models Solving Markov Decision Processes

no code implementations6 Dec 2021 Qi Pang, Yuanyuan Yuan, Shuai Wang

During fuzzing, MDPFuzz decides which mutated state to retain by measuring if it can reduce cumulative rewards or form a new state sequence.

Autonomous Driving Collision Avoidance +2

Revisiting Neuron Coverage for DNN Testing: A Layer-Wise and Distribution-Aware Criterion

1 code implementation3 Dec 2021 Yuanyuan Yuan, Qi Pang, Shuai Wang

We demonstrate that NLC is significantly correlated with the diversity of a test suite across a number of tasks (classification and generation) and data formats (image and text).

DNN Testing Test

Provably Valid and Diverse Mutations of Real-World Media Data for DNN Testing

no code implementations3 Dec 2021 Yuanyuan Yuan, Qi Pang, Shuai Wang

In contrast, we discuss the feasibility of mutating real-world media data with provably high DIV and VAL based on manifold.

DNN Testing valid

Dispensed Transformer Network for Unsupervised Domain Adaptation

no code implementations28 Oct 2021 Yunxiang Li, Jingxiong Li, Ruilong Dan, Shuai Wang, Kai Jin, Guodong Zeng, Jun Wang, Xiangji Pan, Qianni Zhang, Huiyu Zhou, Qun Jin, Li Wang, Yaqi Wang

To mitigate this problem, a novel unsupervised domain adaptation (UDA) method named dispensed Transformer network (DTNet) is introduced in this paper.

Unsupervised Domain Adaptation

Dual Shape Guided Segmentation Network for Organs-at-Risk in Head and Neck CT Images

no code implementations23 Oct 2021 Shuai Wang, Theodore Yanagihara, Bhishamjit Chera, Colette Shen, Pew-Thian Yap, Jun Lian

To deal with the large shape variation and unclear boundary of OARs in CT images, we represent the organ shape using an organ-specific unilateral inverse-distance map (UIDM) and guide the segmentation task from two different perspectives: direct shape guidance by following the segmentation prediction and across shape guidance by sharing the segmentation feature.


GT U-Net: A U-Net Like Group Transformer Network for Tooth Root Segmentation

1 code implementation30 Sep 2021 Yunxiang Li, Shuai Wang, Jun Wang, Guodong Zeng, Wenjun Liu, Qianni Zhang, Qun Jin, Yaqi Wang

In this paper, we propose a novel end-to-end U-Net like Group Transformer Network (GT U-Net) for the tooth root segmentation.

Anatomy Segmentation

FED-$\chi^2$: Secure Federated Correlation Test

no code implementations29 Sep 2021 Lun Wang, Qi Pang, Shuai Wang, Dawn Song

In this paper, we propose the first secure federated $\chi^2$-test protocol, FED-$\chi^2$.


Secure Byzantine-Robust Federated Learning with Dimension-free Error

no code implementations29 Sep 2021 Lun Wang, Qi Pang, Shuai Wang, Dawn Song

In the present work, we propose a federated learning protocol with bi-directional security guarantees.

Federated Learning

Paint4Poem: A Dataset for Artistic Visualization of Classical Chinese Poems

1 code implementation23 Sep 2021 Dan Li, Shuai Wang, Jie Zou, Chang Tian, Elisha Nieuwburg, Fengyuan Sun, Evangelos Kanoulas

We create abenchmark for Paint4Poem: we train two representative text-to-image generation models: AttnGAN and MirrorGAN, and evaluate theirperformance regarding painting pictorial quality, painting stylistic relevance, and semantic relevance between poems and paintings. The results indicate that the models are able to generate paintings that have good pictorial quality and mimic Feng Zikai's style, but thereflection of poem semantics is limited.

Few-Shot Learning

Unit-Modulus Wireless Federated Learning Via Penalty Alternating Minimization

no code implementations31 Aug 2021 Shuai Wang, Dachuan Li, Rui Wang, Qi Hao, Yik-Chung Wu, Derrick Wing Kwan Ng

Wireless federated learning (FL) is an emerging machine learning paradigm that trains a global parametric model from distributed datasets via wireless communications.

Federated Learning

Accelerating Federated Edge Learning via Optimized Probabilistic Device Scheduling

no code implementations24 Jul 2021 Maojun Zhang, Guangxu Zhu, Shuai Wang, Jiamo Jiang, Caijun Zhong, Shuguang Cui

Building on the analytical result, an optimized probabilistic scheduling policy is derived in closed-form by solving the approximate communication time minimization problem.

Autonomous Driving Learning Theory +2

Accelerating Edge Intelligence via Integrated Sensing and Communication

no code implementations20 Jul 2021 Tong Zhang, Shuai Wang, Guoliang Li, Fan Liu, Guangxu Zhu, Rui Wang

Conventionally, the sensing and communication stages are executed sequentially, which results in excessive amount of dataset generation and uploading time.

Integrated Sensing and Communication from Learning Perspective: An SDP3 Approach

no code implementations20 Jul 2021 Guoliang Li, Shuai Wang, Jie Li, Rui Wang, Fan Liu, Xiaohui Peng, Tony Xiao Han, Chengzhong Xu

Characterizing the sensing and communication performance tradeoff in integrated sensing and communication (ISAC) systems is challenging in the applications of learning-based human motion recognition.

Perception Matters: Detecting Perception Failures of VQA Models Using Metamorphic Testing

1 code implementation CVPR 2021 Yuanyuan Yuan, Shuai Wang, Mingyue Jiang, Tsong Yueh Chen

MetaVQA checks whether the answer to (i, q) satisfies metamorphic relationships (MRs), denoting perception consistency, with the composed answers of transformed questions and images.

Benchmarking DNN Testing +2

Privileged Graph Distillation for Cold Start Recommendation

no code implementations31 May 2021 Shuai Wang, Kun Zhang, Le Wu, Haiping Ma, Richang Hong, Meng Wang

The teacher model is composed of a heterogeneous graph structure for warm users and items with privileged CF links.

Collaborative Filtering Recommendation Systems

AGMB-Transformer: Anatomy-Guided Multi-Branch Transformer Network for Automated Evaluation of Root Canal Therapy

1 code implementation2 May 2021 Yunxiang Li, Guodong Zeng, Yifan Zhang, Jun Wang, Qianni Zhang, Qun Jin, Lingling Sun, Qisi Lian, Neng Xia, Ruizi Peng, Kai Tang, Yaqi Wang, Shuai Wang

Accurate evaluation of the treatment result on X-ray images is a significant and challenging step in root canal therapy since the incorrect interpretation of the therapy results will hamper timely follow-up which is crucial to the patients' treatment outcome.

Anatomy General Classification

Wireless Sensing With Deep Spectrogram Network and Primitive Based Autoregressive Hybrid Channel Model

no code implementations21 Apr 2021 Guoliang Li, Shuai Wang, Jie Li, Rui Wang, Xiaohui Peng, Tony Xiao Han

Although wireless channel models can be adopted for dataset generation, current channel models are mostly designed for communication rather than sensing.

Scene Understanding

Distributed Dynamic Map Fusion via Federated Learning for Intelligent Networked Vehicles

1 code implementation5 Mar 2021 Zijian Zhang, Shuai Wang, Yuncong Hong, Liangkai Zhou, Qi Hao

The technology of dynamic map fusion among networked vehicles has been developed to enlarge sensing ranges and improve sensing accuracies for individual vehicles.

Federated Learning Knowledge Distillation +1

Edge Federated Learning Via Unit-Modulus Over-The-Air Computation

1 code implementation28 Jan 2021 Shuai Wang, Yuncong Hong, Rui Wang, Qi Hao, Yik-Chung Wu, Derrick Wing Kwan Ng

Simulation results show that the proposed UMAirComp framework with PAM algorithm achieves a smaller mean square error of model parameters' estimation, training loss, and test error compared with other benchmark schemes.

Autonomous Driving Federated Learning

On Secure Degrees of Freedom of the MIMO Interference Channel with Local Output Feedback

no code implementations3 Jan 2021 Tong Zhang, Yinfei Xu, Shuai Wang, Miaowen Wen, Rui Wang

This paper studies the problem of sum-secure degrees of freedom (SDoF) of the (M, M, N, N) multiple-input multiple-output (MIMO) interference channel with local output feedback, so as to build an information-theoretic foundation and provide practical transmission schemes for 6G-enabled vehicles-to-vehicles (V2V).

Information Theory Information Theory

Private Image Reconstruction from System Side Channels Using Generative Models

2 code implementations ICLR 2021 Yuanyuan Yuan, Shuai Wang, Junping Zhang

Given the ever-growing adoption of machine learning as a service (MLaaS), image analysis software on cloud platforms has been exploited by reconstructing private user images from system side channels.

Image Reconstruction Side Channel Analysis

F^2ed-Learning: Good Fences Make Good Neighbors

no code implementations1 Jan 2021 Lun Wang, Qi Pang, Shuai Wang, Dawn Song

In this paper, we present F^2ed-Learning, the first federated learning protocol simultaneously defending against both semi-honest server and Byzantine malicious clients.

Federated Learning

A General Recurrent Tracking Framework Without Real Data

no code implementations ICCV 2021 Shuai Wang, Hao Sheng, Yang Zhang, Yubin Wu, Zhang Xiong

Based on this framework, a Recurrent Tracking Unit (RTU) is designed to score potential tracks through long-term information.

Multi-Object Tracking

Reconfigurable Intelligent Surface Assisted Mobile Edge Computing with Heterogeneous Learning Tasks

no code implementations25 Dec 2020 Shanfeng Huang, Shuai Wang, Rui Wang, Miaowen Wen, Kaibin Huang

The ever-growing popularity and rapid improving of artificial intelligence (AI) have raised rethinking on the evolution of wireless networks.

3D Object Detection Autonomous Driving +2

MT-Teql: Evaluating and Augmenting Consistency of Text-to-SQL Models with Metamorphic Testing

no code implementations21 Dec 2020 Pingchuan Ma, Shuai Wang

Envisioning the general difficulty for text-to-SQL models to preserve prediction consistency against linguistic and schema variations, we propose MT-Teql, a Metamorphic Testing-based framework for systematically evaluating and augmenting the consistency of TExt-to-SQL models.


Multi-Domain Multi-Task Rehearsal for Lifelong Learning

no code implementations14 Dec 2020 Fan Lyu, Shuai Wang, Wei Feng, Zihan Ye, Fuyuan Hu, Song Wang

Rehearsal, seeking to remind the model by storing old knowledge in lifelong learning, is one of the most effective ways to mitigate catastrophic forgetting, i. e., biased forgetting of previous knowledge when moving to new tasks.

Multiscale Attention Guided Network for COVID-19 Diagnosis Using Chest X-ray Images

1 code implementation11 Nov 2020 Jingxiong Li, Yaqi Wang, Shuai Wang, Jun Wang, Jun Liu, Qun Jin, Lingling Sun

Moreover, massive data collection is impractical for a newly emerged disease, which limited the performance of data thirsty deep learning models.

Classification COVID-19 Diagnosis +1

Learning Centric Wireless Resource Allocation for Edge Computing: Algorithm and Experiment

no code implementations29 Oct 2020 Liangkai Zhou, Yuncong Hong, Shuai Wang, Ruihua Han, Dachuan Li, Rui Wang, Qi Hao

Edge intelligence is an emerging network architecture that integrates sensing, communication, computing components, and supports various machine learning applications, where a fundamental communication question is: how to allocate the limited wireless resources (such as time, energy) to the simultaneous model training of heterogeneous learning tasks?


A Knowledge-Driven Approach to Classifying Object and Attribute Coreferences in Opinion Mining

no code implementations Findings of the Association for Computational Linguistics 2020 Jiahua Chen, Shuai Wang, Sahisnu Mazumder, Bing Liu

Classifying and resolving coreferences of objects (e. g., product names) and attributes (e. g., product aspects) in opinionated reviews is crucial for improving the opinion mining performance.

Opinion Mining

Towards Bidirectional Protection in Federated Learning

no code implementations2 Oct 2020 Lun Wang, Qi Pang, Shuai Wang, Dawn Song

At one end of the spectrum, some work uses secure aggregation techniques to hide the individual client's updates and only reveal the aggregated global update to a malicious server that strives to infer the clients' privacy from their updates.

Federated Learning

Edge Learning with Unmanned Ground Vehicle: Joint Path, Energy and Sample Size Planning

no code implementations7 Sep 2020 Dan Liu, Shuai Wang, Zhigang Wen, Lei Cheng, Miaowen Wen, Yik-Chung Wu

However, different devices may transmit different data for different machine learning jobs and a fundamental question is how to jointly plan the UGV path, the devices' energy consumption, and the number of samples for different jobs?

BIG-bench Machine Learning Edge-computing

Learning Centric Power Allocation for Edge Intelligence

no code implementations21 Jul 2020 Shuai Wang, Rui Wang, Qi Hao, Yik-Chung Wu, H. Vincent Poor

While machine-type communication (MTC) devices generate massive data, they often cannot process this data due to limited energy and computation power.


Improving Positive Unlabeled Learning: Practical AUL Estimation and New Training Method for Extremely Imbalanced Data Sets

no code implementations21 Apr 2020 Liwei Jiang, Dan Li, Qisheng Wang, Shuai Wang, Songtao Wang

Secondly, we propose ProbTagging, a new training method for extremely imbalanced data sets, where the number of unlabeled samples is hundreds or thousands of times that of positive samples.

MUTATT: Visual-Textual Mutual Guidance for Referring Expression Comprehension

no code implementations18 Mar 2020 Shuai Wang, Fan Lyu, Wei Feng, Song Wang

In this paper, we argue that for REC the referring expression and the target region are semantically correlated and subject, location and relationship consistency exist between vision and language. On top of this, we propose a novel approach called MutAtt to construct mutual guidance between vision and language, which treat vision and language equally thus yield compact information matching.

Referring Expression Referring Expression Comprehension

Intelligent Home 3D: Automatic 3D-House Design from Linguistic Descriptions Only

1 code implementation CVPR 2020 Qi Chen, Qi Wu, Rui Tang, Yu-Han Wang, Shuai Wang, Mingkui Tan

To this end, we propose a House Plan Generative Model (HPGM) that first translates the language input to a structural graph representation and then predicts the layout of rooms with a Graph Conditioned Layout Prediction Network (GC LPN) and generates the interior texture with a Language Conditioned Texture GAN (LCT-GAN).

Text to 3D

Federated Matrix Factorization: Algorithm Design and Application to Data Clustering

no code implementations12 Feb 2020 Shuai Wang, Tsung-Hui Chang

Recent demands on data privacy have called for federated learning (FL) as a new distributed learning paradigm in massive and heterogeneous networks.

Clustering Federated Learning

Metamorphic Testing for Object Detection Systems

no code implementations19 Dec 2019 Shuai Wang, Zhendong Su

To fill this critical gap, we introduce the design and realization of MetaOD, the first metamorphic testing system for object detectors to effectively reveal erroneous detection results by commercial object detectors.

Autonomous Driving object-detection +1

Machine Intelligence at the Edge with Learning Centric Power Allocation

no code implementations12 Nov 2019 Shuai Wang, Yik-Chung Wu, Minghua Xia, Rui Wang, H. Vincent Poor

However, power allocation in this paradigm requires maximizing the learning performance instead of the communication throughput, for which the celebrated water-filling and max-min fairness algorithms become inefficient.

Fairness Learning Theory

Building an Application Independent Natural Language Interface

no code implementations30 Oct 2019 Sahisnu Mazumder, Bing Liu, Shuai Wang, Sepideh Esmaeilpour

Traditional approaches to building natural language (NL) interfaces typically use a semantic parser to parse the user command and convert it to a logical form, which is then translated to an executable action in an application.

Lifelong and Interactive Learning of Factual Knowledge in Dialogues

no code implementations WS 2019 Sahisnu Mazumder, Bing Liu, Shuai Wang, Nianzu Ma

Dialogue systems are increasingly using knowledge bases (KBs) storing real-world facts to help generate quality responses.

Margin Matters: Towards More Discriminative Deep Neural Network Embeddings for Speaker Recognition

no code implementations18 Jun 2019 Xu Xiang, Shuai Wang, Houjun Huang, Yanmin Qian, Kai Yu

The proposed approach can achieve the state-of-the-art performance, with 25% ~ 30% equal error rate (EER) reduction on both tasks when compared to strong baselines using cross entropy loss with softmax, obtaining 2. 238% EER on VoxCeleb1 test set and 2. 761% EER on SITW core-core test set, respectively.

Speaker Recognition Test

Forward and Backward Knowledge Transfer for Sentiment Classification

no code implementations8 Jun 2019 Hao Wang, Bing Liu, Shuai Wang, Nianzu Ma, Yan Yang

That is, it is possible to improve the NB classifier for a task by improving its model parameters directly by using the retained knowledge from other tasks.

Classification General Classification +3

Clustering by Orthogonal NMF Model and Non-Convex Penalty Optimization

1 code implementation3 Jun 2019 Shuai Wang, Tsung-Hui Chang, Ying Cui, Jong-Shi Pang

We then apply a non-convex penalty (NCP) approach to add them to the objective as penalty terms, leading to a problem that is efficiently solvable.


Guided Exploration in Deep Reinforcement Learning

no code implementations27 Sep 2018 Sahisnu Mazumder, Bing Liu, Shuai Wang, Yingxuan Zhu, Xiaotian Yin, Lifeng Liu, Jian Li, Yongbing Huang

This paper proposes a new method to drastically speed up deep reinforcement learning (deep RL) training for problems that have the property of \textit{state-action permissibility} (SAP).

reinforcement-learning Reinforcement Learning (RL)

Deep Learning for Sentiment Analysis : A Survey

1 code implementation24 Jan 2018 Lei Zhang, Shuai Wang, Bing Liu

Deep learning has emerged as a powerful machine learning technique that learns multiple layers of representations or features of the data and produces state-of-the-art prediction results.

BIG-bench Machine Learning Sentiment Analysis

Contextual and Position-Aware Factorization Machines for Sentiment Classification

no code implementations18 Jan 2018 Shuai Wang, Mianwei Zhou, Geli Fei, Yi Chang, Bing Liu

While existing machine learning models have achieved great success for sentiment classification, they typically do not explicitly capture sentiment-oriented word interaction, which can lead to poor results for fine-grained analysis at the snippet level (a phrase or sentence).

Classification General Classification +4

Translingual Obfuscation

no code implementations5 Jan 2016 Pei Wang, Shuai Wang, Jiang Ming, Yufei Jiang, Dinghao Wu

We introduce translingual obfuscation, a new software obfuscation scheme which makes programs obscure by "misusing" the unique features of certain programming languages.

Cryptography and Security Software Engineering

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