Search Results for author: Xiao Yang

Found 88 papers, 38 papers with code

Using Word Embeddings in Twitter Election Classification

no code implementations22 Jun 2016 Xiao Yang, Craig Macdonald, Iadh Ounis

In this paper, using a Twitter election classification task that aims to detect election-related tweets, we investigate the impact of the background dataset used to train the embedding models, the context window size and the dimensionality of word embeddings on the classification performance.

Classification General Classification +3

Fast Predictive Image Registration

no code implementations8 Jul 2016 Xiao Yang, Roland Kwitt, Marc Niethammer

We present a method to predict image deformations based on patch-wise image appearance.

Image Registration

Efficient Registration of Pathological Images: A Joint PCA/Image-Reconstruction Approach

no code implementations31 Mar 2017 Xu Han, Xiao Yang, Stephen Aylward, Roland Kwitt, Marc Niethammer

Registration involving one or more images containing pathologies is challenging, as standard image similarity measures and spatial transforms cannot account for common changes due to pathologies.

Image Reconstruction

Fast Predictive Multimodal Image Registration

no code implementations31 Mar 2017 Xiao Yang, Roland Kwitt, Martin Styner, Marc Niethammer

We introduce a deep encoder-decoder architecture for image deformation prediction from multimodal images.

Image Registration

Learning non-parametric Markov networks with mutual information

1 code implementation8 Aug 2017 Janne Leppä-aho, Santeri Räisänen, Xiao Yang, Teemu Roos

We propose a method for learning Markov network structures for continuous data without invoking any assumptions about the distribution of the variables.

Adversarial Training for Community Question Answer Selection Based on Multi-scale Matching

no code implementations22 Apr 2018 Xiao Yang, Miaosen Wang, Wei Wang, Madian Khabsa, Ahmed Awadallah, Daniel Kifer, C. Lee Giles

We frame this task as a binary (relevant/irrelevant) classification problem, and present an adversarial training framework to alleviate label imbalance issue.

Answer Selection General Classification

Distractor Generation for Multiple Choice Questions Using Learning to Rank

1 code implementation WS 2018 Chen Liang, Xiao Yang, Neisarg Dave, Drew Wham, Bart Pursel, C. Lee Giles

We investigate how machine learning models, specifically ranking models, can be used to select useful distractors for multiple choice questions.

BIG-bench Machine Learning Distractor Generation +3

TextContourNet: a Flexible and Effective Framework for Improving Scene Text Detection Architecture with a Multi-task Cascade

no code implementations9 Sep 2018 Dafang He, Xiao Yang, Daniel Kifer, C. Lee Giles

We propose a novel and effective framework for this and experimentally demonstrate that: (1) A CNN that can be effectively used to extract instance-level text contour from natural images.

Scene Text Detection Text Detection

AiAds: Automated and Intelligent Advertising System for Sponsored Search

no code implementations28 Jul 2019 Xiao Yang, Daren Sun, Ruiwei Zhu, Tao Deng, Zhi Guo, Jiao Ding, Shouke Qin, Zongyao Ding, Yanfeng Zhu

Sponsored search has more than 20 years of history, and it has been proven to be a successful business model for online advertising.

Marketing Retrieval

Design and Interpretation of Universal Adversarial Patches in Face Detection

no code implementations ECCV 2020 Xiao Yang, Fangyun Wei, Hongyang Zhang, Jun Zhu

We consider universal adversarial patches for faces -- small visual elements whose addition to a face image reliably destroys the performance of face detectors.

Face Detection

Benchmarking Adversarial Robustness

no code implementations26 Dec 2019 Yinpeng Dong, Qi-An Fu, Xiao Yang, Tianyu Pang, Hang Su, Zihao Xiao, Jun Zhu

Deep neural networks are vulnerable to adversarial examples, which becomes one of the most important research problems in the development of deep learning.

Adversarial Attack Adversarial Robustness +2

Boosting Adversarial Training with Hypersphere Embedding

1 code implementation NeurIPS 2020 Tianyu Pang, Xiao Yang, Yinpeng Dong, Kun Xu, Jun Zhu, Hang Su

Adversarial training (AT) is one of the most effective defenses against adversarial attacks for deep learning models.

Representation Learning

Towards Face Encryption by Generating Adversarial Identity Masks

1 code implementation ICCV 2021 Xiao Yang, Yinpeng Dong, Tianyu Pang, Hang Su, Jun Zhu, Yuefeng Chen, Hui Xue

As billions of personal data being shared through social media and network, the data privacy and security have drawn an increasing attention.

Face Recognition

RobFR: Benchmarking Adversarial Robustness on Face Recognition

2 code implementations8 Jul 2020 Xiao Yang, Dingcheng Yang, Yinpeng Dong, Hang Su, Wenjian Yu, Jun Zhu

Based on large-scale evaluations, the commercial FR API services fail to exhibit acceptable performance on robustness evaluation, and we also draw several important conclusions for understanding the adversarial robustness of FR models and providing insights for the design of robust FR models.

Adversarial Robustness Benchmarking +1

Qlib: An AI-oriented Quantitative Investment Platform

2 code implementations22 Sep 2020 Xiao Yang, Weiqing Liu, Dong Zhou, Jiang Bian, Tie-Yan Liu

Quantitative investment aims to maximize the return and minimize the risk in a sequential trading period over a set of financial instruments.

Portfolio Optimization Stock Market Prediction

BayesAdapter: Being Bayesian, Inexpensively and Robustly, via Bayesian Fine-tuning

no code implementations28 Sep 2020 Zhijie Deng, Xiao Yang, Hao Zhang, Yinpeng Dong, Jun Zhu

Despite their theoretical appealingness, Bayesian neural networks (BNNs) are falling far behind in terms of adoption in real-world applications compared with normal NNs, mainly due to their limited scalability in training, and low fidelity in their uncertainty estimates.

Uncertainty Quantification Variational Inference

Bag of Tricks for Adversarial Training

2 code implementations ICLR 2021 Tianyu Pang, Xiao Yang, Yinpeng Dong, Hang Su, Jun Zhu

Adversarial training (AT) is one of the most effective strategies for promoting model robustness.

Adversarial Robustness Benchmarking

Incentive Mechanism Design for ROI-constrained Auto-bidding

no code implementations4 Dec 2020 Bin Li, Xiao Yang, Daren Sun, Zhi Ji, Zhen Jiang, Cong Han, Dong Hao

Auto-bidding plays an important role in online advertising and has become a crucial tool for advertisers and advertising platforms to meet their performance objectives and optimize the efficiency of ad delivery.

Computer Science and Game Theory

Joint Network Topology Inference via Structured Fusion Regularization

no code implementations5 Mar 2021 Yanli Yuan, De Wen Soh, Xiao Yang, Kun Guo, Tony Q. S. Quek

Theoretically, we provide a theoretical analysis of the proposed graph estimator, which establishes a non-asymptotic bound of the estimation error under the high-dimensional setting and reflects the effect of several key factors on the convergence rate of our algorithm.

Computational Efficiency

Black-box Detection of Backdoor Attacks with Limited Information and Data

no code implementations ICCV 2021 Yinpeng Dong, Xiao Yang, Zhijie Deng, Tianyu Pang, Zihao Xiao, Hang Su, Jun Zhu

Although deep neural networks (DNNs) have made rapid progress in recent years, they are vulnerable in adversarial environments.

PointShuffleNet: Learning Non-Euclidean Features with Homotopy Equivalence and Mutual Information

no code implementations31 Mar 2021 Linchao He, Mengting Luo, Dejun Zhang, Xiao Yang, Hu Chen, Yi Zhang

In this paper, we introduce the homotopy equivalence relation (HER) to make the neural networks learn the data distribution from a high-dimension manifold.

Contrastive Learning Point Cloud Classification

Adversarial Open Domain Adaptation for Sketch-to-Photo Synthesis

2 code implementations12 Apr 2021 Xiaoyu Xiang, Ding Liu, Xiao Yang, Yiheng Zhu, Xiaohui Shen, Jan P. Allebach

In this paper, we explore open-domain sketch-to-photo translation, which aims to synthesize a realistic photo from a freehand sketch with its class label, even if the sketches of that class are missing in the training data.

Domain Adaptation Image-to-Image Translation +1

Unsupervised Part Segmentation through Disentangling Appearance and Shape

no code implementations CVPR 2021 Shilong Liu, Lei Zhang, Xiao Yang, Hang Su, Jun Zhu

We study the problem of unsupervised discovery and segmentation of object parts, which, as an intermediate local representation, are capable of finding intrinsic object structure and providing more explainable recognition results.

Disentanglement Object +3

Exploring Memorization in Adversarial Training

1 code implementation ICLR 2022 Yinpeng Dong, Ke Xu, Xiao Yang, Tianyu Pang, Zhijie Deng, Hang Su, Jun Zhu

In this paper, we explore the memorization effect in adversarial training (AT) for promoting a deeper understanding of model capacity, convergence, generalization, and especially robust overfitting of the adversarially trained models.

Memorization

Accumulative Poisoning Attacks on Real-time Data

1 code implementation NeurIPS 2021 Tianyu Pang, Xiao Yang, Yinpeng Dong, Hang Su, Jun Zhu

Collecting training data from untrusted sources exposes machine learning services to poisoning adversaries, who maliciously manipulate training data to degrade the model accuracy.

Federated Learning

Semantic StyleGAN

no code implementations arXiv:2112.02236v2 [cs.CV] 7 Dec 2021 2021 Researchers at ByteDance Inc, Yichun Shi, Xiao Yang, Yangyue Wan, Xiaohui Shen

SemanticStyleGAN presents a method where a generator is trained to model local semantic parts separately and synthesizes images in a compositional way.

Disentanglement

Query2Label: A Simple Transformer Way to Multi-Label Classification

2 code implementations22 Jul 2021 Shilong Liu, Lei Zhang, Xiao Yang, Hang Su, Jun Zhu

The use of Transformer is rooted in the need of extracting local discriminative features adaptively for different labels, which is a strongly desired property due to the existence of multiple objects in one image.

Classification Multi-Label Classification

PIVQGAN: Posture and Identity Disentangled Image-to-Image Translation via Vector Quantization

no code implementations29 Sep 2021 Bingchen Liu, Yizhe Zhu, Xiao Yang, Ahmed Elgammal

The VQSN module facilitates a more delicate separation of posture and identity, while the training scheme ensures the VQSN module learns the pose-related representations.

Disentanglement Image-to-Image Translation +2

Adversarial Semantic Contour for Object Detection

no code implementations ICML Workshop AML 2021 Yichi Zhang, Zijian Zhu, Xiao Yang, Jun Zhu

To address this issue, we propose a novel method of Adversarial Semantic Contour (ASC) guided by object contour as prior.

Object object-detection +1

Model-Agnostic Meta-Attack: Towards Reliable Evaluation of Adversarial Robustness

no code implementations13 Oct 2021 Xiao Yang, Yinpeng Dong, Wenzhao Xiang, Tianyu Pang, Hang Su, Jun Zhu

The vulnerability of deep neural networks to adversarial examples has motivated an increasing number of defense strategies for promoting model robustness.

Adversarial Robustness

An Improved Reinforcement Learning Model Based on Sentiment Analysis

no code implementations19 Nov 2021 Yizhuo Li, Peng Zhou, Fangyi Li, Xiao Yang

The authors combined the deep Q network in reinforcement learning with the sentiment quantitative indicator ARBR to build a high-frequency stock trading model for the share market.

reinforcement-learning Reinforcement Learning (RL) +1

SemanticStyleGAN: Learning Compositional Generative Priors for Controllable Image Synthesis and Editing

1 code implementation CVPR 2022 Yichun Shi, Xiao Yang, Yangyue Wan, Xiaohui Shen

When combined with editing methods designed for StyleGANs, it can achieve a more fine-grained control to edit synthesized or real images.

Disentanglement Facial Editing +2

DDG-DA: Data Distribution Generation for Predictable Concept Drift Adaptation

1 code implementation11 Jan 2022 Wendi Li, Xiao Yang, Weiqing Liu, Yingce Xia, Jiang Bian

To handle concept drift, previous methods first detect when/where the concept drift happens and then adapt models to fit the distribution of the latest data.

Stock Prediction

DAB-DETR: Dynamic Anchor Boxes are Better Queries for DETR

7 code implementations ICLR 2022 Shilong Liu, Feng Li, Hao Zhang, Xiao Yang, Xianbiao Qi, Hang Su, Jun Zhu, Lei Zhang

We present in this paper a novel query formulation using dynamic anchor boxes for DETR (DEtection TRansformer) and offer a deeper understanding of the role of queries in DETR.

Object Detection

Robustness and Accuracy Could Be Reconcilable by (Proper) Definition

1 code implementation21 Feb 2022 Tianyu Pang, Min Lin, Xiao Yang, Jun Zhu, Shuicheng Yan

The trade-off between robustness and accuracy has been widely studied in the adversarial literature.

Inductive Bias

Controllable Evaluation and Generation of Physical Adversarial Patch on Face Recognition

no code implementations9 Mar 2022 Xiao Yang, Yinpeng Dong, Tianyu Pang, Zihao Xiao, Hang Su, Jun Zhu

It is therefore imperative to develop a framework that can enable a comprehensive evaluation of the vulnerability of face recognition in the physical world.

3D Face Modelling Face Recognition

A Challenging Benchmark of Anime Style Recognition

1 code implementation29 Apr 2022 Haotang Li, Shengtao Guo, Kailin Lyu, Xiao Yang, Tianchen Chen, Jianqing Zhu, Huanqiang Zeng

Given two images of different anime roles, anime style recognition (ASR) aims to learn abstract painting style to determine whether the two images are from the same work, which is an interesting but challenging problem.

Art Analysis Face Recognition +1

RGBD1K: A Large-scale Dataset and Benchmark for RGB-D Object Tracking

1 code implementation21 Aug 2022 Xue-Feng Zhu, Tianyang Xu, Zhangyong Tang, Zucheng Wu, Haodong Liu, Xiao Yang, Xiao-Jun Wu, Josef Kittler

To demonstrate the benefits of training on a larger RGB-D data set in general, and RGBD1K in particular, we develop a transformer-based RGB-D tracker, named SPT, as a baseline for future visual object tracking studies using the new dataset.

Visual Object Tracking

Shifted Diffusion for Text-to-image Generation

1 code implementation CVPR 2023 Yufan Zhou, Bingchen Liu, Yizhe Zhu, Xiao Yang, Changyou Chen, Jinhui Xu

Unlike the baseline diffusion model used in DALL-E 2, our method seamlessly encodes prior knowledge of the pre-trained CLIP model in its diffusion process by designing a new initialization distribution and a new transition step of the diffusion.

Zero-Shot Text-to-Image Generation

Detecting and measuring human gastric peristalsis using magnetically controlled capsule endoscope

no code implementations24 Jan 2023 Xueshen Li, Yu Gan, David Duan, Xiao Yang

In this paper, we develop algorithms to detect and measure human gastric peristalsis (contraction wave) using video sequences acquired by MCCE.

A Comprehensive Study on Robustness of Image Classification Models: Benchmarking and Rethinking

no code implementations28 Feb 2023 Chang Liu, Yinpeng Dong, Wenzhao Xiang, Xiao Yang, Hang Su, Jun Zhu, Yuefeng Chen, Yuan He, Hui Xue, Shibao Zheng

In our benchmark, we evaluate the robustness of 55 typical deep learning models on ImageNet with diverse architectures (e. g., CNNs, Transformers) and learning algorithms (e. g., normal supervised training, pre-training, adversarial training) under numerous adversarial attacks and out-of-distribution (OOD) datasets.

Adversarial Robustness Benchmarking +2

A Recipe for Watermarking Diffusion Models

1 code implementation17 Mar 2023 Yunqing Zhao, Tianyu Pang, Chao Du, Xiao Yang, Ngai-Man Cheung, Min Lin

Diffusion models (DMs) have demonstrated advantageous potential on generative tasks.

Towards Effective Adversarial Textured 3D Meshes on Physical Face Recognition

1 code implementation CVPR 2023 Xiao Yang, Chang Liu, Longlong Xu, Yikai Wang, Yinpeng Dong, Ning Chen, Hang Su, Jun Zhu

The goal of this work is to develop a more reliable technique that can carry out an end-to-end evaluation of adversarial robustness for commercial systems.

Adversarial Robustness Face Recognition

Common Diffusion Noise Schedules and Sample Steps are Flawed

1 code implementation15 May 2023 Shanchuan Lin, Bingchen Liu, Jiashi Li, Xiao Yang

We discover that common diffusion noise schedules do not enforce the last timestep to have zero signal-to-noise ratio (SNR), and some implementations of diffusion samplers do not start from the last timestep.

SAM for Poultry Science

no code implementations17 May 2023 Xiao Yang, Haixing Dai, Zihao Wu, Ramesh Bist, Sachin Subedi, Jin Sun, Guoyu Lu, Changying Li, Tianming Liu, Lilong Chai

This study aims to assess the zero-shot segmentation performance of SAM on representative chicken segmentation tasks, including part-based segmentation and the use of infrared thermal images, and to explore chicken-tracking tasks by using SAM as a segmentation tool.

Object Tracking Segmentation +2

Robust Classification via a Single Diffusion Model

2 code implementations24 May 2023 Huanran Chen, Yinpeng Dong, Zhengyi Wang, Xiao Yang, Chengqi Duan, Hang Su, Jun Zhu

Since our method does not require training on particular adversarial attacks, we demonstrate that it is more generalizable to defend against multiple unseen threats.

Adversarial Defense Adversarial Robustness +2

Unifying gradient regularization for Heterogeneous Graph Neural Networks

1 code implementation25 May 2023 Xiao Yang, Xuejiao Zhao, Zhiqi Shen

Grug provides a unified framework integrating graph topology and node features, based on which we conduct a detailed theoretical analysis of their effectiveness.

On Evaluating Adversarial Robustness of Large Vision-Language Models

1 code implementation NeurIPS 2023 Yunqing Zhao, Tianyu Pang, Chao Du, Xiao Yang, Chongxuan Li, Ngai-Man Cheung, Min Lin

Large vision-language models (VLMs) such as GPT-4 have achieved unprecedented performance in response generation, especially with visual inputs, enabling more creative and adaptable interaction than large language models such as ChatGPT.

Adversarial Robustness multimodal generation +1

Improving Opinion-based Question Answering Systems Through Label Error Detection and Overwrite

no code implementations13 Jun 2023 Xiao Yang, Ahmed K. Mohamed, Shashank Jain, Stanislav Peshterliev, Debojeet Chatterjee, Hanwen Zha, Nikita Bhalla, Gagan Aneja, Pranab Mohanty

Importantly, LEDO is computationally efficient compared to methods that require loss function change, and cost-effective as the resulting data can be used in the same continuous training pipeline for production.

Label Error Detection Machine Reading Comprehension +2

AdvFAS: A robust face anti-spoofing framework against adversarial examples

no code implementations4 Aug 2023 Jiawei Chen, Xiao Yang, Heng Yin, Mingzhi Ma, Bihui Chen, Jianteng Peng, Yandong Guo, Zhaoxia Yin, Hang Su

Ensuring the reliability of face recognition systems against presentation attacks necessitates the deployment of face anti-spoofing techniques.

Adversarial Defense Face Anti-Spoofing +1

Knowledge-Driven Multi-Agent Reinforcement Learning for Computation Offloading in Cybertwin-Enabled Internet of Vehicles

no code implementations4 Aug 2023 Ruijin Sun, Xiao Yang, Nan Cheng, Xiucheng Wang, Changle Li

By offloading computation-intensive tasks of vehicles to roadside units (RSUs), mobile edge computing (MEC) in the Internet of Vehicles (IoV) can relieve the onboard computation burden.

Edge-computing Multi-agent Reinforcement Learning

Root Pose Decomposition Towards Generic Non-rigid 3D Reconstruction with Monocular Videos

no code implementations ICCV 2023 Yikai Wang, Yinpeng Dong, Fuchun Sun, Xiao Yang

The key idea of our method, Root Pose Decomposition (RPD), is to maintain a per-frame root pose transformation, meanwhile building a dense field with local transformations to rectify the root pose.

3D Reconstruction Object

MVDream: Multi-view Diffusion for 3D Generation

2 code implementations31 Aug 2023 Yichun Shi, Peng Wang, Jianglong Ye, Mai Long, Kejie Li, Xiao Yang

We introduce MVDream, a diffusion model that is able to generate consistent multi-view images from a given text prompt.

How Robust is Google's Bard to Adversarial Image Attacks?

1 code implementation21 Sep 2023 Yinpeng Dong, Huanran Chen, Jiawei Chen, Zhengwei Fang, Xiao Yang, Yichi Zhang, Yu Tian, Hang Su, Jun Zhu

By attacking white-box surrogate vision encoders or MLLMs, the generated adversarial examples can mislead Bard to output wrong image descriptions with a 22% success rate based solely on the transferability.

Adversarial Robustness Chatbot +1

Leveraging Large Language Model for Automatic Evolving of Industrial Data-Centric R&D Cycle

no code implementations17 Oct 2023 Xu Yang, Xiao Yang, Weiqing Liu, Jinhui Li, Peng Yu, Zeqi Ye, Jiang Bian

In the wake of relentless digital transformation, data-driven solutions are emerging as powerful tools to address multifarious industrial tasks such as forecasting, anomaly detection, planning, and even complex decision-making.

Anomaly Detection Decision Making +2

Evil Geniuses: Delving into the Safety of LLM-based Agents

1 code implementation20 Nov 2023 Yu Tian, Xiao Yang, Jingyuan Zhang, Yinpeng Dong, Hang Su

Rapid advancements in large language models (LLMs) have revitalized in LLM-based agents, exhibiting impressive human-like behaviors and cooperative capabilities in various scenarios.

Specificity

YOLO-OB: An improved anchor-free real-time multiscale colon polyp detector in colonoscopy

1 code implementation14 Dec 2023 Xiao Yang, Enmin Song, Guangzhi Ma, Yunfeng Zhu, Dongming Yu, Bowen Ding, Xianyuan Wang

These problems reduce the performance of polyp detection and also lower the model's training and detection efficiency.

Diffusion Model with Perceptual Loss

no code implementations30 Dec 2023 Shanchuan Lin, Xiao Yang

In this paper, we show that the effectiveness of classifier-free guidance partly originates from it being a form of implicit perceptual guidance.

Denoising

SDXL-Lightning: Progressive Adversarial Diffusion Distillation

no code implementations21 Feb 2024 Shanchuan Lin, Anran Wang, Xiao Yang

We propose a diffusion distillation method that achieves new state-of-the-art in one-step/few-step 1024px text-to-image generation based on SDXL.

Text-to-Image Generation

BSPA: Exploring Black-box Stealthy Prompt Attacks against Image Generators

no code implementations23 Feb 2024 Yu Tian, Xiao Yang, Yinpeng Dong, Heming Yang, Hang Su, Jun Zhu

It allows users to design specific prompts to generate realistic images through some black-box APIs.

GuardT2I: Defending Text-to-Image Models from Adversarial Prompts

no code implementations3 Mar 2024 Yijun Yang, Ruiyuan Gao, Xiao Yang, Jianyuan Zhong, Qiang Xu

Recent advancements in Text-to-Image (T2I) models have raised significant safety concerns about their potential misuse for generating inappropriate or Not-Safe-For-Work (NSFW) contents, despite existing countermeasures such as NSFW classifiers or model fine-tuning for inappropriate concept removal.

Binary Classification Language Modelling +1

AnimateDiff-Lightning: Cross-Model Diffusion Distillation

no code implementations19 Mar 2024 Shanchuan Lin, Xiao Yang

We present AnimateDiff-Lightning for lightning-fast video generation.

Video Generation

一种非结构化数据表征增强的术后风险预测模型(An Unstructured Data Representation Enhanced Model for Postoperative Risk Prediction)

no code implementations CCL 2022 Yaqiang Wang, Xiao Yang, Xuechao Hao, Hongping Shu, Guo Chen, Tao Zhu

“准确的术后风险预测对临床资源规划和应急方案准备以及降低患者的术后风险和死亡率具有积极作用。术后风险预测目前主要基于术前和术中的患者基本信息、实验室检查、生命体征等结构化数据, 而蕴含丰富语义信息的非结构化术前诊断的价值还有待验证。针对该问题, 本文提出一种非结构化数据表征增强的术后风险预测模型, 利用自注意力机制, 精巧的将结构化数据与术前诊断数据进行信息加权融合。基于临床数据, 将本文方法与术后风险预测常用的统计机器学习模型以及最新的深度神经网络进行对比, 本文方法不仅提升了术后风险预测的性能, 同时也为预测模型带来了良好的可解释性。”

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