Search Results for author: Hao Yang

Found 127 papers, 32 papers with code

HwTscSU’s Submissions on WAT 2022 Shared Task

no code implementations WAT 2022 Yilun Liu, Zhen Zhang, Shimin Tao, Junhui Li, Hao Yang

In this paper we describe our submission to the shared tasks of the 9th Workshop on Asian Translation (WAT 2022) on NICT–SAP under the team name ”HwTscSU”.

Domain Adaptation NMT +1

数字人文视角下的《史记》《汉书》比较研究(A Comparative Study of Shiji and Hanshu from the Perspective of Digital Humanities)

no code implementations CCL 2022 Zekun Deng, Hao Yang, Jun Wang

"《史记》和《汉书》具有经久不衰的研究价值。尽管两书异同的研究已经较为丰富, 但研究的全面性、完备性、科学性、客观性均仍显不足。在数字人文的视角下, 本文利用计算语言学方法, 通过对字、词、命名实体、段落等的多粒度、多角度分析, 开展对于《史》《汉》的比较研究。首先, 本文对于《史》《汉》中的字、词、命名实体的分布和特点进行对比, 以遍历穷举的考察方式提炼出两书在主要内容上的相同点与不同点, 揭示了汉武帝之前和汉武帝到西汉灭亡两段历史时期在政治、文化、思想上的重要变革与承袭。其次, 本文使用一种融入命名实体作为外部特征的文本相似度算法对于《史记》《汉书》的异文进行自动发现, 成功识别出过去研究者通过人工手段没有发现的袭用段落, 使得我们对于《史》《汉》的承袭关系形成更加完整和立体的认识。再次, 本文通过计算异文段落之间的最长公共子序列来自动得出两段异文之间存在的差异, 从宏观统计上证明了《汉书》文字风格《史记》的差别, 并从微观上进一步对二者语言特点进行了阐释, 为理解《史》《汉》异文特点提供了新的角度和启发。本研究站在数字人文的视域下, 利用先进的计算方法对于传世千年的中国古代经典进行了再审视、再发现, 其方法对于今人研究古籍有一定的借鉴价值。”

Efficient Transfer Learning for Quality Estimation with Bottleneck Adapter Layer

no code implementations EAMT 2020 Hao Yang, Minghan Wang, Ning Xie, Ying Qin, Yao Deng

Compared with the commonly used NuQE baseline, BAL-QE achieves 47% (En-Ru) and 75% (En-De) of performance promotions.

NMT Transfer Learning

Make the Blind Translator See The World: A Novel Transfer Learning Solution for Multimodal Machine Translation

no code implementations MTSummit 2021 Minghan Wang, Jiaxin Guo, Yimeng Chen, Chang Su, Min Zhang, Shimin Tao, Hao Yang

Based on large-scale pretrained networks and the liability to be easily overfitting with limited labelled training data of multimodal translation (MMT) is a critical issue in MMT.

Multimodal Machine Translation NMT +2

HI-CMLM: Improve CMLM with Hybrid Decoder Input

no code implementations INLG (ACL) 2021 Minghan Wang, Guo Jiaxin, Yuxia Wang, Yimeng Chen, Su Chang, Daimeng Wei, Min Zhang, Shimin Tao, Hao Yang

Mask-predict CMLM (Ghazvininejad et al., 2019) has achieved stunning performance among non-autoregressive NMT models, but we find that the mechanism of predicting all of the target words only depending on the hidden state of [MASK] is not effective and efficient in initial iterations of refinement, resulting in ungrammatical repetitions and slow convergence.

NMT Translation

HW-TSC’s Submissions to the WMT21 Biomedical Translation Task

no code implementations WMT (EMNLP) 2021 Hao Yang, Zhanglin Wu, Zhengzhe Yu, Xiaoyu Chen, Daimeng Wei, Zongyao Li, Hengchao Shang, Minghan Wang, Jiaxin Guo, Lizhi Lei, Chuanfei Xu, Min Zhang, Ying Qin

This paper describes the submission of Huawei Translation Service Center (HW-TSC) to WMT21 biomedical translation task in two language pairs: Chinese↔English and German↔English (Our registered team name is HuaweiTSC).


Text Style Transfer Back-Translation

1 code implementation2 Jun 2023 Daimeng Wei, Zhanglin Wu, Hengchao Shang, Zongyao Li, Minghan Wang, Jiaxin Guo, Xiaoyu Chen, Zhengzhe Yu, Hao Yang

To address this issue, we propose Text Style Transfer Back Translation (TST BT), which uses a style transfer model to modify the source side of BT data.

Data Augmentation Domain Adaptation +4

Investigating Pre-trained Audio Encoders in the Low-Resource Condition

no code implementations28 May 2023 Hao Yang, Jinming Zhao, Gholamreza Haffari, Ehsan Shareghi

Pre-trained speech encoders have been central to pushing state-of-the-art results across various speech understanding and generation tasks.

Integrating Action Knowledge and LLMs for Task Planning and Situation Handling in Open Worlds

no code implementations27 May 2023 Yan Ding, Xiaohan Zhang, Saeid Amiri, Nieqing Cao, Hao Yang, Andy Kaminski, Chad Esselink, Shiqi Zhang

Each situation corresponds to a state instance wherein a robot is potentially unable to complete a task using a solution that normally works.

UNIMO-3: Multi-granularity Interaction for Vision-Language Representation Learning

no code implementations23 May 2023 Hao Yang, Can Gao, Hao Líu, Xinyan Xiao, Yanyan Zhao, Bing Qin

The experimental results show that our model achieves state-of-the-art performance in various downstream tasks, and through ablation study can prove that effective cross-layer learning improves the model's ability of multimodal representation.

Representation Learning

Imbalanced Aircraft Data Anomaly Detection

no code implementations17 May 2023 Hao Yang, Junyu Gao, Yuan Yuan, Xuelong Li

Anomaly detection in temporal data from sensors under aviation scenarios is a practical but challenging task: 1) long temporal data is difficult to extract contextual information with temporal correlation; 2) the anomalous data are rare in time series, causing normal/abnormal imbalance in anomaly detection, making the detector classification degenerate or even fail.

Anomaly Detection

Musketeer (All for One, and One for All): A Generalist Vision-Language Model with Task Explanation Prompts

no code implementations11 May 2023 Zhaoyang Zhang, Yantao Shen, Kunyu Shi, Zhaowei Cai, Jun Fang, Siqi Deng, Hao Yang, Davide Modolo, Zhuowen Tu, Stefano Soatto

We present a sequence-to-sequence vision-language model whose parameters are jointly trained on all tasks (all for one) and fully shared among multiple tasks (one for all), resulting in a single model which we named Musketeer.

Language Modelling

Context-aware Domain Adaptation for Time Series Anomaly Detection

no code implementations15 Apr 2023 Kwei-Herng Lai, Lan Wang, Huiyuan Chen, Kaixiong Zhou, Fei Wang, Hao Yang, Xia Hu

We formulate context sampling into the Markov decision process and exploit deep reinforcement learning to optimize the time series domain adaptation process via context sampling and design a tailored reward function to generate domain-invariant features that better align two domains for anomaly detection.

Anomaly Detection Domain Adaptation +2

Few-shot Class-incremental Learning for Cross-domain Disease Classification

no code implementations12 Apr 2023 Hao Yang, Weijian Huang, Jiarun Liu, Cheng Li, Shanshan Wang

The ability to incrementally learn new classes from limited samples is crucial to the development of artificial intelligence systems for real clinical application.

class-incremental learning Cross-Domain Few-Shot +3

InterFormer: Real-time Interactive Image Segmentation

1 code implementation6 Apr 2023 You Huang, Hao Yang, Ke Sun, Shengchuan Zhang, Guannan Jiang, Rongrong Ji, Liujuan Cao

Second, the model has to repeatedly process the image, the annotator's current click, and the model's feedback of the annotator's former clicks at each step of interaction, resulting in redundant computations.

Image Segmentation Interactive Segmentation +1

ContraNeRF: Generalizable Neural Radiance Fields for Synthetic-to-real Novel View Synthesis via Contrastive Learning

no code implementations CVPR 2023 Hao Yang, Lanqing Hong, Aoxue Li, Tianyang Hu, Zhenguo Li, Gim Hee Lee, LiWei Wang

In this work, we first investigate the effects of synthetic data in synthetic-to-real novel view synthesis and surprisingly observe that models trained with synthetic data tend to produce sharper but less accurate volume densities.

Contrastive Learning Generalizable Novel View Synthesis +2

MGA: Medical generalist agent through text-guided knowledge transformation

no code implementations15 Mar 2023 Weijian Huang, Hao Yang, Cheng Li, Mingtong Dai, Rui Yang, Shanshan Wang

To this end, we propose a novel medical generalist agent, MGA, that can address three kinds of common clinical tasks via clinical reports knowledge transformation.

Clinical Knowledge Inductive Bias

Introspective Cross-Attention Probing for Lightweight Transfer of Pre-trained Models

no code implementations7 Mar 2023 Yonatan Dukler, Alessandro Achille, Hao Yang, Varsha Vivek, Luca Zancato, Ben Bowman, Avinash Ravichandran, Charless Fowlkes, Ashwin Swaminathan, Stefano Soatto

We show that, even when selecting a single top-scoring adapter, InCA achieves performance comparable to full fine-tuning, at a cost comparable to fine-tuning just the last layer.

Transfer Learning

SwiftAvatar: Efficient Auto-Creation of Parameterized Stylized Character on Arbitrary Avatar Engines

no code implementations19 Jan 2023 Shizun Wang, Weihong Zeng, Xu Wang, Hao Yang, Li Chen, Yi Yuan, Yunzhao Zeng, Min Zheng, Chuang Zhang, Ming Wu

To this end, we propose SwiftAvatar, a novel avatar auto-creation framework that is evidently superior to previous works.

Guided Recommendation for Model Fine-Tuning

no code implementations CVPR 2023 Hao Li, Charless Fowlkes, Hao Yang, Onkar Dabeer, Zhuowen Tu, Stefano Soatto

With thousands of historical training jobs, a recommendation system can be learned to predict the model selection score given the features of the dataset and the model as input.

Model Selection Transfer Learning

P-Transformer: Towards Better Document-to-Document Neural Machine Translation

no code implementations12 Dec 2022 Yachao Li, Junhui Li, Jing Jiang, Shimin Tao, Hao Yang, Min Zhang

To alleviate this problem, we propose a position-aware Transformer (P-Transformer) to enhance both the absolute and relative position information in both self-attention and cross-attention.

Machine Translation NMT +1

OFASys: A Multi-Modal Multi-Task Learning System for Building Generalist Models

1 code implementation8 Dec 2022 Jinze Bai, Rui Men, Hao Yang, Xuancheng Ren, Kai Dang, Yichang Zhang, Xiaohuan Zhou, Peng Wang, Sinan Tan, An Yang, Zeyu Cui, Yu Han, Shuai Bai, Wenbin Ge, Jianxin Ma, Junyang Lin, Jingren Zhou, Chang Zhou

As a starting point, we provide presets of 7 different modalities and 23 highly-diverse example tasks in OFASys, with which we also develop a first-in-kind, single model, OFA+, that can handle text, image, speech, video, and motion data.

Multi-Task Learning

TinyKG: Memory-Efficient Training Framework for Knowledge Graph Neural Recommender Systems

no code implementations8 Dec 2022 Huiyuan Chen, Xiaoting Li, Kaixiong Zhou, Xia Hu, Chin-Chia Michael Yeh, Yan Zheng, Hao Yang

We found that our TinyKG with INT2 quantization aggressively reduces the memory footprint of activation maps with $7 \times$, only with $2\%$ loss in accuracy, allowing us to deploy KGNNs on memory-constrained devices.

Knowledge Graphs Quantization +1

Denoising Self-attentive Sequential Recommendation

no code implementations8 Dec 2022 Huiyuan Chen, Yusan Lin, Menghai Pan, Lan Wang, Chin-Chia Michael Yeh, Xiaoting Li, Yan Zheng, Fei Wang, Hao Yang

Transformer-based sequential recommenders are very powerful for capturing both short-term and long-term sequential item dependencies.

Denoising Sequential Recommendation

Towards Generating Adversarial Examples on Mixed-type Data

no code implementations17 Oct 2022 Han Xu, Menghai Pan, Zhimeng Jiang, Huiyuan Chen, Xiaoting Li, Mahashweta Das, Hao Yang

The existence of adversarial attacks (or adversarial examples) brings huge concern about the machine learning (ML) model's safety issues.

Anomaly Detection Vocal Bursts Type Prediction

RedApt: An Adaptor for wav2vec 2 Encoding \\ Faster and Smaller Speech Translation without Quality Compromise

no code implementations16 Oct 2022 Jinming Zhao, Hao Yang, Gholamreza Haffari, Ehsan Shareghi

Pre-trained speech Transformers in speech translation (ST) have facilitated state-of-the-art (SotA) results; yet, using such encoders is computationally expensive.


Robot Task Planning and Situation Handling in Open Worlds

no code implementations4 Oct 2022 Yan Ding, Xiaohan Zhang, Saeid Amiri, Nieqing Cao, Hao Yang, Chad Esselink, Shiqi Zhang

This paper introduces a novel algorithm (COWP) for open-world task planning and situation handling that dynamically augments the robot's action knowledge with task-oriented common sense.

Common Sense Reasoning Robot Task Planning

MaskCLIP: Masked Self-Distillation Advances Contrastive Language-Image Pretraining

no code implementations CVPR 2023 Xiaoyi Dong, Jianmin Bao, Yinglin Zheng, Ting Zhang, Dongdong Chen, Hao Yang, Ming Zeng, Weiming Zhang, Lu Yuan, Dong Chen, Fang Wen, Nenghai Yu

Second, masked self-distillation is also consistent with vision-language contrastive from the perspective of training objective as both utilize the visual encoder for feature aligning, and thus is able to learn local semantics getting indirect supervision from the language.

Representation Learning

Prompt Tuning for Generative Multimodal Pretrained Models

1 code implementation4 Aug 2022 Hao Yang, Junyang Lin, An Yang, Peng Wang, Chang Zhou, Hongxia Yang

Prompt tuning has become a new paradigm for model tuning and it has demonstrated success in natural language pretraining and even vision pretraining.

Image Captioning Visual Entailment +1

Rethinking Few-Shot Object Detection on a Multi-Domain Benchmark

1 code implementation22 Jul 2022 Kibok Lee, Hao Yang, Satyaki Chakraborty, Zhaowei Cai, Gurumurthy Swaminathan, Avinash Ravichandran, Onkar Dabeer

Most existing works on few-shot object detection (FSOD) focus on a setting where both pre-training and few-shot learning datasets are from a similar domain.

Few-Shot Learning Few-Shot Object Detection +1

Boosting 3D Object Detection via Object-Focused Image Fusion

1 code implementation21 Jul 2022 Hao Yang, Chen Shi, Yihong Chen, LiWei Wang

Given a set of point features and image feature maps, DeMF adaptively aggregates image features by taking the projected 2D location of the 3D point as reference.

3D Object Detection object-detection

M-Adapter: Modality Adaptation for End-to-End Speech-to-Text Translation

1 code implementation3 Jul 2022 Jinming Zhao, Hao Yang, Ehsan Shareghi, Gholamreza Haffari

End-to-end speech-to-text translation models are often initialized with pre-trained speech encoder and pre-trained text decoder.

Speech-to-Text Translation Translation

Reliable Representations Make A Stronger Defender: Unsupervised Structure Refinement for Robust GNN

1 code implementation30 Jun 2022 Kuan Li, Yang Liu, Xiang Ao, Jianfeng Chi, Jinghua Feng, Hao Yang, Qing He

However, both strategies are faced with some immediate problems: raw features cannot represent various properties of nodes (e. g., structure information), and representations learned by supervised GNN may suffer from the poor performance of the classifier on the poisoned graph.

MACSA: A Multimodal Aspect-Category Sentiment Analysis Dataset with Multimodal Fine-grained Aligned Annotations

no code implementations28 Jun 2022 Hao Yang, Yanyan Zhao, Jianwei Liu, Yang Wu, Bing Qin

In this paper, we propose a new dataset, the Multimodal Aspect-Category Sentiment Analysis (MACSA) dataset, which contains more than 21K text-image pairs.

Sentiment Analysis

Traffic-Twitter Transformer: A Nature Language Processing-joined Framework For Network-wide Traffic Forecasting

no code implementations19 Jun 2022 Meng-Ju Tsai, Zhiyong Cui, Hao Yang, Cole Kopca, Sophie Tien, Yinhai Wang

To better manage future roadway capacity and accommodate social and human impacts, it is crucial to propose a flexible and comprehensive framework to predict physical-aware long-term traffic conditions for public users and transportation agencies.

Management Time Series Analysis +1

Instance-wise Prompt Tuning for Pretrained Language Models

no code implementations4 Jun 2022 Yuezihan Jiang, Hao Yang, Junyang Lin, Hanyu Zhao, An Yang, Chang Zhou, Hongxia Yang, Zhi Yang, Bin Cui

Prompt Learning has recently gained great popularity in bridging the gap between pretraining tasks and various downstream tasks.

Exploring Entity Interactions for Few-Shot Relation Learning (Student Abstract)

no code implementations4 May 2022 Yi Liang, Shuai Zhao, Bo Cheng, Yuwei Yin, Hao Yang

Few-shot relation learning refers to infer facts for relations with a limited number of observed triples.

Metric Learning

Neighbors Are Not Strangers: Improving Non-Autoregressive Translation under Low-Frequency Lexical Constraints

1 code implementation NAACL 2022 Chun Zeng, Jiangjie Chen, Tianyi Zhuang, Rui Xu, Hao Yang, Ying Qin, Shimin Tao, Yanghua Xiao

To this end, we propose a plug-in algorithm for this line of work, i. e., Aligned Constrained Training (ACT), which alleviates this problem by familiarizing the model with the source-side context of the constraints.


Real-Time Neural Character Rendering with Pose-Guided Multiplane Images

1 code implementation25 Apr 2022 Hao Ouyang, Bo Zhang, Pan Zhang, Hao Yang, Jiaolong Yang, Dong Chen, Qifeng Chen, Fang Wen

We propose pose-guided multiplane image (MPI) synthesis which can render an animatable character in real scenes with photorealistic quality.

Image-to-Image Translation Neural Rendering +1

Large-Scale Pre-training for Person Re-identification with Noisy Labels

2 code implementations CVPR 2022 Dengpan Fu, Dongdong Chen, Hao Yang, Jianmin Bao, Lu Yuan, Lei Zhang, Houqiang Li, Fang Wen, Dong Chen

Since theses ID labels automatically derived from tracklets inevitably contain noises, we develop a large-scale Pre-training framework utilizing Noisy Labels (PNL), which consists of three learning modules: supervised Re-ID learning, prototype-based contrastive learning, and label-guided contrastive learning.

Contrastive Learning Multi-Object Tracking +3

Sentiment Word Aware Multimodal Refinement for Multimodal Sentiment Analysis with ASR Errors

1 code implementation Findings (ACL) 2022 Yang Wu, Yanyan Zhao, Hao Yang, Song Chen, Bing Qin, Xiaohuan Cao, Wenting Zhao

Through further analysis of the ASR outputs, we find that in some cases the sentiment words, the key sentiment elements in the textual modality, are recognized as other words, which makes the sentiment of the text change and hurts the performance of multimodal sentiment models directly.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +3

Rethinking Feature Uncertainty in Stochastic Neural Networks for Adversarial Robustness

no code implementations1 Jan 2022 Hao Yang, Min Wang, Zhengfei Yu, Yun Zhou

Extensive experiments on well-known white- and black-box attacks show that MFDV-SNN achieves a significant improvement over existing methods, which indicates that it is a simple but effective method to improve model robustness.

Adversarial Robustness

Joint-training on Symbiosis Networks for Deep Nueral Machine Translation models

no code implementations22 Dec 2021 Zhengzhe Yu, Jiaxin Guo, Minghan Wang, Daimeng Wei, Hengchao Shang, Zongyao Li, Zhanglin Wu, Yuxia Wang, Yimeng Chen, Chang Su, Min Zhang, Lizhi Lei, Shimin Tao, Hao Yang

Deep encoders have been proven to be effective in improving neural machine translation (NMT) systems, but it reaches the upper bound of translation quality when the number of encoder layers exceeds 18.

Machine Translation NMT +1

Self-Distillation Mixup Training for Non-autoregressive Neural Machine Translation

no code implementations22 Dec 2021 Jiaxin Guo, Minghan Wang, Daimeng Wei, Hengchao Shang, Yuxia Wang, Zongyao Li, Zhengzhe Yu, Zhanglin Wu, Yimeng Chen, Chang Su, Min Zhang, Lizhi Lei, Shimin Tao, Hao Yang

An effective training strategy to improve the performance of AT models is Self-Distillation Mixup (SDM) Training, which pre-trains a model on raw data, generates distilled data by the pre-trained model itself and finally re-trains a model on the combination of raw data and distilled data.

Knowledge Distillation Machine Translation +1

General Facial Representation Learning in a Visual-Linguistic Manner

1 code implementation CVPR 2022 Yinglin Zheng, Hao Yang, Ting Zhang, Jianmin Bao, Dongdong Chen, Yangyu Huang, Lu Yuan, Dong Chen, Ming Zeng, Fang Wen

In this paper, we study the transfer performance of pre-trained models on face analysis tasks and introduce a framework, called FaRL, for general Facial Representation Learning in a visual-linguistic manner.

 Ranked #1 on Face Parsing on CelebAMask-HQ (using extra training data)

Face Alignment Face Parsing +1

Delayed Propagation Transformer: A Universal Computation Engine towards Practical Control in Cyber-Physical Systems

1 code implementation NeurIPS 2021 Wenqing Zheng, Qiangqiang Guo, Hao Yang, Peihao Wang, Zhangyang Wang

This paper presents the Delayed Propagation Transformer (DePT), a new transformer-based model that specializes in the global modeling of CPS while taking into account the immutable constraints from the physical world.

Inductive Bias

Few-shot graph link prediction with domain adaptation

no code implementations29 Sep 2021 Hao Zhu, Mahashweta Das, Mangesh Bendre, Fei Wang, Hao Yang, Soha Hassoun

In this work, we propose an adversarial training based modification to the current state-of-the-arts link prediction method to solve this problem.

Domain Adaptation Few-Shot Learning +1

ADNet: Leveraging Error-Bias Towards Normal Direction in Face Alignment

1 code implementation ICCV 2021 Yangyu Huang, Hao Yang, Chong Li, Jongyoo Kim, Fangyun Wei

On the other hand, AAM is an attention module which can get anisotropic attention mask focusing on the region of point and its local edge connected by adjacent points, it has a stronger response in tangent than in normal, which means relaxed constraints in the tangent.

Face Alignment

How Does Adversarial Fine-Tuning Benefit BERT?

no code implementations31 Aug 2021 Javid Ebrahimi, Hao Yang, Wei zhang

Adversarial training (AT) is one of the most reliable methods for defending against adversarial attacks in machine learning.

Continual Learning Dependency Parsing +2

Event2Graph: Event-driven Bipartite Graph for Multivariate Time-series Anomaly Detection

no code implementations15 Aug 2021 Yuhang Wu, Mengting Gu, Lan Wang, Yusan Lin, Fei Wang, Hao Yang

Modeling inter-dependencies between time-series is the key to achieve high performance in anomaly detection for multivariate time-series data.

Anomaly Detection Time Series Anomaly Detection

Task and Situation Structures for Service Agent Planning

no code implementations27 Jul 2021 Hao Yang, Tavan Eftekhar, Chad Esselink, Yan Ding, Shiqi Zhang

Everyday tasks are characterized by their varieties and variations, and frequently are not clearly specified to service agents.

Patch-Wise Spatial-Temporal Quality Enhancement for HEVC Compressed Video

1 code implementation journal 2021 Qing Ding, Liquan Shen, Liangwei Yu, Hao Yang, Mai Xu

To overcome these limitations, we propose a patch-wise spatial-temporal quality enhancement network which firstly extracts spatial and temporal features, then recalibrates and fuses the obtained spatial and temporal features.

Quantization Video Enhancement

Normalization of Language Embeddings for Cross-Lingual Alignment

1 code implementation NeurIPS 2021 Prince Osei Aboagye, Jeff Phillips, Yan Zheng, Chin-Chia Michael Yeh, Junpeng Wang, Wei zhang, Liang Wang, Hao Yang

Learning a good transfer function to map the word vectors from two languages into a shared cross-lingual word vector space plays a crucial role in cross-lingual NLP.


Pick and Choose: A GNN-based Imbalanced Learning Approach for Fraud Detection

1 code implementation The Web Conference 2021 Yang Liu1, Xiang Ao, Zidi Qin, Jianfeng Chi, Jinghua Feng, Hao Yang, Qing He

Graph-based fraud detection approaches have escalated lots of attention recently due to the abundant relational information of graph-structured data, which may be beneficial for the detection of fraudsters.

Fraud Detection Node Classification

Integrating Subgraph-aware Relation and DirectionReasoning for Question Answering

no code implementations1 Apr 2021 Xu Wang, Shuai Zhao, Bo Cheng, Jiale Han, Yingting Li, Hao Yang, Ivan Sekulic, Guoshun Nan

Question Answering (QA) models over Knowledge Bases (KBs) are capable of providing more precise answers by utilizing relation information among entities.

Question Answering

Learning from Noisy Labels via Dynamic Loss Thresholding

no code implementations1 Apr 2021 Hao Yang, Youzhi Jin, Ziyin Li, Deng-Bao Wang, Lei Miao, Xin Geng, Min-Ling Zhang

During the training process, DLT records the loss value of each sample and calculates dynamic loss thresholds.

Style-based Point Generator with Adversarial Rendering for Point Cloud Completion

1 code implementation CVPR 2021 Chulin Xie, Chuxin Wang, Bo Zhang, Hao Yang, Dong Chen, Fang Wen

In this paper, we proposed a novel Style-based Point Generator with Adversarial Rendering (SpareNet) for point cloud completion.

 Ranked #1 on Point Cloud Completion on ShapeNet (Earth Mover's Distance metric)

Point Cloud Completion

Adversarial Example Detection Using Latent Neighborhood Graph

no code implementations ICCV 2021 Ahmed Abusnaina, Yuhang Wu, Sunpreet Arora, Yizhen Wang, Fei Wang, Hao Yang, David Mohaisen

We present the first graph-based adversarial detection method that constructs a Latent Neighborhood Graph (LNG) around an input example to determine if the input example is adversarial.

Adversarial Attack Graph Attention

On Position Embeddings in BERT

no code implementations ICLR 2021 Benyou Wang, Lifeng Shang, Christina Lioma, Xin Jiang, Hao Yang, Qun Liu, Jakob Grue Simonsen

Various Position Embeddings (PEs) have been proposed in Transformer based architectures~(e. g. BERT) to model word order.

General Classification Translation

Beating Attackers At Their Own Games: Adversarial Example Detection Using Adversarial Gradient Directions

no code implementations31 Dec 2020 Yuhang Wu, Sunpreet S. Arora, Yanhong Wu, Hao Yang

Adversarial examples are input examples that are specifically crafted to deceive machine learning classifiers.

Unsupervised Pre-training for Person Re-identification

1 code implementation CVPR 2021 Dengpan Fu, Dongdong Chen, Jianmin Bao, Hao Yang, Lu Yuan, Lei Zhang, Houqiang Li, Dong Chen

In this paper, we present a large scale unlabeled person re-identification (Re-ID) dataset "LUPerson" and make the first attempt of performing unsupervised pre-training for improving the generalization ability of the learned person Re-ID feature representation.

Ranked #2 on Person Re-Identification on Market-1501 (using extra training data)

Data Augmentation Person Re-Identification +1

Gaussian State-Based Quantum Illumination with Simple Photodetection

no code implementations27 Nov 2020 Hao Yang, Wojciech Roga, Jonathan D. Pritchard, John Jeffers

We use the continuous-variable Gaussian quantum information formalism to show that quantum illumination is better for object detection compared with coherent states of the same mean photon number, even for simple direct photodetection.

Object Detection Quantum Physics

A coarse-to-fine framework for unsupervised multi-contrast MR image deformable registration with dual consistency constraint

no code implementations5 Aug 2020 Weijian Huang, Hao Yang, Xinfeng Liu, Cheng Li, Ian Zhang, Rongpin Wang, Hairong Zheng, Shan-Shan Wang

Multi-contrast magnetic resonance (MR) image registration is useful in the clinic to achieve fast and accurate imaging-based disease diagnosis and treatment planning.

Image Registration

Edge Computing for Real-Time Near-Crash Detection for Smart Transportation Applications

no code implementations2 Aug 2020 Ruimin Ke, Zhiyong Cui, Yanlong Chen, Meixin Zhu, Hao Yang, Yinhai Wang

It is among the first efforts in applying edge computing for real-time traffic video analytics and is expected to benefit multiple sub-fields in smart transportation research and applications.

Autonomous Driving Edge-computing +2

Category-Specific CNN for Visual-aware CTR Prediction at

no code implementations18 Jun 2020 Hu Liu, Jing Lu, Hao Yang, Xiwei Zhao, Sulong Xu, Hao Peng, Zehua Zhang, Wenjie Niu, Xiaokun Zhu, Yongjun Bao, Weipeng Yan

Existing algorithms usually extract visual features using off-the-shelf Convolutional Neural Networks (CNNs) and late fuse the visual and non-visual features for the finally predicted CTR.

Click-Through Rate Prediction

GroupIM: A Mutual Information Maximization Framework for Neural Group Recommendation

1 code implementation5 Jun 2020 Aravind Sankar, Yanhong Wu, Yuhang Wu, Wei zhang, Hao Yang, Hari Sundaram

We study the problem of making item recommendations to ephemeral groups, which comprise users with limited or no historical activities together.

Transfer Learning via Contextual Invariants for One-to-Many Cross-Domain Recommendation

no code implementations21 May 2020 Adit Krishnan, Mahashweta Das, Mangesh Bendre, Hao Yang, Hari Sundaram

The rapid proliferation of new users and items on the social web has aggravated the gray-sheep user/long-tail item challenge in recommender systems.

Clustering Collaborative Filtering +2

Fashion Recommendation and Compatibility Prediction Using Relational Network

no code implementations13 May 2020 Maryam Moosaei, Yusan Lin, Hao Yang

There are a few approaches that consider an entire outfit, but these approaches have limitations such as requiring rich semantic information, category labels, and fixed order of items.

Adversarial Light Projection Attacks on Face Recognition Systems: A Feasibility Study

no code implementations24 Mar 2020 Dinh-Luan Nguyen, Sunpreet S. Arora, Yuhang Wu, Hao Yang

While feasible, digital attacks have limited applicability in attacking deployed systems, including face recognition systems, where an adversary typically has access to the input and not the transmission channel.

Face Recognition

Feedback Graph Convolutional Network for Skeleton-based Action Recognition

no code implementations17 Mar 2020 Hao Yang, Dan Yan, Li Zhang, Dong Li, YunDa Sun, ShaoDi You, Stephen J. Maybank

It transmits the high-level semantic features to the low-level layers and flows temporal information stage by stage to progressively model global spatial-temporal features for action recognition; (3) The FGCN model provides early predictions.

Action Recognition Skeleton Based Action Recognition

Rethinking the Hyperparameters for Fine-tuning

1 code implementation ICLR 2020 Hao Li, Pratik Chaudhari, Hao Yang, Michael Lam, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto

Our findings challenge common practices of fine-tuning and encourages deep learning practitioners to rethink the hyperparameters for fine-tuning.

Transfer Learning

Multi-Task Incremental Learning for Object Detection

no code implementations13 Feb 2020 Xialei Liu, Hao Yang, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto

For the difficult cases, where the domain gaps and especially category differences are large, we explore three different exemplar sampling methods and show the proposed adaptive sampling method is effective to select diverse and informative samples from entire datasets, to further prevent forgetting.

Incremental Learning object-detection +1

FaceShifter: Towards High Fidelity And Occlusion Aware Face Swapping

8 code implementations31 Dec 2019 Lingzhi Li, Jianmin Bao, Hao Yang, Dong Chen, Fang Wen

We propose a novel attributes encoder for extracting multi-level target face attributes, and a new generator with carefully designed Adaptive Attentional Denormalization (AAD) layers to adaptively integrate the identity and the attributes for face synthesis.

Face Generation Face Swapping +1

Face X-ray for More General Face Forgery Detection

4 code implementations CVPR 2020 Lingzhi Li, Jianmin Bao, Ting Zhang, Hao Yang, Dong Chen, Fang Wen, Baining Guo

For this reason, face X-ray provides an effective way for detecting forgery generated by most existing face manipulation algorithms.

DeepFake Detection Face Swapping

motif2vec: Motif Aware Node Representation Learning for Heterogeneous Networks

no code implementations22 Aug 2019 Manoj Reddy Dareddy, Mahashweta Das, Hao Yang

Supervised machine learning tasks in networks such as node classification and link prediction require us to perform feature engineering that is known and agreed to be the key to success in applied machine learning.

BIG-bench Machine Learning Feature Engineering +4

Detecting 11K Classes: Large Scale Object Detection without Fine-Grained Bounding Boxes

no code implementations ICCV 2019 Hao Yang, Hao Wu, Hao Chen

However, these methods require fully annotated object bounding boxes for training, which are incredibly hard to scale up due to the high annotation cost.

object-detection Object Detection +1

Position Focused Attention Network for Image-Text Matching

1 code implementation23 Jul 2019 Yaxiong Wang, Hao Yang, Xueming Qian, Lin Ma, Jing Lu, Biao Li, Xin Fan

Then, an attention mechanism is proposed to model the relations between the image region and blocks and generate the valuable position feature, which will be further utilized to enhance the region expression and model a more reliable relationship between the visual image and the textual sentence.

Text Matching

CLCI-Net: Cross-Level fusion and Context Inference Networks for Lesion Segmentation of Chronic Stroke

2 code implementations16 Jul 2019 Hao Yang, Weijian Huang, Kehan Qi, Cheng Li, Xinfeng Liu, Meiyun Wang, Hairong Zheng, Shan-Shan Wang

To address these challenges, this paper proposes a Cross-Level fusion and Context Inference Network (CLCI-Net) for the chronic stroke lesion segmentation from T1-weighted MR images.

Image Segmentation Lesion Segmentation +1

Face Parsing with RoI Tanh-Warping

2 code implementations CVPR 2019 Jinpeng Lin, Hao Yang, Dong Chen, Ming Zeng, Fang Wen, Lu Yuan

It uses hierarchical local based method for inner facial components and global methods for outer facial components.

Face Parsing

Real-Time Steganalysis for Stream Media Based on Multi-channel Convolutional Sliding Windows

no code implementations4 Feb 2019 Zhongliang Yang, Hao Yang, Yuting Hu, Yongfeng Huang, Yu-Jin Zhang

To solve these two challenges, in this paper, combined with the sliding window detection algorithm and Convolution Neural Network we propose a real-time VoIP steganalysis method which based on multi-channel convolution sliding windows.


Dynamic Graph Representation Learning via Self-Attention Networks

2 code implementations22 Dec 2018 Aravind Sankar, Yanhong Wu, Liang Gou, Wei zhang, Hao Yang

Learning latent representations of nodes in graphs is an important and ubiquitous task with widespread applications such as link prediction, node classification, and graph visualization.

General Classification Graph Embedding +3

An End-to-End Multi-task Learning Model for Fact Checking

no code implementations WS 2018 Sizhen Li, Shuai Zhao, Bo Cheng, Hao Yang

With huge amount of information generated every day on the web, fact checking is an important and challenging task which can help people identify the authenticity of most claims as well as providing evidences selected from knowledge source like Wikipedia.

Common Sense Reasoning Entity Linking +4

Exploiting Web Images for Weakly Supervised Object Detection

no code implementations27 Jul 2017 Qingyi Tao, Hao Yang, Jianfei Cai

Object detection without bounding box annotations, i. e, weakly supervised detection methods, are still lagging far behind.

Ranked #17 on Weakly Supervised Object Detection on PASCAL VOC 2012 test (using extra training data)

object-detection Transfer Learning +1

MIML-FCN+: Multi-instance Multi-label Learning via Fully Convolutional Networks with Privileged Information

no code implementations CVPR 2017 Hao Yang, Joey Tianyi Zhou, Jianfei Cai, Yew Soon Ong

As the proposed PI loss is convex and SGD compatible and the framework itself is a fully convolutional network, MIML-FCN+ can be easily integrated with state of-the-art deep learning networks.

Image Captioning Multi-Label Learning +1

Improving Multi-label Learning with Missing Labels by Structured Semantic Correlations

no code implementations4 Aug 2016 Hao Yang, Joey Tianyi Zhou, Jianfei Cai

Experimental results demonstrate the effectiveness of the proposed semantic descriptor and the usefulness of incorporating the structured semantic correlations.

Multi-Label Learning Object Recognition

A Comparative Study of Object Trackers for Infrared Flying Bird Tracking

no code implementations18 Jan 2016 Ying Huang, Hong Zheng, Haibin Ling, Erik Blasch, Hao Yang

Bird strikes present a huge risk for aircraft, especially since traditional airport bird surveillance is mainly dependent on inefficient human observation.

A Parallel Way to Select the Parameters of SVM Based on the Ant Optimization Algorithm

no code implementations19 May 2014 Chao Zhang, Hong-cen Mei, Hao Yang

A large number of experimental data shows that Support Vector Machine (SVM) algorithm has obvious advantages in text classification, handwriting recognition, image classification, bioinformatics, and some other fields.

Algorithm General Classification +4

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