Search Results for author: Nenghai Yu

Found 77 papers, 24 papers with code

Invertible Mask Network for Face Privacy-Preserving

no code implementations19 Apr 2022 Yang Yang, Yiyang Huang, Ming Shi, Kejiang Chen, Weiming Zhang, Nenghai Yu

Then, put the "Mask" face onto the protected face and generate the masked face, in which the masked face is indistinguishable from "Mask" face.

Shape-invariant 3D Adversarial Point Clouds

1 code implementation8 Mar 2022 Qidong Huang, Xiaoyi Dong, Dongdong Chen, Hang Zhou, Weiming Zhang, Nenghai Yu

In this paper, we propose a novel Point-Cloud Sensitivity Map to boost both the efficiency and imperceptibility of point perturbations.

Protecting Celebrities from DeepFake with Identity Consistency Transformer

1 code implementation2 Mar 2022 Xiaoyi Dong, Jianmin Bao, Dongdong Chen, Ting Zhang, Weiming Zhang, Nenghai Yu, Dong Chen, Fang Wen, Baining Guo

In this work we propose Identity Consistency Transformer, a novel face forgery detection method that focuses on high-level semantics, specifically identity information, and detecting a suspect face by finding identity inconsistency in inner and outer face regions.

Face Swapping

Self-supervised Transformer for Deepfake Detection

no code implementations2 Mar 2022 Hanqing Zhao, Wenbo Zhou, Dongdong Chen, Weiming Zhang, Nenghai Yu

After pre-training with our method, the model will then be partially fine-tuned for deepfake detection task.

Contrastive Learning DeepFake Detection +3

Online Multi-Object Tracking with Unsupervised Re-Identification Learning and Occlusion Estimation

no code implementations4 Jan 2022 Qiankun Liu, Dongdong Chen, Qi Chu, Lu Yuan, Bin Liu, Lei Zhang, Nenghai Yu

In addition, such practice of re-identification still can not track those highly occluded objects when they are missed by the detector.

Ranked #6 on Multi-Object Tracking on MOT16 (using extra training data)

Multi-Object Tracking Occlusion Estimation +1

Initiative Defense against Facial Manipulation

no code implementations19 Dec 2021 Qidong Huang, Jie Zhang, Wenbo Zhou, WeimingZhang, Nenghai Yu

To this end, we first imitate the target manipulation model with a surrogate model, and then devise a poison perturbation generator to obtain the desired venom.

Face Reenactment

Tracing Text Provenance via Context-Aware Lexical Substitution

no code implementations15 Dec 2021 Xi Yang, Jie Zhang, Kejiang Chen, Weiming Zhang, Zehua Ma, Feng Wang, Nenghai Yu

Tracing text provenance can help claim the ownership of text content or identify the malicious users who distribute misleading content like machine-generated fake news.

Optical Character Recognition

HairCLIP: Design Your Hair by Text and Reference Image

1 code implementation9 Dec 2021 Tianyi Wei, Dongdong Chen, Wenbo Zhou, Jing Liao, Zhentao Tan, Lu Yuan, Weiming Zhang, Nenghai Yu

Hair editing is an interesting and challenging problem in computer vision and graphics.

Speech Pattern based Black-box Model Watermarking for Automatic Speech Recognition

no code implementations19 Oct 2021 Haozhe Chen, Weiming Zhang, Kunlin Liu, Kejiang Chen, Han Fang, Nenghai Yu

As an effective method for intellectual property (IP) protection, model watermarking technology has been applied on a wide variety of deep neural networks (DNN), including speech classification models.

Automatic Speech Recognition

Unsupervised Finetuning

no code implementations18 Oct 2021 Suichan Li, Dongdong Chen, Yinpeng Chen, Lu Yuan, Lei Zhang, Qi Chu, Bin Liu, Nenghai Yu

This problem is more challenging than the supervised counterpart, as the low data density in the small-scale target data is not friendly for unsupervised learning, leading to the damage of the pretrained representation and poor representation in the target domain.

Temporal RoI Align for Video Object Recognition

1 code implementation8 Sep 2021 Tao Gong, Kai Chen, Xinjiang Wang, Qi Chu, Feng Zhu, Dahua Lin, Nenghai Yu, Huamin Feng

In this work, considering the features of the same object instance are highly similar among frames in a video, a novel Temporal RoI Align operator is proposed to extract features from other frames feature maps for current frame proposals by utilizing feature similarity.

Frame Instance Segmentation +4

ISNet: Integrate Image-Level and Semantic-Level Context for Semantic Segmentation

1 code implementation ICCV 2021 Zhenchao Jin, Bin Liu, Qi Chu, Nenghai Yu

Third, we compute the similarities between each pixel representation and the image-level contextual information, the semantic-level contextual information, respectively.

Semantic Segmentation

Exploring Structure Consistency for Deep Model Watermarking

no code implementations5 Aug 2021 Jie Zhang, Dongdong Chen, Jing Liao, Han Fang, Zehua Ma, Weiming Zhang, Gang Hua, Nenghai Yu

However, little attention has been devoted to the protection of DNNs in image processing tasks.

Data Augmentation

Poison Ink: Robust and Invisible Backdoor Attack

no code implementations5 Aug 2021 Jie Zhang, Dongdong Chen, Jing Liao, Qidong Huang, Gang Hua, Weiming Zhang, Nenghai Yu

As the image structure can keep its semantic meaning during the data transformation, such trigger pattern is inherently robust to data transformations.

Backdoor Attack Data Poisoning

Abnormal Behavior Detection Based on Target Analysis

no code implementations29 Jul 2021 Luchuan Song, Bin Liu, Huihui Zhu, Qi Chu, Nenghai Yu

To this end, we propose a multivariate fusion method that analyzes each target through three branches: object, action and motion.

Cascaded Residual Density Network for Crowd Counting

no code implementations29 Jul 2021 Kun Zhao, Luchuan Song, Bin Liu, Qi Chu, Nenghai Yu

Crowd counting is a challenging task due to the issues such as scale variation and perspective variation in real crowd scenes.

Crowd Counting

Improve Unsupervised Pretraining for Few-label Transfer

no code implementations ICCV 2021 Suichan Li, Dongdong Chen, Yinpeng Chen, Lu Yuan, Lei Zhang, Qi Chu, Bin Liu, Nenghai Yu

Unsupervised pretraining has achieved great success and many recent works have shown unsupervised pretraining can achieve comparable or even slightly better transfer performance than supervised pretraining on downstream target datasets.

Contrastive Learning

CSWin Transformer: A General Vision Transformer Backbone with Cross-Shaped Windows

4 code implementations1 Jul 2021 Xiaoyi Dong, Jianmin Bao, Dongdong Chen, Weiming Zhang, Nenghai Yu, Lu Yuan, Dong Chen, Baining Guo

By further pretraining on the larger dataset ImageNet-21K, we achieve 87. 5% Top-1 accuracy on ImageNet-1K and high segmentation performance on ADE20K with 55. 7 mIoU.

Image Classification Semantic Segmentation

E2Style: Improve the Efficiency and Effectiveness of StyleGAN Inversion

2 code implementations15 Apr 2021 Tianyi Wei, Dongdong Chen, Wenbo Zhou, Jing Liao, Weiming Zhang, Lu Yuan, Gang Hua, Nenghai Yu

This paper studies the problem of StyleGAN inversion, which plays an essential role in enabling the pretrained StyleGAN to be used for real image editing tasks.

Face Parsing

Reversible Watermarking in Deep Convolutional Neural Networks for Integrity Authentication

no code implementations9 Apr 2021 Xiquan Guan, Huamin Feng, Weiming Zhang, Hang Zhou, Jie Zhang, Nenghai Yu

Specifically, we present the reversible watermarking problem of deep convolutional neural networks and utilize the pruning theory of model compression technology to construct a host sequence used for embedding watermarking information by histogram shift.

Model Compression

Towards Generalizable and Robust Face Manipulation Detection via Bag-of-local-feature

no code implementations14 Mar 2021 Changtao Miao, Qi Chu, Weihai Li, Tao Gong, Wanyi Zhuang, Nenghai Yu

Over the past several years, in order to solve the problem of malicious abuse of facial manipulation technology, face manipulation detection technology has obtained considerable attention and achieved remarkable progress.

Diverse Semantic Image Synthesis via Probability Distribution Modeling

1 code implementation CVPR 2021 Zhentao Tan, Menglei Chai, Dongdong Chen, Jing Liao, Qi Chu, Bin Liu, Gang Hua, Nenghai Yu

In this paper, we propose a novel diverse semantic image synthesis framework from the perspective of semantic class distributions, which naturally supports diverse generation at semantic or even instance level.

Image-to-Image Translation

Deep Model Intellectual Property Protection via Deep Watermarking

1 code implementation8 Mar 2021 Jie Zhang, Dongdong Chen, Jing Liao, Weiming Zhang, Huamin Feng, Gang Hua, Nenghai Yu

By jointly training the target model and watermark embedding, the extra barrier can even be absorbed into the target model.

Multi-attentional Deepfake Detection

no code implementations CVPR 2021 Hanqing Zhao, Wenbo Zhou, Dongdong Chen, Tianyi Wei, Weiming Zhang, Nenghai Yu

Most of them model deepfake detection as a vanilla binary classification problem, i. e, first use a backbone network to extract a global feature and then feed it into a binary classifier (real/fake).

Data Augmentation DeepFake Detection +1

Adversarial Examples Detection beyond Image Space

1 code implementation23 Feb 2021 Kejiang Chen, Yuefeng Chen, Hang Zhou, Chuan Qin, Xiaofeng Mao, Weiming Zhang, Nenghai Yu

To detect both few-perturbation attacks and large-perturbation attacks, we propose a method beyond image space by a two-stream architecture, in which the image stream focuses on the pixel artifacts and the gradient stream copes with the confidence artifacts.

Return-Based Contrastive Representation Learning for Reinforcement Learning

no code implementations ICLR 2021 Guoqing Liu, Chuheng Zhang, Li Zhao, Tao Qin, Jinhua Zhu, Jian Li, Nenghai Yu, Tie-Yan Liu

Recently, various auxiliary tasks have been proposed to accelerate representation learning and improve sample efficiency in deep reinforcement learning (RL).

Atari Games reinforcement-learning +1

Are Fewer Labels Possible for Few-shot Learning?

no code implementations10 Dec 2020 Suichan Li, Dongdong Chen, Yinpeng Chen, Lu Yuan, Lei Zhang, Qi Chu, Nenghai Yu

We conduct experiments on 10 different few-shot target datasets, and our average few-shot performance outperforms both vanilla inductive unsupervised transfer and supervised transfer by a large margin.

Few-Shot Learning

Efficient Semantic Image Synthesis via Class-Adaptive Normalization

1 code implementation8 Dec 2020 Zhentao Tan, Dongdong Chen, Qi Chu, Menglei Chai, Jing Liao, Mingming He, Lu Yuan, Gang Hua, Nenghai Yu

Spatially-adaptive normalization (SPADE) is remarkably successful recently in conditional semantic image synthesis \cite{park2019semantic}, which modulates the normalized activation with spatially-varying transformations learned from semantic layouts, to prevent the semantic information from being washed away.

Image Generation

Identity-Driven DeepFake Detection

no code implementations7 Dec 2020 Xiaoyi Dong, Jianmin Bao, Dongdong Chen, Weiming Zhang, Nenghai Yu, Dong Chen, Fang Wen, Baining Guo

Our approach takes as input the suspect image/video as well as the target identity information (a reference image or video).

DeepFake Detection Face Swapping

LG-GAN: Label Guided Adversarial Network for Flexible Targeted Attack of Point Cloud-based Deep Networks

no code implementations1 Nov 2020 Hang Zhou, Dongdong Chen, Jing Liao, Weiming Zhang, Kejiang Chen, Xiaoyi Dong, Kunlin Liu, Gang Hua, Nenghai Yu

To overcome these shortcomings, this paper proposes a novel label guided adversarial network (LG-GAN) for real-time flexible targeted point cloud attack.

MichiGAN: Multi-Input-Conditioned Hair Image Generation for Portrait Editing

1 code implementation30 Oct 2020 Zhentao Tan, Menglei Chai, Dongdong Chen, Jing Liao, Qi Chu, Lu Yuan, Sergey Tulyakov, Nenghai Yu

In this paper, we present MichiGAN (Multi-Input-Conditioned Hair Image GAN), a novel conditional image generation method for interactive portrait hair manipulation.

Conditional Image Generation

Passport-aware Normalization for Deep Model Protection

1 code implementation NeurIPS 2020 Jie Zhang, Dongdong Chen, Jing Liao, Weiming Zhang, Gang Hua, Nenghai Yu

Only when the model IP is suspected to be stolen by someone, the private passport-aware branch is added back for ownership verification.

Model Compression

GreedyFool: Distortion-Aware Sparse Adversarial Attack

1 code implementation NeurIPS 2020 Xiaoyi Dong, Dongdong Chen, Jianmin Bao, Chuan Qin, Lu Yuan, Weiming Zhang, Nenghai Yu, Dong Chen

Sparse adversarial samples are a special branch of adversarial samples that can fool the target model by only perturbing a few pixels.

Adversarial Attack

Rethinking Spatially-Adaptive Normalization

no code implementations6 Apr 2020 Zhentao Tan, Dongdong Chen, Qi Chu, Menglei Chai, Jing Liao, Mingming He, Lu Yuan, Nenghai Yu

Despite its impressive performance, a more thorough understanding of the true advantages inside the box is still highly demanded, to help reduce the significant computation and parameter overheads introduced by these new structures.

Image Generation

Density-Aware Graph for Deep Semi-Supervised Visual Recognition

no code implementations CVPR 2020 Suichan Li, Bin Liu, Dong-Dong Chen, Qi Chu, Lu Yuan, Nenghai Yu

Motivated by these limitations, this paper proposes to solve the SSL problem by building a novel density-aware graph, based on which the neighborhood information can be easily leveraged and the feature learning and label propagation can also be trained in an end-to-end way.

Cross-modality Person re-identification with Shared-Specific Feature Transfer

no code implementations CVPR 2020 Yan Lu, Yue Wu, Bin Liu, Tianzhu Zhang, Baopu Li, Qi Chu, Nenghai Yu

In this paper, we tackle the above limitation by proposing a novel cross-modality shared-specific feature transfer algorithm (termed cm-SSFT) to explore the potential of both the modality-shared information and the modality-specific characteristics to boost the re-identification performance.

Cross-Modality Person Re-identification Person Re-Identification

Model Watermarking for Image Processing Networks

1 code implementation25 Feb 2020 Jie Zhang, Dong-Dong Chen, Jing Liao, Han Fang, Weiming Zhang, Wenbo Zhou, HAO CUI, Nenghai Yu

In this way, when the attacker trains one surrogate model by using the input-output pairs of the target model, the hidden watermark will be learned and extracted afterward.

Self-supervised Adversarial Training

1 code implementation15 Nov 2019 Kejiang Chen, Hang Zhou, Yuefeng Chen, Xiaofeng Mao, Yuhong Li, Yuan He, Hui Xue, Weiming Zhang, Nenghai Yu

Recent work has demonstrated that neural networks are vulnerable to adversarial examples.

Self-Supervised Learning

Demonstration Actor Critic

no code implementations25 Sep 2019 Guoqing Liu, Li Zhao, Pushi Zhang, Jiang Bian, Tao Qin, Nenghai Yu, Tie-Yan Liu

One approach leverages demonstration data in a supervised manner, which is simple and direct, but can only provide supervision signal over those states seen in the demonstrations.

Once a MAN: Towards Multi-Target Attack via Learning Multi-Target Adversarial Network Once

no code implementations ICCV 2019 Jiangfan Han, Xiaoyi Dong, Ruimao Zhang, Dong-Dong Chen, Weiming Zhang, Nenghai Yu, Ping Luo, Xiaogang Wang

Recently, generation-based methods have received much attention since they directly use feed-forward networks to generate the adversarial samples, which avoid the time-consuming iterative attacking procedure in optimization-based and gradient-based methods.

Classification General Classification

A General Decoupled Learning Framework for Parameterized Image Operators

no code implementations11 Jul 2019 Qingnan Fan, Dong-Dong Chen, Lu Yuan, Gang Hua, Nenghai Yu, Baoquan Chen

To overcome this limitation, we propose a new decoupled learning algorithm to learn from the operator parameters to dynamically adjust the weights of a deep network for image operators, denoted as the base network.

A Large Scale Urban Surveillance Video Dataset for Multiple-Object Tracking and Behavior Analysis

no code implementations26 Apr 2019 Guojun Yin, Bin Liu, Huihui Zhu, Tao Gong, Nenghai Yu

Multiple-object tracking and behavior analysis have been the essential parts of surveillance video analysis for public security and urban management.

Multiple Object Tracking

Context and Attribute Grounded Dense Captioning

no code implementations CVPR 2019 Guojun Yin, Lu Sheng, Bin Liu, Nenghai Yu, Xiaogang Wang, Jing Shao

Dense captioning aims at simultaneously localizing semantic regions and describing these regions-of-interest (ROIs) with short phrases or sentences in natural language.

DUP-Net: Denoiser and Upsampler Network for 3D Adversarial Point Clouds Defense

1 code implementation ICCV 2019 Hang Zhou, Kejiang Chen, Weiming Zhang, Han Fang, Wenbo Zhou, Nenghai Yu

We propose a Denoiser and UPsampler Network (DUP-Net) structure as defenses for 3D adversarial point cloud classification, where the two modules reconstruct surface smoothness by dropping or adding points.

Denoising Point Cloud Classification

Real-Time Anomaly Detection With HMOF Feature

no code implementations12 Dec 2018 Huihui Zhu, Bin Liu, Guojun Yin, Yan Lu, Weihai Li, Nenghai Yu

Most existing methods are computation consuming, which cannot satisfy the real-time requirement.

Anomaly Detection Optical Flow Estimation

CAAD 2018: Iterative Ensemble Adversarial Attack

no code implementations7 Nov 2018 Jiayang Liu, Weiming Zhang, Nenghai Yu

Deep Neural Networks (DNNs) have recently led to significant improvements in many fields.

Adversarial Attack

Emerging Applications of Reversible Data Hiding

no code implementations7 Nov 2018 Dongdong Hou, Weiming Zhang, Jiayang Liu, Siyan Zhou, Dong-Dong Chen, Nenghai Yu

Reversible data hiding (RDH) is one special type of information hiding, by which the host sequence as well as the embedded data can be both restored from the marked sequence without loss.

CAAD 2018: Powerful None-Access Black-Box Attack Based on Adversarial Transformation Network

no code implementations3 Nov 2018 Xiaoyi Dong, Weiming Zhang, Nenghai Yu

In this paper, we propose an improvement of Adversarial Transformation Networks(ATN) to generate adversarial examples, which can fool white-box models and black-box models with a state of the art performance and won the 2rd place in the non-target task in CAAD 2018.

Capacity Control of ReLU Neural Networks by Basis-path Norm

no code implementations19 Sep 2018 Shuxin Zheng, Qi Meng, Huishuai Zhang, Wei Chen, Nenghai Yu, Tie-Yan Liu

Motivated by this, we propose a new norm \emph{Basis-path Norm} based on a group of linearly independent paths to measure the capacity of neural networks more accurately.

Decouple Learning for Parameterized Image Operators

1 code implementation ECCV 2018 Qingnan Fan, Dong-Dong Chen, Lu Yuan, Gang Hua, Nenghai Yu, Baoquan Chen

Many different deep networks have been used to approximate, accelerate or improve traditional image operators, such as image smoothing, super-resolution and denoising.

Denoising image smoothing +1

Zoom-Net: Mining Deep Feature Interactions for Visual Relationship Recognition

no code implementations ECCV 2018 Guojun Yin, Lu Sheng, Bin Liu, Nenghai Yu, Xiaogang Wang, Jing Shao, Chen Change Loy

We show that by encouraging deep message propagation and interactions between local object features and global predicate features, one can achieve compelling performance in recognizing complex relationships without using any linguistic priors.

Model-Level Dual Learning

no code implementations ICML 2018 Yingce Xia, Xu Tan, Fei Tian, Tao Qin, Nenghai Yu, Tie-Yan Liu

Many artificial intelligence tasks appear in dual forms like English$\leftrightarrow$French translation and speech$\leftrightarrow$text transformation.

Machine Translation Sentiment Analysis +1

Detection based Defense against Adversarial Examples from the Steganalysis Point of View

no code implementations CVPR 2019 Jiayang Liu, Weiming Zhang, Yiwei Zhang, Dongdong Hou, Yujia Liu, Hongyue Zha, Nenghai Yu

Moreover, secondary adversarial attacks cannot be directly performed to our method because our method is not based on a neural network but based on high-dimensional artificial features and FLD (Fisher Linear Discriminant) ensemble.

Stereoscopic Neural Style Transfer

no code implementations CVPR 2018 Dongdong Chen, Lu Yuan, Jing Liao, Nenghai Yu, Gang Hua

This paper presents the first attempt at stereoscopic neural style transfer, which responds to the emerging demand for 3D movies or AR/VR.

Style Transfer

Deliberation Networks: Sequence Generation Beyond One-Pass Decoding

no code implementations NeurIPS 2017 Yingce Xia, Fei Tian, Lijun Wu, Jianxin Lin, Tao Qin, Nenghai Yu, Tie-Yan Liu

In this work, we introduce the deliberation process into the encoder-decoder framework and propose deliberation networks for sequence generation.

Image Captioning Machine Translation +2

Enhanced Attacks on Defensively Distilled Deep Neural Networks

no code implementations16 Nov 2017 Yujia Liu, Weiming Zhang, Shaohua Li, Nenghai Yu

In this paper, we first propose the epsilon-neighborhood attack, which can fool the defensively distilled networks with 100% success rate in the white-box setting, and it is fast to generate adversarial examples with good visual quality.

Face Recognition General Classification +2

Dual Supervised Learning

1 code implementation ICML 2017 Yingce Xia, Tao Qin, Wei Chen, Jiang Bian, Nenghai Yu, Tie-Yan Liu

Many supervised learning tasks are emerged in dual forms, e. g., English-to-French translation vs. French-to-English translation, speech recognition vs. text to speech, and image classification vs. image generation.

General Classification Image Classification +5

Coherent Online Video Style Transfer

no code implementations ICCV 2017 Dongdong Chen, Jing Liao, Lu Yuan, Nenghai Yu, Gang Hua

Training a feed-forward network for fast neural style transfer of images is proven to be successful.

Frame Image Stylization +1

StyleBank: An Explicit Representation for Neural Image Style Transfer

1 code implementation CVPR 2017 Dongdong Chen, Lu Yuan, Jing Liao, Nenghai Yu, Gang Hua

It also enables us to conduct incremental learning to add a new image style by learning a new filter bank while holding the auto-encoder fixed.

Incremental Learning Style Transfer

Learning Spatial Regularization with Image-level Supervisions for Multi-label Image Classification

2 code implementations CVPR 2017 Feng Zhu, Hongsheng Li, Wanli Ouyang, Nenghai Yu, Xiaogang Wang

Analysis of the learned SRN model demonstrates that it can effectively capture both semantic and spatial relations of labels for improving classification performance.

Classification General Classification +2

Dual Learning for Machine Translation

1 code implementation NeurIPS 2016 Yingce Xia, Di He, Tao Qin, Li-Wei Wang, Nenghai Yu, Tie-Yan Liu, Wei-Ying Ma

Based on the feedback signals generated during this process (e. g., the language-model likelihood of the output of a model, and the reconstruction error of the original sentence after the primal and dual translations), we can iteratively update the two models until convergence (e. g., using the policy gradient methods).

Language Modelling Machine Translation +2

SOL: A Library for Scalable Online Learning Algorithms

1 code implementation28 Oct 2016 Yue Wu, Steven C. H. Hoi, Chenghao Liu, Jing Lu, Doyen Sahoo, Nenghai Yu

SOL is an open-source library for scalable online learning algorithms, and is particularly suitable for learning with high-dimensional data.

General Classification Multi-class Classification +1

Asynchronous Stochastic Gradient Descent with Delay Compensation

no code implementations ICML 2017 Shuxin Zheng, Qi Meng, Taifeng Wang, Wei Chen, Nenghai Yu, Zhi-Ming Ma, Tie-Yan Liu

We propose a novel technology to compensate this delay, so as to make the optimization behavior of ASGD closer to that of sequential SGD.

Graph Construction with Label Information for Semi-Supervised Learning

no code implementations8 Jul 2016 Liansheng Zhuang, Zihan Zhou, Jingwen Yin, Shenghua Gao, Zhouchen Lin, Yi Ma, Nenghai Yu

In the literature, most existing graph-based semi-supervised learning (SSL) methods only use the label information of observed samples in the label propagation stage, while ignoring such valuable information when learning the graph.

graph construction Graph Learning

Thompson Sampling for Budgeted Multi-armed Bandits

no code implementations1 May 2015 Yingce Xia, Haifang Li, Tao Qin, Nenghai Yu, Tie-Yan Liu

In this paper, we extend the Thompson sampling to Budgeted MAB, where there is random cost for pulling an arm and the total cost is constrained by a budget.

Multi-Armed Bandits

Large-scale Online Feature Selection for Ultra-high Dimensional Sparse Data

no code implementations27 Sep 2014 Yue Wu, Steven C. H. Hoi, Tao Mei, Nenghai Yu

However, unlike many second-order learning methods that often suffer from extra high computational cost, we devise a novel smart algorithm for second-order online feature selection using a MaxHeap-based approach, which is not only more effective than the existing first-order approaches, but also significantly more efficient and scalable for large-scale feature selection with ultra-high dimensional sparse data, as validated from our extensive experiments.

Learning Bregman Distance Functions and Its Application for Semi-Supervised Clustering

no code implementations NeurIPS 2009 Lei Wu, Rong Jin, Steven C. Hoi, Jianke Zhu, Nenghai Yu

Learning distance functions with side information plays a key role in many machine learning and data mining applications.

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