Search Results for author: Xin Wang

Found 392 papers, 132 papers with code

Dependency Position Encoding for Relation Extraction

no code implementations Findings (NAACL) 2022 Qiushi Guo, Xin Wang, Dehong Gao

Leveraging the dependency tree of the input sentence is able to improve the model performance for relation extraction.

Relation Extraction

OIE@OIA: an Adaptable and Efficient Open Information Extraction Framework

no code implementations ACL 2022 Xin Wang, Minlong Peng, Mingming Sun, Ping Li

OIE@OIA follows the methodology of Open Information eXpression (OIX): parsing a sentence to an Open Information Annotation (OIA) Graph and then adapting the OIA graph to different OIE tasks with simple rules.

Open Information Extraction

A Predicate-Function-Argument Annotation of Natural Language for Open-Domain Information eXpression

no code implementations EMNLP 2020 Mingming Sun, Wenyue Hua, Zoey Liu, Xin Wang, Kangjie Zheng, Ping Li

Based on the same platform of OIX, the OIE strategies are reusable, and people can select a set of strategies to assemble their algorithm for a specific task so that the adaptability may be significantly increased.

Open Information Extraction

Deep Reinforcement Learning for Image-to-Image Translation

1 code implementation24 Sep 2023 Xin Wang, Ziwei Luo, Jing Hu, Chengming Feng, Shu Hu, Bin Zhu, Xi Wu, Siwei Lyu

The key feature in the RL-I2IT framework is to decompose a monolithic learning process into small steps with a lightweight model to progressively transform a source image successively to a target image.

Decision Making reinforcement-learning

WiCV@CVPR2023: The Eleventh Women In Computer Vision Workshop at the Annual CVPR Conference

no code implementations22 Sep 2023 Doris Antensteiner, Marah Halawa, Asra Aslam, Ivaxi Sheth, Sachini Herath, Ziqi Huang, Sunnie S. Y. Kim, Aparna Akula, Xin Wang

In this paper, we present the details of Women in Computer Vision Workshop - WiCV 2023, organized alongside the hybrid CVPR 2023 in Vancouver, Canada.

On-the-Fly SfM: What you capture is What you get

no code implementations21 Sep 2023 Zongqian Zhan, Rui Xia, Yifei Yu, Yibo Xu, Xin Wang

Over the last decades, ample achievements have been made on Structure from motion (SfM).

Image Registration Image Retrieval +1

For A More Comprehensive Evaluation of 6DoF Object Pose Tracking

no code implementations14 Sep 2023 Yang Li, Fan Zhong, Xin Wang, Shuangbing Song, Jiachen Li, Xueying Qin, Changhe Tu

The limitations of previous scoring methods and error metrics are analyzed, based on which we introduce our improved evaluation methods.

Pose Tracking

Can large-scale vocoded spoofed data improve speech spoofing countermeasure with a self-supervised front end?

1 code implementation12 Sep 2023 Xin Wang, Junichi Yamagishi

While many datasets use spoofed data generated by speech synthesis systems, it was recently found that data vocoded by neural vocoders were also effective as the spoofed training data.

Self-Supervised Learning Speech Synthesis

Outlier Robust Adversarial Training

1 code implementation10 Sep 2023 Shu Hu, Zhenhuan Yang, Xin Wang, Yiming Ying, Siwei Lyu

Theoretically, we show that the learning objective of ORAT satisfies the $\mathcal{H}$-consistency in binary classification, which establishes it as a proper surrogate to adversarial 0/1 loss.

Adversarial Attack Binary Classification

Control-Oriented Modeling and Layer-to-Layer Spatial Control of Powder Bed Fusion Processes

no code implementations8 Sep 2023 Xin Wang, Bumsoo Park, Robert G. Landers, Sandipan Mishra, Douglas A. Bristow

However, due to inherent process variability, it is still very costly and time consuming to certify the process and the part.

DRAG: Divergence-based Adaptive Aggregation in Federated learning on Non-IID Data

no code implementations4 Sep 2023 Feng Zhu, Jingjing Zhang, Shengyun Liu, Xin Wang

Local stochastic gradient descent (SGD) is a fundamental approach in achieving communication efficiency in Federated Learning (FL) by allowing individual workers to perform local updates.

Federated Learning

BenchTemp: A General Benchmark for Evaluating Temporal Graph Neural Networks

1 code implementation31 Aug 2023 Qiang Huang, Jiawei Jiang, Xi Susie Rao, Ce Zhang, Zhichao Han, Zitao Zhang, Xin Wang, Yongjun He, Quanqing Xu, Yang Zhao, Chuang Hu, Shuo Shang, Bo Du

To handle graphs in which features or connectivities are evolving over time, a series of temporal graph neural networks (TGNNs) have been proposed.

Link Prediction Node Classification

Large Graph Models: A Perspective

1 code implementation28 Aug 2023 Ziwei Zhang, Haoyang Li, Zeyang Zhang, Yijian Qin, Xin Wang, Wenwu Zhu

Large models have emerged as the most recent groundbreaking achievements in artificial intelligence, and particularly machine learning.

A Survey on Fairness in Large Language Models

no code implementations20 Aug 2023 Yingji Li, Mengnan Du, Rui Song, Xin Wang, Ying Wang

Then, for large-scale LLMs, we introduce recent fairness research, including fairness evaluation, reasons for bias, and debiasing methods.


Unsupervised Multiplex Graph Learning with Complementary and Consistent Information

1 code implementation3 Aug 2023 Liang Peng, Xin Wang, Xiaofeng Zhu

Unsupervised multiplex graph learning (UMGL) has been shown to achieve significant effectiveness for different downstream tasks by exploring both complementary information and consistent information among multiple graphs.

Graph Learning Representation Learning

SphereNet: Learning a Noise-Robust and General Descriptor for Point Cloud Registration

no code implementations18 Jul 2023 Guiyu Zhao, Zhentao Guo, Xin Wang, Hongbin Ma

However, most methods are susceptible to noise and have poor generalization ability on unseen datasets.

Point Cloud Registration

Mixed-Precision Quantization with Cross-Layer Dependencies

no code implementations11 Jul 2023 Zihao Deng, Xin Wang, Sayeh Sharify, Michael Orshansky

Quantization assigning the same bit-width to all layers leads to large accuracy degradation at low precision and is wasteful at high precision settings.


Over-The-Air Federated Learning: Status Quo, Open Challenges, and Future Directions

no code implementations3 Jul 2023 Bingnan Xiao, Xichen Yu, Wei Ni, Xin Wang, H. Vincent Poor

The development of applications based on artificial intelligence and implemented over wireless networks is increasingly rapidly and is expected to grow dramatically in the future.

Federated Learning

An Explainable Deep Framework: Towards Task-Specific Fusion for Multi-to-One MRI Synthesis

1 code implementation3 Jul 2023 Luyi Han, Tianyu Zhang, Yunzhi Huang, Haoran Dou, Xin Wang, Yuan Gao, Chunyao Lu, Tan Tao, Ritse Mann

Multi-sequence MRI is valuable in clinical settings for reliable diagnosis and treatment prognosis, but some sequences may be unusable or missing for various reasons.

Efficient Search and Detection of Relevant Plant Parts using Semantics-Aware Active Vision

no code implementations16 Jun 2023 Akshay K. Burusa, Joost Scholten, David Rapado Rincon, Xin Wang, Eldert J. van Henten, Gert Kootstra

To automate harvesting and de-leafing of tomato plants using robots, it is important to search and detect the relevant plant parts, namely tomatoes, peduncles, and petioles.

Towards single integrated spoofing-aware speaker verification embeddings

1 code implementation30 May 2023 Sung Hwan Mun, Hye-jin Shim, Hemlata Tak, Xin Wang, Xuechen Liu, Md Sahidullah, Myeonghun Jeong, Min Hyun Han, Massimiliano Todisco, Kong Aik Lee, Junichi Yamagishi, Nicholas Evans, Tomi Kinnunen, Nam Soo Kim, Jee-weon Jung

Second, competitive performance should be demonstrated compared to the fusion of automatic speaker verification (ASV) and countermeasure (CM) embeddings, which outperformed single embedding solutions by a large margin in the SASV2022 challenge.

Speaker Verification

Controllable Text-to-Image Generation with GPT-4

no code implementations29 May 2023 Tianjun Zhang, Yi Zhang, Vibhav Vineet, Neel Joshi, Xin Wang

Control-GPT works by querying GPT-4 to write TikZ code, and the generated sketches are used as references alongside the text instructions for diffusion models (e. g., ControlNet) to generate photo-realistic images.

Instruction Following

Range-Based Equal Error Rate for Spoof Localization

1 code implementation28 May 2023 Lin Zhang, Xin Wang, Erica Cooper, Nicholas Evans, Junichi Yamagishi

To properly measure misclassified ranges and better evaluate spoof localization performance, we upgrade point-based EER to range-based EER.

Integrating Listwise Ranking into Pairwise-based Image-Text Retrieval

1 code implementation26 May 2023 Zheng Li, Caili Guo, Xin Wang, Zerun Feng, Yanjun Wang

Given a query caption, the goal is to rank candidate images by relevance, from large to small.

Retrieval Text Retrieval

WeiAvg: Federated Learning Model Aggregation Promoting Data Diversity

no code implementations24 May 2023 Fan Dong, Ali Abbasi, Steve Drew, Henry Leung, Xin Wang, Jiayu Zhou

Federated learning provides a promising privacy-preserving way for utilizing large-scale private edge data from massive Internet-of-Things (IoT) devices.

Federated Learning Privacy Preserving

TOAST: Transfer Learning via Attention Steering

1 code implementation24 May 2023 Baifeng Shi, Siyu Gai, Trevor Darrell, Xin Wang

We introduce Top-Down Attention Steering (TOAST), a novel transfer learning algorithm that keeps the pre-trained backbone frozen, selects task-relevant features in the output, and feeds those features back to the model to steer the attention to the task-specific features.

Fine-Grained Image Classification Instruction Following +2

Gorilla: Large Language Model Connected with Massive APIs

1 code implementation24 May 2023 Shishir G. Patil, Tianjun Zhang, Xin Wang, Joseph E. Gonzalez

Large Language Models (LLMs) have seen an impressive wave of advances recently, with models now excelling in a variety of tasks, such as mathematical reasoning and program synthesis.

Language Modelling Large Language Model +3

Efficient information recovery from Pauli noise via classical shadow

no code implementations6 May 2023 Yifei Chen, Zhan Yu, Chenghong Zhu, Xin Wang

The rapid advancement of quantum computing has led to an extensive demand for effective techniques to extract classical information from quantum systems, particularly in fields like quantum machine learning and quantum chemistry.

Quantum Machine Learning

Clothes Grasping and Unfolding Based on RGB-D Semantic Segmentation

no code implementations5 May 2023 Xingyu Zhu, Xin Wang, Jonathan Freer, Hyung Jin Chang, Yixing Gao

These methods often utilize physics engines to synthesize depth images to reduce the cost of real labeled data collection.

Data Augmentation Semantic Segmentation

DisenBooth: Identity-Preserving Disentangled Tuning for Subject-Driven Text-to-Image Generation

no code implementations5 May 2023 Hong Chen, YiPeng Zhang, Xin Wang, Xuguang Duan, Yuwei Zhou, Wenwu Zhu

To tackle the problems, we propose DisenBooth, an identity-preserving disentangled tuning framework for subject-driven text-to-image generation in this paper.

Denoising Disentanglement

DELTA: Dynamic Embedding Learning with Truncated Conscious Attention for CTR Prediction

no code implementations3 May 2023 Chen Zhu, Liang Du, Hong Chen, Shuang Zhao, Zixun Sun, Xin Wang, Wenwu Zhu

To tackle this problem, inspired by the Global Workspace Theory in conscious processing, which posits that only a specific subset of the product features are pertinent while the rest can be noisy and even detrimental to human-click behaviors, we propose a CTR model that enables Dynamic Embedding Learning with Truncated Conscious Attention for CTR prediction, termed DELTA.

Click-Through Rate Prediction

An Implicit Alignment for Video Super-Resolution

1 code implementation29 Apr 2023 Kai Xu, Ziwei Yu, Xin Wang, Michael Bi Mi, Angela Yao

Video super-resolution commonly uses a frame-wise alignment to support the propagation of information over time.

Video Super-Resolution

Harnessing the Power of Text-image Contrastive Models for Automatic Detection of Online Misinformation

no code implementations19 Apr 2023 Hao Chen, Peng Zheng, Xin Wang, Shu Hu, Bin Zhu, Jinrong Hu, Xi Wu, Siwei Lyu

As growing usage of social media websites in the recent decades, the amount of news articles spreading online rapidly, resulting in an unprecedented scale of potentially fraudulent information.

Contrastive Learning Misinformation +1

USNID: A Framework for Unsupervised and Semi-supervised New Intent Discovery

1 code implementation16 Apr 2023 Hanlei Zhang, Hua Xu, Xin Wang, Fei Long, Kai Gao

New intent discovery is of great value to natural language processing, allowing for a better understanding of user needs and providing friendly services.

Clustering Intent Discovery +3

Arbitrary Reduction of MRI Inter-slice Spacing Using Hierarchical Feature Conditional Diffusion

no code implementations16 Apr 2023 Xin Wang, Zhenrong Shen, Zhiyun Song, Sheng Wang, Mengjun Liu, Lichi Zhang, Kai Xuan, Qian Wang

Magnetic resonance (MR) images collected in 2D scanning protocols typically have large inter-slice spacing, resulting in high in-plane resolution but reduced through-plane resolution.


CIMI4D: A Large Multimodal Climbing Motion Dataset under Human-scene Interactions

no code implementations CVPR 2023 Ming Yan, Xin Wang, Yudi Dai, Siqi Shen, Chenglu Wen, Lan Xu, Yuexin Ma, Cheng Wang

The core of this dataset is a blending optimization process, which corrects for the pose as it drifts and is affected by the magnetic conditions.

Pose Prediction

Domain Adaptive Semantic Segmentation by Optimal Transport

no code implementations29 Mar 2023 Yaqian Guo, Xin Wang, Ce Li, Shihui Ying

Second, we utilize OT to achieve a more robust alignment of source and target domains in output space, where the OT plan defines a well attention mechanism to improve the adaptation of the model.

Autonomous Driving Domain Adaptation +1

Damage detection of high-speed railway box girder using train-induced dynamic responses

no code implementations23 Mar 2023 Xin Wang, Yi Zhuo, Shunlong Li

This paper proposes a damage detection method based on the train-induced responses of high-speed railway box girder.

Top-Down Visual Attention from Analysis by Synthesis

1 code implementation CVPR 2023 Baifeng Shi, Trevor Darrell, Xin Wang

In this paper, we consider top-down attention from a classic Analysis-by-Synthesis (AbS) perspective of vision.

Retrieval Semantic Segmentation +1

A Survey of Graph Prompting Methods: Techniques, Applications, and Challenges

no code implementations13 Mar 2023 Xuansheng Wu, Kaixiong Zhou, Mingchen Sun, Xin Wang, Ninghao Liu

In particular, we introduce the basic concepts of graph prompt learning, organize the existing work of designing graph prompting functions, and describe their applications and future challenges.

Optimal Beamforming for MIMO DFRC Systems with Transmit Covariance Constraints

no code implementations6 Mar 2023 Chenhao Yang, Xin Wang, Wei Ni, Yi Jiang

Under this approach, we reveal that the optimal receive beamforming is given by the classic MMSE one and the optimal transmit beamforming design amounts to solving an orthogonal Procrustes problem, thereby allowing for closed-form solutions to subproblems in each BCD step and fast convergence of the proposed algorithm to a high-quality (near-optimal) overall beamforming design.

Selectively Hard Negative Mining for Alleviating Gradient Vanishing in Image-Text Matching

no code implementations1 Mar 2023 Zheng Li, Caili Guo, Xin Wang, Zerun Feng, Zhongtian Du

To alleviate the gradient vanishing problem, we propose a Selectively Hard Negative Mining (SelHN) strategy, which chooses whether to mine hard negative samples according to the gradient vanishing condition.

Image-text matching Text Matching

RIS-Assisted Jamming Rejection and Path Planning for UAV-Borne IoT Platform: A New Deep Reinforcement Learning Framework

no code implementations10 Feb 2023 Shuyan Hu, Xin Yuan, Wei Ni, Xin Wang, Abbas Jamalipour

This paper presents a new deep reinforcement learning (DRL)-based approach to the trajectory planning and jamming rejection of an unmanned aerial vehicle (UAV) for the Internet-of-Things (IoT) applications.

Trajectory Planning

Unsupervised Deep Learning for IoT Time Series

no code implementations7 Feb 2023 Ya Liu, Yingjie Zhou, Kai Yang, Xin Wang

IoT time series analysis has found numerous applications in a wide variety of areas, ranging from health informatics to network security.

Clustering Representation Learning +3

Curriculum Graph Machine Learning: A Survey

no code implementations6 Feb 2023 Haoyang Li, Xin Wang, Wenwu Zhu

To the best of our knowledge, this paper is the first survey for curriculum graph machine learning.

Model Optimization

IMPORTANT-Net: Integrated MRI Multi-Parameter Reinforcement Fusion Generator with Attention Network for Synthesizing Absent Data

no code implementations3 Feb 2023 Tianyu Zhang, Tao Tan, Luyi Han, Xin Wang, Yuan Gao, Jonas Teuwen, Regina Beets-Tan, Ritse Mann

Then the multi-parameter fusion with attention module enables the interaction of the encoded information from different parameters through a set of algorithmic strategies, and applies different weights to the information through the attention mechanism after information fusion to obtain refined representation information.

Lesion Classification Lesion Detection

Synthesis-based Imaging-Differentiation Representation Learning for Multi-Sequence 3D/4D MRI

1 code implementation1 Feb 2023 Luyi Han, Tao Tan, Tianyu Zhang, Yunzhi Huang, Xin Wang, Yuan Gao, Jonas Teuwen, Ritse Mann

Multi-sequence MRIs can be necessary for reliable diagnosis in clinical practice due to the complimentary information within sequences.

Representation Learning

The Power of External Memory in Increasing Predictive Model Capacity

no code implementations31 Jan 2023 Cenk Baykal, Dylan J Cutler, Nishanth Dikkala, Nikhil Ghosh, Rina Panigrahy, Xin Wang

One way of introducing sparsity into deep networks is by attaching an external table of parameters that is sparsely looked up at different layers of the network.

Language Modelling

Alternating Updates for Efficient Transformers

no code implementations30 Jan 2023 Cenk Baykal, Dylan Cutler, Nishanth Dikkala, Nikhil Ghosh, Rina Panigrahy, Xin Wang

We introduce Alternating Updates (AltUp), a simple-to-implement method to increase a model's capacity without the computational burden.

Attacking Important Pixels for Anchor-free Detectors

no code implementations26 Jan 2023 Yunxu Xie, Shu Hu, Xin Wang, Quanyu Liao, Bin Zhu, Xi Wu, Siwei Lyu

Existing adversarial attacks on object detection focus on attacking anchor-based detectors, which may not work well for anchor-free detectors.

Adversarial Attack object-detection +2

You Do Not Need Additional Priors or Regularizers in Retinex-Based Low-Light Image Enhancement

no code implementations CVPR 2023 Huiyuan Fu, Wenkai Zheng, Xiangyu Meng, Xin Wang, Chuanming Wang, Huadong Ma

The Retinex-based methods require decomposing the image into reflectance and illumination components, which is a highly ill-posed problem and there is no available ground truth.

Contrastive Learning Low-Light Image Enhancement +1

Doubly Right Object Recognition: A Why Prompt for Visual Rationales

1 code implementation CVPR 2023 Chengzhi Mao, Revant Teotia, Amrutha Sundar, Sachit Menon, Junfeng Yang, Xin Wang, Carl Vondrick

We propose a ``doubly right'' object recognition benchmark, where the metric requires the model to simultaneously produce both the right labels as well as the right rationales.

Object Recognition

Hiding speaker's sex in speech using zero-evidence speaker representation in an analysis/synthesis pipeline

1 code implementation29 Nov 2022 Paul-Gauthier Noé, Xiaoxiao Miao, Xin Wang, Junichi Yamagishi, Jean-François Bonastre, Driss Matrouf

The use of modern vocoders in an analysis/synthesis pipeline allows us to investigate high-quality voice conversion that can be used for privacy purposes.

Voice Conversion

Disentangled Representation Learning

no code implementations21 Nov 2022 Xin Wang, Hong Chen, Si'ao Tang, Zihao Wu, Wenwu Zhu

Disentangled Representation Learning (DRL) aims to learn a model capable of identifying and disentangling the underlying factors hidden in the observable data in representation form.

Representation Learning

FedSiam-DA: Dual-aggregated Federated Learning via Siamese Network under Non-IID Data

no code implementations17 Nov 2022 Ming Yang, Yanhan Wang, Xin Wang, Zhenyong Zhang, Xiaoming Wu, Peng Cheng

Federated learning is a distributed learning that allows each client to keep the original data locally and only upload the parameters of the local model to the server.

Contrastive Learning Federated Learning

Superresolution Reconstruction of Single Image for Latent features

no code implementations16 Nov 2022 Xin Wang, Jing-Ke Yan, Jing-Ye Cai, Jian-Hua Deng, Qin Qin, Qin Wang, Heng Xiao, Yao Cheng, Peng-Fei Ye

Therefore, it is often challenging to meet the requirements of High-quality sampling, fast Sampling, and diversity of details and texture after Sampling simultaneously in a SISR task. It leads to model collapse, lack of details and texture features after Sampling, and too long Sampling time in High Resolution (HR) image reconstruction methods.

Denoising Image Reconstruction +1

Shared Loss between Generators of GANs

no code implementations14 Nov 2022 Xin Wang

Traditional GANs fall prey to the mode collapse problem, which means that they are unable to generate the different variations of data present in the input dataset.

LiDAL: Inter-frame Uncertainty Based Active Learning for 3D LiDAR Semantic Segmentation

1 code implementation11 Nov 2022 Zeyu Hu, Xuyang Bai, Runze Zhang, Xin Wang, Guangyuan Sun, Hongbo Fu, Chiew-Lan Tai

We propose LiDAL, a novel active learning method for 3D LiDAR semantic segmentation by exploiting inter-frame uncertainty among LiDAR frames.

Active Learning LIDAR Semantic Segmentation +1

Large Language Models with Controllable Working Memory

no code implementations9 Nov 2022 Daliang Li, Ankit Singh Rawat, Manzil Zaheer, Xin Wang, Michal Lukasik, Andreas Veit, Felix Yu, Sanjiv Kumar

By contrast, when the context is irrelevant to the task, the model should ignore it and fall back on its internal knowledge.

Lightweight Neural Network with Knowledge Distillation for CSI Feedback

no code implementations31 Oct 2022 Yiming Cui, Jiajia Guo, Zheng Cao, Huaze Tang, Chao-Kai Wen, Shi Jin, Xin Wang, Xiaolin Hou

Firstly, an autoencoder KD-based method is introduced by training a student autoencoder to mimic the reconstructed CSI of a pretrained teacher autoencoder.

Knowledge Distillation

Detection of Real-time DeepFakes in Video Conferencing with Active Probing and Corneal Reflection

no code implementations21 Oct 2022 Hui Guo, Xin Wang, Siwei Lyu

Specifically, we authenticate video calls by displaying a distinct pattern on the screen and using the corneal reflection extracted from the images of the call participant's face.

Spoofed training data for speech spoofing countermeasure can be efficiently created using neural vocoders

1 code implementation19 Oct 2022 Xin Wang, Junichi Yamagishi

To make better use of pairs of bona fide and spoofed data, this study introduces a contrastive feature loss that can be plugged into the standard training criterion.

InFIP: An Explainable DNN Intellectual Property Protection Method based on Intrinsic Features

no code implementations14 Oct 2022 Mingfu Xue, Xin Wang, Yinghao Wu, Shifeng Ni, Yushu Zhang, Weiqiang Liu

Since the intrinsic feature is composed of unique interpretation of the model's decision, the intrinsic feature can be regarded as fingerprint of the model.

Explainable artificial intelligence

GGViT:Multistream Vision Transformer Network in Face2Face Facial Reenactment Detection

no code implementations12 Oct 2022 Haotian Wu, Peipei Wang, Xin Wang, Ji Xiang, Rui Gong

The compression of videos on social media has destroyed some pixel details that could be used to detect forgeries.

Block Format Error Bounds and Optimal Block Size Selection

no code implementations11 Oct 2022 Ilya Soloveychik, Ilya Lyubomirsky, Xin Wang, Sudeep Bhoja

This measure allows us to determine the optimal parameters, such as the block size, yielding highest accuracy.

3D Matting: A Benchmark Study on Soft Segmentation Method for Pulmonary Nodules Applied in Computed Tomography

no code implementations11 Oct 2022 Lin Wang, Xiufen Ye, Donghao Zhang, Wanji He, Lie Ju, Yi Luo, Huan Luo, Xin Wang, Wei Feng, Kaimin Song, Xin Zhao, ZongYuan Ge

In this work, we introduce the image matting into the 3D scenes and use the alpha matte, i. e., a soft mask, to describe lesions in a 3D medical image.

Binarization Image Matting

STSyn: Speeding Up Local SGD with Straggler-Tolerant Synchronization

no code implementations6 Oct 2022 Feng Zhu, Jingjing Zhang, Xin Wang

Synchronous local stochastic gradient descent (local SGD) suffers from some workers being idle and random delays due to slow and straggling workers, as it waits for the workers to complete the same amount of local updates.

Unified Loss of Pair Similarity Optimization for Vision-Language Retrieval

no code implementations28 Sep 2022 Zheng Li, Caili Guo, Xin Wang, Zerun Feng, Jenq-Neng Hwang, Zhongtian Du

More specifically, Triplet loss with Hard Negative mining (Triplet-HN), which is widely used in existing retrieval models to improve the discriminative ability, is easy to fall into local minima in training.

Contrastive Learning Retrieval +2

3D Matting: A Soft Segmentation Method Applied in Computed Tomography

no code implementations16 Sep 2022 Lin Wang, Xiufen Ye, Donghao Zhang, Wanji He, Lie Ju, Xin Wang, Wei Feng, Kaimin Song, Xin Zhao, ZongYuan Ge

It can be caused by many factors, such as the imaging properties, pathological anatomy, and the weak representation of the binary masks, which brings challenges to accurate 3D segmentation.

Anatomy Image Matting

Joint Speaker Encoder and Neural Back-end Model for Fully End-to-End Automatic Speaker Verification with Multiple Enrollment Utterances

no code implementations1 Sep 2022 Chang Zeng, Xiaoxiao Miao, Xin Wang, Erica Cooper, Junichi Yamagishi

Conventional automatic speaker verification systems can usually be decomposed into a front-end model such as time delay neural network (TDNN) for extracting speaker embeddings and a back-end model such as statistics-based probabilistic linear discriminant analysis (PLDA) or neural network-based neural PLDA (NPLDA) for similarity scoring.

Data Augmentation Speaker Verification

NeurIPS'22 Cross-Domain MetaDL competition: Design and baseline results

no code implementations31 Aug 2022 Dustin Carrión-Ojeda, Hong Chen, Adrian El Baz, Sergio Escalera, Chaoyu Guan, Isabelle Guyon, Ihsan Ullah, Xin Wang, Wenwu Zhu

We present the design and baseline results for a new challenge in the ChaLearn meta-learning series, accepted at NeurIPS'22, focusing on "cross-domain" meta-learning.

Few-Shot Image Classification Few-Shot Learning +1

NL2GDPR: Automatically Develop GDPR Compliant Android Application Features from Natural Language

no code implementations29 Aug 2022 Faysal Hossain Shezan, Yingjie Lao, Minlong Peng, Xin Wang, Mingming Sun, Ping Li

At the core, NL2GDPR is a privacy-centric information extraction model, appended with a GDPR policy finder and a policy generator.

Data-Driven Control of Distributed Event-Triggered Network Systems

no code implementations22 Aug 2022 Xin Wang, Jian Sun, Gang Wang, Frank Allgöwer, Jie Chen

The present paper deals with data-driven event-triggered control of a class of unknown discrete-time interconnected systems (a. k. a.

Efficient Climate Simulation via Machine Learning Method

no code implementations15 Aug 2022 Xin Wang, Wei Xue, Yilun Han, Guangwen Yang

We develop a user-friendly platform NeuroGCM for efficiently developing hybrid modeling in climate simulation.

GPPT: Graph Pre-training and Prompt Tuning to Generalize Graph Neural Networks

1 code implementation SIGKDD 2022 Mingchen Sun, Kaixiong Zhou, Xin He, Ying Wang, Xin Wang

Based on the pre-trained model, we propose the graph prompting function to modify the standalone node into a token pair, and reformulate the downstream node classification looking the same as edge prediction.

Few-Shot Learning Node Classification +3

Revisiting Adversarial Attacks on Graph Neural Networks for Graph Classification

no code implementations13 Aug 2022 Xin Wang, Heng Chang, Beini Xie, Tian Bian, Shiji Zhou, Daixin Wang, Zhiqiang Zhang, Wenwu Zhu

Graph neural networks (GNNs) have achieved tremendous success in the task of graph classification and its diverse downstream real-world applications.

Graph Classification

A Theoretical View on Sparsely Activated Networks

no code implementations8 Aug 2022 Cenk Baykal, Nishanth Dikkala, Rina Panigrahy, Cyrus Rashtchian, Xin Wang

After representing LSH-based sparse networks with our model, we prove that sparse networks can match the approximation power of dense networks on Lipschitz functions.

Event-triggered Consensus Control of Heterogeneous Multi-agent Systems: Model- and Data-based Analysis

no code implementations1 Aug 2022 Xin Wang, Jian Sun, Gang Wang, Jie Chen

This article deals with model- and data-based consensus control of heterogenous leader-following multi-agent systems (MASs) under an event-triggering transmission scheme.

Trajectory Planning of Cellular-Connected UAV for Communication-assisted Radar Sensing

no code implementations27 Jul 2022 Shuyan Hu, Xin Yuan, Wei Ni, Xin Wang

Being a key technology for beyond fifth-generation wireless systems, joint communication and radar sensing (JCAS) utilizes the reflections of communication signals to detect foreign objects and deliver situational awareness.

Trajectory Planning

Proving Common Mechanisms Shared by Twelve Methods of Boosting Adversarial Transferability

no code implementations24 Jul 2022 Quanshi Zhang, Xin Wang, Jie Ren, Xu Cheng, Shuyun Lin, Yisen Wang, Xiangming Zhu

This paper summarizes the common mechanism shared by twelve previous transferability-boosting methods in a unified view, i. e., these methods all reduce game-theoretic interactions between regional adversarial perturbations.

PanGu-Coder: Program Synthesis with Function-Level Language Modeling

1 code implementation22 Jul 2022 Fenia Christopoulou, Gerasimos Lampouras, Milan Gritta, Guchun Zhang, Yinpeng Guo, Zhongqi Li, Qi Zhang, Meng Xiao, Bo Shen, Lin Li, Hao Yu, Li Yan, Pingyi Zhou, Xin Wang, Yuchi Ma, Ignacio Iacobacci, Yasheng Wang, Guangtai Liang, Jiansheng Wei, Xin Jiang, Qianxiang Wang, Qun Liu

We present PanGu-Coder, a pretrained decoder-only language model adopting the PanGu-Alpha architecture for text-to-code generation, i. e. the synthesis of programming language solutions given a natural language problem description.

Code Generation Language Modelling +2

Neural-Sim: Learning to Generate Training Data with NeRF

1 code implementation22 Jul 2022 Yunhao Ge, Harkirat Behl, Jiashu Xu, Suriya Gunasekar, Neel Joshi, Yale Song, Xin Wang, Laurent Itti, Vibhav Vineet

However, existing approaches either require human experts to manually tune each scene property or use automatic methods that provide little to no control; this requires rendering large amounts of random data variations, which is slow and is often suboptimal for the target domain.

Object Detection

Scene Recognition with Objectness, Attribute and Category Learning

no code implementations20 Jul 2022 Ji Zhang, Jean-Paul Ainam, Li-hui Zhao, Wenai Song, Xin Wang

Based on the complementarity of attribute and category labels, we propose a Multi-task Attribute-Scene Recognition (MASR) network which learns a category embedding and at the same time predicts scene attributes.

Scene Classification Scene Recognition

Rank-based Decomposable Losses in Machine Learning: A Survey

no code implementations18 Jul 2022 Shu Hu, Xin Wang, Siwei Lyu

Following these categories, we review the literature on rank-based aggregate losses and rank-based individual losses.

BIG-bench Machine Learning

Scaling Novel Object Detection with Weakly Supervised Detection Transformers

1 code implementation11 Jul 2022 Tyler LaBonte, Yale Song, Xin Wang, Vibhav Vineet, Neel Joshi

A critical object detection task is finetuning an existing model to detect novel objects, but the standard workflow requires bounding box annotations which are time-consuming and expensive to collect.

Multiple Instance Learning object-detection +2

Unsupervised Domain Adaptive Fundus Image Segmentation with Category-level Regularization

1 code implementation8 Jul 2022 Wei Feng, Lin Wang, Lie Ju, Xin Zhao, Xin Wang, Xiaoyu Shi, ZongYuan Ge

Existing unsupervised domain adaptation methods based on adversarial learning have achieved good performance in several medical imaging tasks.

Image Segmentation Semantic Segmentation +1

Enhanced brain structure-function tethering in transmodal cortex revealed by high-frequency eigenmodes

no code implementations7 Jul 2022 Yaqian Yang, Zhiming Zheng, Longzhao Liu, Hongwei Zheng, Yi Zhen, Yi Zheng, Xin Wang, Shaoting Tang

Specifically, low-frequency eigenmodes, which are considered sufficient to capture the essence of the functional network, contribute little to functional connectivity reconstruction in transmodal regions, resulting in structure-function decoupling along the unimodal-transmodal gradient.

NAS-Bench-Graph: Benchmarking Graph Neural Architecture Search

1 code implementation18 Jun 2022 Yijian Qin, Ziwei Zhang, Xin Wang, Zeyang Zhang, Wenwu Zhu

To the best of our knowledge, our work is the first benchmark for graph neural architecture search.

Benchmarking Neural Architecture Search

Concentration of Data Encoding in Parameterized Quantum Circuits

no code implementations16 Jun 2022 Guangxi Li, Ruilin Ye, Xuanqiang Zhao, Xin Wang

This result in particular implies that the average encoded state will concentrate on the maximally mixed state at an exponential speed on depth.

Combinatorial Optimization

A Comprehensive Survey on Deep Clustering: Taxonomy, Challenges, and Future Directions

1 code implementation15 Jun 2022 Sheng Zhou, Hongjia Xu, Zhuonan Zheng, Jiawei Chen, Zhao Li, Jiajun Bu, Jia Wu, Xin Wang, Wenwu Zhu, Martin Ester

Motivated by the tremendous success of deep learning in clustering, one of the most fundamental machine learning tasks, and the large number of recent advances in this direction, in this paper we conduct a comprehensive survey on deep clustering by proposing a new taxonomy of different state-of-the-art approaches.

Clustering Deep Clustering +1

Deep Learning-based Massive MIMO CSI Acquisition for 5G Evolution and 6G

no code implementations10 Jun 2022 Xin Wang, Xiaolin Hou, Lan Chen, Yoshihisa Kishiyama, Takahiro Asai

Considering its large impact on air-interface design, it will be a candidate technology for 6th generation (6G) networks, in which an air interface designed by artificial intelligence can be used.

Mitigating barren plateaus of variational quantum eigensolvers

no code implementations26 May 2022 Xia Liu, Geng Liu, Jiaxin Huang, Hao-Kai Zhang, Xin Wang

Variational quantum algorithms (VQAs) are expected to establish valuable applications on near-term quantum computers.

Spatial Attention-based Implicit Neural Representation for Arbitrary Reduction of MRI Slice Spacing

no code implementations23 May 2022 Xin Wang, Sheng Wang, Honglin Xiong, Kai Xuan, Zixu Zhuang, Mengjun Liu, Zhenrong Shen, Xiangyu Zhao, Lichi Zhang, Qian Wang

Magnetic resonance (MR) images collected in 2D clinical protocols typically have large inter-slice spacing, resulting in high in-plane resolution and reduced through-plane resolution.


Power and limitations of single-qubit native quantum neural networks

no code implementations16 May 2022 Zhan Yu, Hongshun Yao, Mujin Li, Xin Wang

Quantum neural networks (QNNs) have emerged as a leading strategy to establish applications in machine learning, chemistry, and optimization.

The VoicePrivacy 2020 Challenge Evaluation Plan

1 code implementation14 May 2022 Natalia Tomashenko, Brij Mohan Lal Srivastava, Xin Wang, Emmanuel Vincent, Andreas Nautsch, Junichi Yamagishi, Nicholas Evans, Jose Patino, Jean-François Bonastre, Paul-Gauthier Noé, Massimiliano Todisco

The VoicePrivacy Challenge aims to promote the development of privacy preservation tools for speech technology by gathering a new community to define the tasks of interest and the evaluation methodology, and benchmarking solutions through a series of challenges.


Open-Eye: An Open Platform to Study Human Performance on Identifying AI-Synthesized Faces

no code implementations13 May 2022 Hui Guo, Shu Hu, Xin Wang, Ming-Ching Chang, Siwei Lyu

In this work, we develop an online platform called Open-eye to study the human performance of AI-synthesized face detection.

Face Detection

Quantum Self-Attention Neural Networks for Text Classification

no code implementations11 May 2022 Guangxi Li, Xuanqiang Zhao, Xin Wang

Although some efforts based on syntactic analysis have opened the door to research in Quantum NLP (QNLP), limitations such as heavy syntactic preprocessing and syntax-dependent network architecture make them impracticable on larger and real-world data sets.

text-classification Text Classification

Fundamental limitations on optimization in variational quantum algorithms

no code implementations10 May 2022 Hao-Kai Zhang, Chengkai Zhu, Geng Liu, Xin Wang

Exploring quantum applications of near-term quantum devices is a rapidly growing field of quantum information science with both theoretical and practical interests.

An Edge-Cloud Integrated Framework for Flexible and Dynamic Stream Analytics

no code implementations10 May 2022 Xin Wang, Azim Khan, Jianwu Wang, Aryya Gangopadhyay, Carl E. Busart, Jade Freeman

In this paper, we study how to best leverage edge and cloud resources to achieve better accuracy and latency for stream analytics using a type of RNN model called long short-term memory (LSTM).

Cloud Computing Edge-computing +3

CODE-MVP: Learning to Represent Source Code from Multiple Views with Contrastive Pre-Training

no code implementations Findings (NAACL) 2022 Xin Wang, Yasheng Wang, Yao Wan, Jiawei Wang, Pingyi Zhou, Li Li, Hao Wu, Jin Liu

Specifically, we first extract multiple code views using compiler tools, and learn the complementary information among them under a contrastive learning framework.

Contrastive Learning Defect Detection +2

Receiver Design for MIMO Unsourced Random Access with SKP Coding

no code implementations30 Apr 2022 Zeyu Han, Xiaojun Yuan, Chongbin Xu, Xin Wang

In this letter, we extend the sparse Kronecker-product (SKP) coding scheme, originally designed for the additive white Gaussian noise (AWGN) channel, to multiple input multiple output (MIMO) unsourced random access (URA).

Visual Attention Emerges from Recurrent Sparse Reconstruction

1 code implementation23 Apr 2022 Baifeng Shi, Yale Song, Neel Joshi, Trevor Darrell, Xin Wang

We present VARS, Visual Attention from Recurrent Sparse reconstruction, a new attention formulation built on two prominent features of the human visual attention mechanism: recurrency and sparsity.

The PartialSpoof Database and Countermeasures for the Detection of Short Fake Speech Segments Embedded in an Utterance

no code implementations11 Apr 2022 Lin Zhang, Xin Wang, Erica Cooper, Nicholas Evans, Junichi Yamagishi

Since the short spoofed speech segments to be embedded by attackers are of variable length, six different temporal resolutions are considered, ranging from as short as 20 ms to as large as 640 ms. Third, we propose a new CM that enables the simultaneous use of the segment-level labels at different temporal resolutions as well as utterance-level labels to execute utterance- and segment-level detection at the same time.

Speaker Verification Speech Synthesis +2

Flexible Sampling for Long-tailed Skin Lesion Classification

no code implementations7 Apr 2022 Lie Ju, Yicheng Wu, Lin Wang, Zhen Yu, Xin Zhao, Xin Wang, Paul Bonnington, ZongYuan Ge

To address this, in this paper, we propose a curriculum learning-based framework called Flexible Sampling for the long-tailed skin lesion classification task.

Classification Lesion Classification +1

Learning to Solve Travelling Salesman Problem with Hardness-adaptive Curriculum

1 code implementation7 Apr 2022 Zeyang Zhang, Ziwei Zhang, Xin Wang, Wenwu Zhu

To solve these challenges, we first propose a principled hardness measurement to quantify the hardness of TSP instances.

Combinatorial Optimization

Investigating Active-learning-based Training Data Selection for Speech Spoofing Countermeasure

1 code implementation28 Mar 2022 Xin Wang, Junich Yamagishi

This study took the initiative and investigated CM training using active learning (AL), a framework that iteratively selects useful data from a large pool set and fine-tunes the CM.

Active Learning Data Augmentation +1

Energy-Efficient UAV-Mounted RIS Assisted Mobile Edge Computing

no code implementations24 Mar 2022 Zhiyuan Zhai, Xinhong Dai, Bin Duo, Xin Wang, Xiaojun Yuan

Unmanned aerial vehicle (UAV) and reconfigurable intelligent surface (RIS) have been recently applied in the field of mobile edge computing (MEC) to improve the data exchange environment by proactively changing the wireless channels through maneuverable location deployment and intelligent signals reflection, respectively.


The VoicePrivacy 2022 Challenge Evaluation Plan

1 code implementation23 Mar 2022 Natalia Tomashenko, Xin Wang, Xiaoxiao Miao, Hubert Nourtel, Pierre Champion, Massimiliano Todisco, Emmanuel Vincent, Nicholas Evans, Junichi Yamagishi, Jean-François Bonastre

Participants apply their developed anonymization systems, run evaluation scripts and submit objective evaluation results and anonymized speech data to the organizers.

Speaker Verification

A Closer Look at Debiased Temporal Sentence Grounding in Videos: Dataset, Metric, and Approach

no code implementations10 Mar 2022 Xiaohan Lan, Yitian Yuan, Xin Wang, Long Chen, Zhi Wang, Lin Ma, Wenwu Zhu

New benchmarking results indicate that our proposed evaluation protocols can better monitor the research progress.


Compilable Neural Code Generation with Compiler Feedback

no code implementations Findings (ACL) 2022 Xin Wang, Yasheng Wang, Yao Wan, Fei Mi, Yitong Li, Pingyi Zhou, Jin Liu, Hao Wu, Xin Jiang, Qun Liu

Automatically generating compilable programs with (or without) natural language descriptions has always been a touchstone problem for computational linguistics and automated software engineering.

Code Completion Code Generation +3

Optimal quantum dataset for learning a unitary transformation

no code implementations1 Mar 2022 Zhan Yu, Xuanqiang Zhao, Benchi Zhao, Xin Wang

In this work, we solve the problem on the minimum size of sufficient quantum datasets for learning a unitary transformation exactly, which reveals the power and limitation of quantum data.

Quantum Machine Learning

Synergistic Network Learning and Label Correction for Noise-robust Image Classification

no code implementations27 Feb 2022 Chen Gong, Kong Bin, Eric J. Seibel, Xin Wang, Youbing Yin, Qi Song

Taking the expertise of DNNs to learn meaningful patterns before fitting noise, our framework first trains two networks over the current dataset with small loss selection.

Image Classification

Model-Based and Data-Driven Control of Event- and Self-Triggered Discrete-Time LTI Systems

no code implementations16 Feb 2022 Xin Wang, Julian Berberich, Jian Sun, Gang Wang, Frank Allgöwer, Jie Chen

To this end, we begin by presenting a dynamic event-triggering scheme (ETS) based on periodic sampling, and a discrete-time looped-functional approach, through which a model-based stability condition is derived.


Out-Of-Distribution Generalization on Graphs: A Survey

no code implementations16 Feb 2022 Haoyang Li, Xin Wang, Ziwei Zhang, Wenwu Zhu

This paper is the first systematic and comprehensive review of OOD generalization on graphs, to the best of our knowledge.

Out-of-Distribution Generalization

GAN-generated Faces Detection: A Survey and New Perspectives

no code implementations15 Feb 2022 Xin Wang, Hui Guo, Shu Hu, Ming-Ching Chang, Siwei Lyu

Generative Adversarial Networks (GAN) have led to the generation of very realistic face images, which have been used in fake social media accounts and other disinformation matters that can generate profound impacts.

Face Detection

Pan More Gold from the Sand: Refining Open-domain Dialogue Training with Noisy Self-Retrieval Generation

no code implementations COLING 2022 Yihe Wang, Yitong Li, Yasheng Wang, Fei Mi, Pingyi Zhou, Xin Wang, Jin Liu, Xin Jiang, Qun Liu

Experiments over publicly available datasets demonstrate that our method can help models generate better responses, even such training data are usually impressed as low-quality data.

Dialogue Generation Retrieval

Dichotomic Pattern Mining with Applications to Intent Prediction from Semi-Structured Clickstream Datasets

no code implementations23 Jan 2022 Xin Wang, Serdar Kadioglu

We introduce a pattern mining framework that operates on semi-structured datasets and exploits the dichotomy between outcomes.

Adaptive Worker Grouping For Communication-Efficient and Straggler-Tolerant Distributed SGD

no code implementations12 Jan 2022 Feng Zhu, Jingjing Zhang, Osvaldo Simeone, Xin Wang

Wall-clock convergence time and communication load are key performance metrics for the distributed implementation of stochastic gradient descent (SGD) in parameter server settings.

Robust Contrastive Learning against Noisy Views

1 code implementation CVPR 2022 Ching-Yao Chuang, R Devon Hjelm, Xin Wang, Vibhav Vineet, Neel Joshi, Antonio Torralba, Stefanie Jegelka, Yale Song

Contrastive learning relies on an assumption that positive pairs contain related views, e. g., patches of an image or co-occurring multimodal signals of a video, that share certain underlying information about an instance.

Binary Classification Contrastive Learning

A Practical Guide to Logical Access Voice Presentation Attack Detection

1 code implementation10 Jan 2022 Xin Wang, Junichi Yamagishi

Presentation attack detection (PAD) for ASV, or speech anti-spoofing, is therefore indispensable.

Speaker Verification Speech Synthesis +1

Self-directed Machine Learning

no code implementations4 Jan 2022 Wenwu Zhu, Xin Wang, Pengtao Xie

Inspired by the concept of self-directed human learning, we introduce the principal concept of Self-directed Machine Learning (SDML) and propose a framework for SDML.

BIG-bench Machine Learning Model Selection

Revisiting Transformation Invariant Geometric Deep Learning: Are Initial Representations All You Need?

no code implementations23 Dec 2021 Ziwei Zhang, Xin Wang, Zeyang Zhang, Peng Cui, Wenwu Zhu

Based on the experimental results, we advocate that TinvNN should be considered a new starting point and an essential baseline for further studies of transformation-invariant geometric deep learning.

Combinatorial Optimization Inductive Bias

A Scalable Deep Reinforcement Learning Model for Online Scheduling Coflows of Multi-Stage Jobs for High Performance Computing

no code implementations21 Dec 2021 Xin Wang, Hong Shen

Coflow is a recently proposed networking abstraction to help improve the communication performance of data-parallel computing jobs.

Reinforcement Learning (RL) Scheduling

Decentralized Stochastic Proximal Gradient Descent with Variance Reduction over Time-varying Networks

no code implementations20 Dec 2021 Xuanjie Li, Yuedong Xu, Jessie Hui Wang, Xin Wang, John C. S. Lui

By transforming our decentralized algorithm into a centralized inexact proximal gradient algorithm with variance reduction, and controlling the bounds of error sequences, we prove that DPSVRG converges at the rate of $O(1/T)$ for general convex objectives plus a non-smooth term with $T$ as the number of iterations, while DSPG converges at the rate $O(\frac{1}{\sqrt{T}})$.

Reproducible and Portable Big Data Analytics in the Cloud

1 code implementation17 Dec 2021 Xin Wang, Pei Guo, Xingyan Li, Aryya Gangopadhyay, Carl E. Busart, Jade Freeman, Jianwu Wang

To tackle these problems, we leverage serverless computing and containerization techniques for automated scalable execution and reproducibility, and utilize the adapter design pattern to enable application portability and reproducibility across different clouds.

Cloud Computing Descriptive

Stochastic Actor-Executor-Critic for Image-to-Image Translation

1 code implementation14 Dec 2021 Ziwei Luo, Jing Hu, Xin Wang, Siwei Lyu, Bin Kong, Youbing Yin, Qi Song, Xi Wu

Training a model-free deep reinforcement learning model to solve image-to-image translation is difficult since it involves high-dimensional continuous state and action spaces.

Continuous Control Image-to-Image Translation +3

You Can Wash Better: Daily Handwashing Assessment with Smartwatches

no code implementations9 Dec 2021 Fei Wang, Xilei Wu, Xin Wang, Jianlei Chi, Jingang Shi, Dong Huang

We propose UWash, an intelligent solution upon smartwatches, to assess handwashing for the purpose of raising users' awareness and cultivating habits in high-quality handwashing.

Gesture Recognition Semantic Segmentation

OOD-GNN: Out-of-Distribution Generalized Graph Neural Network

no code implementations7 Dec 2021 Haoyang Li, Xin Wang, Ziwei Zhang, Wenwu Zhu

Our proposed OOD-GNN employs a novel nonlinear graph representation decorrelation method utilizing random Fourier features, which encourages the model to eliminate the statistical dependence between relevant and irrelevant graph representations through iteratively optimizing the sample graph weights and graph encoder.

Out-of-Distribution Generalization

Towards a Unified Game-Theoretic View of Adversarial Perturbations and Robustness

1 code implementation NeurIPS 2021 Jie Ren, Die Zhang, Yisen Wang, Lu Chen, Zhanpeng Zhou, Yiting Chen, Xu Cheng, Xin Wang, Meng Zhou, Jie Shi, Quanshi Zhang

This paper provides a unified view to explain different adversarial attacks and defense methods, i. e. the view of multi-order interactions between input variables of DNNs.

Adversarial Robustness

Curriculum Disentangled Recommendation with Noisy Multi-feedback

1 code implementation NeurIPS 2021 Hong Chen, Yudong Chen, Xin Wang, Ruobing Xie, Rui Wang, Feng Xia, Wenwu Zhu

However, learning such disentangled representations from multi-feedback data is challenging because i) multi-feedback is complex: there exist complex relations among different types of feedback (e. g., click, unclick, and dislike, etc) as well as various user intentions, and ii) multi-feedback is noisy: there exists noisy (useless) information both in features and labels, which may deteriorate the recommendation performance.

Denoising Representation Learning

Not All Low-Pass Filters are Robust in Graph Convolutional Networks

1 code implementation NeurIPS 2021 Heng Chang, Yu Rong, Tingyang Xu, Yatao Bian, Shiji Zhou, Xin Wang, Junzhou Huang, Wenwu Zhu

Graph Convolutional Networks (GCNs) are promising deep learning approaches in learning representations for graph-structured data.

Disentangled Contrastive Learning on Graphs

no code implementations NeurIPS 2021 Haoyang Li, Xin Wang, Ziwei Zhang, Zehuan Yuan, Hang Li, Wenwu Zhu

Then we propose a novel factor-wise discrimination objective in a contrastive learning manner, which can force the factorized representations to independently reflect the expressive information from different latent factors.

Contrastive Learning Self-Supervised Learning

Graph Differentiable Architecture Search with Structure Learning

no code implementations NeurIPS 2021 Yijian Qin, Xin Wang, Zeyang Zhang, Wenwu Zhu

Extensive experiments on real-world graph datasets demonstrate that our proposed GASSO model is able to achieve state-of-the-art performance compared with existing baselines.

Denoising Graph structure learning +1

HybridGazeNet: Geometric model guided Convolutional Neural Networks for gaze estimation

no code implementations23 Nov 2021 Shaobo Guo, Xiao Jiang, Zhizhong Su, Rui Wu, Xin Wang

As a critical cue for understanding human intention, human gaze provides a key signal for Human-Computer Interaction(HCI) applications.

Gaze Estimation

Active Learning Meets Optimized Item Selection

no code implementations22 Nov 2021 Bernard Kleynhans, Xin Wang, Serdar Kadıoğlu

Designing recommendation systems with limited or no available training data remains a challenge.

Active Learning Clustering +2

Hierarchical Knowledge Guided Learning for Real-world Retinal Diseases Recognition

no code implementations17 Nov 2021 Lie Ju, Zhen Yu, Lin Wang, Xin Zhao, Xin Wang, Paul Bonnington, ZongYuan Ge

From a modeling perspective, most deep learning models trained on these datasets may lack the ability to generalize to rare diseases where only a few available samples are presented for training.

Knowledge Distillation

Investigating self-supervised front ends for speech spoofing countermeasures

1 code implementation15 Nov 2021 Xin Wang, Junichi Yamagishi

Self-supervised speech model is a rapid progressing research topic, and many pre-trained models have been released and used in various down stream tasks.

Face Swapping

A Unified Game-Theoretic Interpretation of Adversarial Robustness

1 code implementation5 Nov 2021 Jie Ren, Die Zhang, Yisen Wang, Lu Chen, Zhanpeng Zhou, Yiting Chen, Xu Cheng, Xin Wang, Meng Zhou, Jie Shi, Quanshi Zhang

This paper provides a unified view to explain different adversarial attacks and defense methods, \emph{i. e.} the view of multi-order interactions between input variables of DNNs.

Adversarial Robustness

CAP: Co-Adversarial Perturbation on Weights and Features for Improving Generalization of Graph Neural Networks

no code implementations28 Oct 2021 Haotian Xue, Kaixiong Zhou, Tianlong Chen, Kai Guo, Xia Hu, Yi Chang, Xin Wang

In this paper, we investigate GNNs from the lens of weight and feature loss landscapes, i. e., the loss changes with respect to model weights and node features, respectively.

Data-driven Control of Dynamic Event-triggered Systems with Delays

no code implementations25 Oct 2021 Xin Wang, Jian Sun, Julian Berberich, Gang Wang, Frank Allgöwer, Jie Chen

Data-based representations for time-invariant linear systems with known or unknown system input matrices are first developed, along with a novel class of dynamic triggering schemes for sampled-data systems with time delays.

Evaluation of Various Open-Set Medical Imaging Tasks with Deep Neural Networks

no code implementations21 Oct 2021 ZongYuan Ge, Xin Wang

The current generation of deep neural networks has achieved close-to-human results on "closed-set" image recognition; that is, the classes being evaluated overlap with the training classes.

Decision Making Open Set Learning

Efficiently Solve the Max-cut Problem via a Quantum Qubit Rotation Algorithm

1 code implementation15 Oct 2021 Xin Wang

The quantum circuits are comprised with single-qubit rotation gates implementing on each qubit.

Combinatorial Optimization

Estimating the confidence of speech spoofing countermeasure

1 code implementation10 Oct 2021 Xin Wang, Junichi Yamagishi

On the ASVspoof2019 logical access database, the results demonstrate that an energy-based estimator and a neural-network-based one achieved acceptable performance in identifying unknown attacks in the test set.

Provable hierarchical lifelong learning with a sketch-based modular architecture

no code implementations29 Sep 2021 Rina Panigrahy, Brendan Juba, Zihao Deng, Xin Wang, Zee Fryer

We propose a modular architecture for lifelong learning of hierarchically structured tasks.


no code implementations29 Sep 2021 Xu Cheng, Xin Wang, Haotian Xue, Zhengyang Liang, Xin Jin, Quanshi Zhang

This paper proposes a hypothesis to analyze the underlying reason for the cognitive difficulty of an image from two perspectives, i. e. a cognitive image usually makes a DNN strongly activated by cognitive concepts; discarding massive non-cognitive concepts may also help the DNN focus on cognitive concepts.