Search Results for author: Chao Li

Found 143 papers, 50 papers with code

Evolutionary Topology Search for Tensor Network Decomposition

no code implementations ICML 2020 Chao Li, Zhun Sun

Tensor network (TN) decomposition is a promising framework to represent extremely high-dimensional problems with few parameters.

Spatially Covariant Lesion Segmentation

no code implementations19 Jan 2023 Hang Zhang, Rongguang Wang, Jinwei Zhang, Dongdong Liu, Chao Li, Jiahao Li

Compared to natural images, medical images usually show stronger visual patterns and therefore this adds flexibility and elasticity to resource-limited clinical applications by injecting proper priors into neural networks.

Lesion Segmentation Tumor Segmentation

Centralized Cooperative Exploration Policy for Continuous Control Tasks

1 code implementation6 Jan 2023 Chao Li, Chen Gong, Qiang He, Xinwen Hou, Yu Liu

To explicitly encourage exploration in continuous control tasks, we propose CCEP (Centralized Cooperative Exploration Policy), which utilizes underestimation and overestimation of value functions to maintain the capacity of exploration.

Continuous Control

Accelerating Self-Imitation Learning from Demonstrations via Policy Constraints and Q-Ensemble

no code implementations7 Dec 2022 Chao Li

Both imitation learning (IL) and learning from demonstrations (LfD) improve the training process by using expert demonstrations, but imperfect expert demonstrations can mislead policy improvement.

Continuous Control Imitation Learning +2

Differentiable Meta Multigraph Search with Partial Message Propagation on Heterogeneous Information Networks

no code implementations27 Nov 2022 Chao Li, Hao Xu, Kun He

To address these issues, we propose a novel method called Partial Message Meta Multigraph search (PMMM) to automatically optimize the neural architecture design on HINs.

Neural Architecture Search Node Classification

Self-supervised Trajectory Representation Learning with Temporal Regularities and Travel Semantics

1 code implementation17 Nov 2022 Jiawei Jiang, Dayan Pan, Houxing Ren, Xiaohan Jiang, Chao Li, Jingyuan Wang

TRL aims to convert complicated raw trajectories into low-dimensional representation vectors, which can be applied to various downstream tasks, such as trajectory classification, clustering, and similarity computation.

Contrastive Learning Graph Attention +2

Hypergraph Transformer for Skeleton-based Action Recognition

no code implementations17 Nov 2022 Yuxuan Zhou, Chao Li, Zhi-Qi Cheng, Yifeng Geng, Xuansong Xie, Margret Keuper

Transformers assume that the input is permutation-invariant and homogeneous (partially alleviated by positional encoding), which ignores an important characteristic of skeleton data, i. e., bone connectivity.

Action Recognition Skeleton Based Action Recognition

LARO: Learned Acquisition and Reconstruction Optimization to accelerate Quantitative Susceptibility Mapping

1 code implementation1 Nov 2022 Jinwei Zhang, Pascal Spincemaille, Hang Zhang, Thanh D. Nguyen, Chao Li, Jiahao Li, Ilhami Kovanlikaya, Mert R. Sabuncu, Yi Wang

In this paper, we present our new framework, called Learned Acquisition and Reconstruction Optimization (LARO), which aims to accelerate the multi-echo gradient echo (mGRE) pulse sequence for QSM.

Instance Segmentation for Chinese Character Stroke Extraction, Datasets and Benchmarks

1 code implementation25 Oct 2022 Lizhao Liu, Kunyang Lin, Shangxin Huang, Zhongli Li, Chao Li, Yunbo Cao, Qingyu Zhou

Moreover, there are no standardized benchmarks to provide a fair comparison between different stroke extraction methods, which, we believe, is a major impediment to the development of Chinese character stroke understanding and related tasks.

Font Generation Instance Segmentation +1

Hierarchical Multi-Interest Co-Network For Coarse-Grained Ranking

no code implementations19 Oct 2022 Xu Yuan, Chen Xu, Qiwei Chen, Tao Zhuang, Hongjie Chen, Chao Li, Junfeng Ge

This paper proposes a Hierarchical Multi-Interest Co-Network (HCN) to capture users' diverse interests in the coarse-grained ranking stage.

Rethinking Prototypical Contrastive Learning through Alignment, Uniformity and Correlation

no code implementations18 Oct 2022 Shentong Mo, Zhun Sun, Chao Li

Particularly, in the classification down-stream tasks with linear probes, our proposed method outperforms the state-of-the-art instance-wise and prototypical contrastive learning methods on the ImageNet-100 dataset by 2. 96% and the ImageNet-1K dataset by 2. 46% under the same settings of batch size and epochs.

Contrastive Learning Self-Supervised Learning

DRKF: Distilled Rotated Kernel Fusion for Efficiently Boosting Rotation Invariance in Image Matching

no code implementations22 Sep 2022 Chao Li, Jiancheng Cai, Ranran Huang, Xinmin Liu

Most existing learning-based image matching pipelines are designed for better feature detectors and descriptors which are robust to repeated textures, viewpoint changes, etc., while little attention has been paid to rotation invariance.

Knowledge Distillation

DBT-DMAE: An Effective Multivariate Time Series Pre-Train Model under Missing Data

no code implementations16 Sep 2022 Kai Zhang, Qinmin Yang, Chao Li

Multivariate time series(MTS) is a universal data type related to many practical applications.

Time Series

Omni-Dimensional Dynamic Convolution

1 code implementation ICLR 2022 Chao Li, Aojun Zhou, Anbang Yao

Learning a single static convolutional kernel in each convolutional layer is the common training paradigm of modern Convolutional Neural Networks (CNNs).

MAFormer: A Transformer Network with Multi-scale Attention Fusion for Visual Recognition

no code implementations31 Aug 2022 Yunhao Wang, Huixin Sun, Xiaodi Wang, Bin Zhang, Chao Li, Ying Xin, Baochang Zhang, Errui Ding, Shumin Han

We develop a simple but effective module to explore the full potential of transformers for visual representation by learning fine-grained and coarse-grained features at a token level and dynamically fusing them.

Instance Segmentation object-detection +2

AiM: Taking Answers in Mind to Correct Chinese Cloze Tests in Educational Applications

1 code implementation COLING 2022 Yusen Zhang, Zhongli Li, Qingyu Zhou, Ziyi Liu, Chao Li, Mina Ma, Yunbo Cao, Hongzhi Liu

To automatically correct handwritten assignments, the traditional approach is to use an OCR model to recognize characters and compare them to answers.

Optical Character Recognition

Siamese Prototypical Contrastive Learning

no code implementations18 Aug 2022 Shentong Mo, Zhun Sun, Chao Li

One of the drawbacks of CSL is that the loss term requires a large number of negative samples to provide better mutual information bound ideally.

Contrastive Learning Self-Supervised Learning

Language Supervised Training for Skeleton-based Action Recognition

1 code implementation10 Aug 2022 Wangmeng Xiang, Chao Li, Yuxuan Zhou, Biao Wang, Lei Zhang

More specifically, we employ a large-scale language model as the knowledge engine to provide text descriptions for body parts movements of actions, and propose a multi-modal training scheme by utilizing the text encoder to generate feature vectors for different body parts and supervise the skeleton encoder for action representation learning.

Action Recognition Language Modelling +2

Spatiotemporal Self-attention Modeling with Temporal Patch Shift for Action Recognition

1 code implementation27 Jul 2022 Wangmeng Xiang, Chao Li, Biao Wang, Xihan Wei, Xian-Sheng Hua, Lei Zhang

For 3D video-based tasks such as action recognition, however, directly applying spatiotemporal transformers on video data will bring heavy computation and memory burdens due to the largely increased number of patches and the quadratic complexity of self-attention computation.

Action Classification Action Recognition

Snipper: A Spatiotemporal Transformer for Simultaneous Multi-Person 3D Pose Estimation Tracking and Forecasting on a Video Snippet

1 code implementation9 Jul 2022 Shihao Zou, Yuanlu Xu, Chao Li, Lingni Ma, Li Cheng, Minh Vo

In this paper, we propose Snipper, a framework to perform multi-person 3D pose estimation, tracking and motion forecasting simultaneously in a single inference.

3D Pose Estimation Motion Forecasting

SALO: An Efficient Spatial Accelerator Enabling Hybrid Sparse Attention Mechanisms for Long Sequences

no code implementations29 Jun 2022 Guan Shen, Jieru Zhao, Quan Chen, Jingwen Leng, Chao Li, Minyi Guo

However, the quadratic complexity of self-attention w. r. t the sequence length incurs heavy computational and memory burdens, especially for tasks with long sequences.

SP-ViT: Learning 2D Spatial Priors for Vision Transformers

no code implementations15 Jun 2022 Yuxuan Zhou, Wangmeng Xiang, Chao Li, Biao Wang, Xihan Wei, Lei Zhang, Margret Keuper, Xiansheng Hua

Unlike convolutional inductive biases, which are forced to focus exclusively on hard-coded local regions, our proposed SPs are learned by the model itself and take a variety of spatial relations into account.

Image Classification

Permutation Search of Tensor Network Structures via Local Sampling

1 code implementation14 Jun 2022 Chao Li, Junhua Zeng, Zerui Tao, Qibin Zhao

Recent works put much effort into tensor network structure search (TN-SS), aiming to select suitable tensor network (TN) structures, involving the TN-ranks, formats, and so on, for the decomposition or learning tasks.

Gleo-Det: Deep Convolution Feature-Guided Detector with Local Entropy Optimization for Salient Points

no code implementations27 Apr 2022 Chao Li, Yanan You, Wenli Zhou

3) With the guidance of convolution features, we define the cost function from both positive and negative sides.

Enhancing the Robustness, Efficiency, and Diversity of Differentiable Architecture Search

no code implementations10 Apr 2022 Chao Li, Jia Ning, Han Hu, Kun He

Differentiable architecture search (DARTS) has attracted much attention due to its simplicity and significant improvement in efficiency.

Multi-modal learning for predicting the genotype of glioma

no code implementations21 Mar 2022 Yiran Wei, Xi Chen, Lei Zhu, Lipei Zhang, Carola-Bibiane Schönlieb, Stephen J. Price, Chao Li

In this study, we propose a multi-modal learning framework using three separate encoders to extract features of focal tumor image, tumor geometrics and global brain networks.

Clinical Knowledge

Type-Driven Multi-Turn Corrections for Grammatical Error Correction

1 code implementation Findings (ACL) 2022 Shaopeng Lai, Qingyu Zhou, Jiali Zeng, Zhongli Li, Chao Li, Yunbo Cao, Jinsong Su

First, they simply mix additionally-constructed training instances and original ones to train models, which fails to help models be explicitly aware of the procedure of gradual corrections.

Data Augmentation Grammatical Error Correction

Predicting conversion of mild cognitive impairment to Alzheimer's disease

no code implementations8 Mar 2022 Yiran Wei, Stephen J. Price, Carola-Bibiane Schönlieb, Chao Li

In this study, we develop a self-supervised contrastive learning approach to generate structural brain networks from routine anatomical MRI under the guidance of diffusion MRI.

Contrastive Learning Management

Fast density peaks clustering algorithm in polar coordinate system

no code implementations Applied Intelligence 2022 Chao Li, Shifei Ding, Xiao Xu, Shuying Du & Tianhao Shi

Density peaks clustering (DPC) algorithm provides an efficient method to quickly find cluster centers with decision graphs.

Mutual Contrastive Low-rank Learning to Disentangle Whole Slide Image Representations for Glioma Grading

no code implementations8 Mar 2022 Lipei Zhang, Yiran Wei, Ying Fu, Stephen Price, Carola-Bibiane Schönlieb, Chao Li

In this proposed scheme, we design a normalized modality contrastive loss (NMC-loss), which could promote to disentangle multi-modality complementary representation of FFPE and frozen sections from the same patient.

Contrastive Learning Disentanglement +1

$A^{3}D$: A Platform of Searching for Robust Neural Architectures and Efficient Adversarial Attacks

no code implementations7 Mar 2022 Jialiang Sun, Wen Yao, Tingsong Jiang, Chao Li, Xiaoqian Chen

To alleviate these problems, in this paper, we first propose a novel platform called auto adversarial attack and defense ($A^{3}D$), which can help search for robust neural network architectures and efficient adversarial attacks.

Adversarial Attack Adversarial Defense +1

Exploring Structural Sparsity in Neural Image Compression

no code implementations9 Feb 2022 Shanzhi Yin, Chao Li, Wen Tan, Youneng Bao, Yongsheng Liang, Wei Liu

Neural image compression have reached or out-performed traditional methods (such as JPEG, BPG, WebP).

Image Compression

Collaborative learning of images and geometrics for predicting isocitrate dehydrogenase status of glioma

no code implementations14 Jan 2022 Yiran Wei, Chao Li, Xi Chen, Carola-Bibiane Schönlieb, Stephen J. Price

Further, the collaborative learning model achieves better performance than either the CNN or the GNN alone.

Improved (Related-key) Differential-based Neural Distinguishers for SIMON and SIMECK Block Ciphers

1 code implementation11 Jan 2022 Jinyu Lu, Guoqiang Liu, Bing Sun, Chao Li, Li Liu

In CRYPTO 2019, Gohr made a pioneering attempt and successfully applied deep learning to the differential cryptanalysis against NSA block cipher SPECK32/64, achieving higher accuracy than the pure differential distinguishers.


Context-Aware Compilation of DNN Training Pipelines across Edge and Cloud

1 code implementation Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2021 Dixi Yao, Liyao Xiang, Zifan Wang, Jiayu Xu, Chao Li, Xinbing Wang

Experimental results show that our system not only adapts well to, but also draws on the varying contexts, delivering a practical and efficient solution to edge-cloud model training.

Ranked #2 on Recommendation Systems on MovieLens 1M (Precision metric)

Image Classification Image Generation +4

Universal Efficient Variable-rate Neural Image Compression

no code implementations18 Nov 2021 Shanzhi Yin, Chao Li, Youneng Bao, Yongsheng Liang

Recently, Learning-based image compression has reached comparable performance with traditional image codecs(such as JPEG, BPG, WebP).

Image Compression

LibCity: An Open Library for Traffic Prediction

1 code implementation International Conference on Advances in Geographic Information Systems 2021 Jingyuan Wang, Jiawei Jiang, Wenjun Jiang, Chao Li, Wayne Xin Zhao

This paper presents LibCity, a unified, comprehensive, and extensible library for traffic prediction, which provides researchers with a credible experimental tool and a convenient development framework.

Multivariate Time Series Forecasting Spatio-Temporal Forecasting +2

Ego4D: Around the World in 3,000 Hours of Egocentric Video

3 code implementations CVPR 2022 Kristen Grauman, Andrew Westbury, Eugene Byrne, Zachary Chavis, Antonino Furnari, Rohit Girdhar, Jackson Hamburger, Hao Jiang, Miao Liu, Xingyu Liu, Miguel Martin, Tushar Nagarajan, Ilija Radosavovic, Santhosh Kumar Ramakrishnan, Fiona Ryan, Jayant Sharma, Michael Wray, Mengmeng Xu, Eric Zhongcong Xu, Chen Zhao, Siddhant Bansal, Dhruv Batra, Vincent Cartillier, Sean Crane, Tien Do, Morrie Doulaty, Akshay Erapalli, Christoph Feichtenhofer, Adriano Fragomeni, Qichen Fu, Abrham Gebreselasie, Cristina Gonzalez, James Hillis, Xuhua Huang, Yifei HUANG, Wenqi Jia, Weslie Khoo, Jachym Kolar, Satwik Kottur, Anurag Kumar, Federico Landini, Chao Li, Yanghao Li, Zhenqiang Li, Karttikeya Mangalam, Raghava Modhugu, Jonathan Munro, Tullie Murrell, Takumi Nishiyasu, Will Price, Paola Ruiz Puentes, Merey Ramazanova, Leda Sari, Kiran Somasundaram, Audrey Southerland, Yusuke Sugano, Ruijie Tao, Minh Vo, Yuchen Wang, Xindi Wu, Takuma Yagi, Ziwei Zhao, Yunyi Zhu, Pablo Arbelaez, David Crandall, Dima Damen, Giovanni Maria Farinella, Christian Fuegen, Bernard Ghanem, Vamsi Krishna Ithapu, C. V. Jawahar, Hanbyul Joo, Kris Kitani, Haizhou Li, Richard Newcombe, Aude Oliva, Hyun Soo Park, James M. Rehg, Yoichi Sato, Jianbo Shi, Mike Zheng Shou, Antonio Torralba, Lorenzo Torresani, Mingfei Yan, Jitendra Malik

We introduce Ego4D, a massive-scale egocentric video dataset and benchmark suite.

De-identification Ethics

L3C-Stereo: Lossless Compression for Stereo Images

no code implementations21 Aug 2021 Zihao Huang, Zhe Sun, Feng Duan, Andrzej Cichocki, Peiying Ruan, Chao Li

To tackle this, we propose L3C-Stereo, a multi-scale lossless compression model consisting of two main modules: the warping module and the probability estimation module.

Autonomous Driving

Adaptive unsupervised learning with enhanced feature representation for intra-tumor partitioning and survival prediction for glioblastoma

no code implementations21 Aug 2021 YiFan Li, Chao Li, Yiran Wei, Stephen Price, Carola-Bibiane Schönlieb, Xi Chen

In this paper, we propose an adaptive unsupervised learning approach for efficient MRI intra-tumor partitioning and glioblastoma survival prediction.

Survival Prediction

Semi-supervised classification of radiology images with NoTeacher: A Teacher that is not Mean

no code implementations10 Aug 2021 Balagopal Unnikrishnan, Cuong Nguyen, Shafa Balaram, Chao Li, Chuan Sheng Foo, Pavitra Krishnaswamy

Specifically, we describe adaptations for scenarios with 2D and 3D inputs, uni and multi-label classification, and class distribution mismatch between labeled and unlabeled portions of the training data.

Classification Image Classification +1

End-to-End User Behavior Retrieval in Click-Through RatePrediction Model

1 code implementation10 Aug 2021 Qiwei Chen, Changhua Pei, Shanshan Lv, Chao Li, Junfeng Ge, Wenwu Ou

Recently, researchers have found that the performance of CTR model can be improved greatly by taking user behavior sequence into consideration, especially long-term user behavior sequence.

Click-Through Rate Prediction Recommendation Systems +1

Integrating Large Circular Kernels into CNNs through Neural Architecture Search

1 code implementation6 Jul 2021 Kun He, Chao Li, Yixiao Yang, Gao Huang, John E. Hopcroft

We first propose a simple yet efficient implementation of the convolution using circular kernels, and empirically show the significant advantages of large circular kernels over the counterpart square kernels.

Data Augmentation Neural Architecture Search

Optimizing the Numbers of Queries and Replies in Federated Learning with Differential Privacy

1 code implementation5 Jul 2021 Yipeng Zhou, Xuezheng Liu, Yao Fu, Di wu, Chao Li, Shui Yu

In this work, we study a crucial question which has been vastly overlooked by existing works: what are the optimal numbers of queries and replies in FL with DP so that the final model accuracy is maximized.

Federated Learning

Self-Supervised Nonlinear Transform-Based Tensor Nuclear Norm for Multi-Dimensional Image Recovery

no code implementations29 May 2021 Yi-Si Luo, Xi-Le Zhao, Tai-Xiang Jiang, Yi Chang, Michael K. Ng, Chao Li

Recently, transform-based tensor nuclear norm minimization methods are considered to capture low-rank tensor structures to recover third-order tensors in multi-dimensional image processing applications.

Graph-Constrained Structure Search for Tensor Network Representation

no code implementations NeurIPS 2021 Chao Li, Junhua Zeng, Zerui Tao, Qibin Zhao

Recent works paid effort on the structure search issue for tensor network (TN) representation, of which the aim is to select the optimal network for TN contraction to fit a tensor.

Egocentric Activity Recognition and Localization on a 3D Map

no code implementations20 May 2021 Miao Liu, Lingni Ma, Kiran Somasundaram, Yin Li, Kristen Grauman, James M. Rehg, Chao Li

Given a video captured from a first person perspective and the environment context of where the video is recorded, can we recognize what the person is doing and identify where the action occurs in the 3D space?

Action Localization Action Recognition +2

Motion Artifact Reduction in Quantitative Susceptibility Mapping using Deep Neural Network

no code implementations4 May 2021 Chao Li, Hang Zhang, Jinwei Zhang, Pascal Spincemaille, Thanh D. Nguyen, Yi Wang

An approach to reduce motion artifacts in Quantitative Susceptibility Mapping using deep learning is proposed.

Image Inpainting by End-to-End Cascaded Refinement with Mask Awareness

1 code implementation28 Apr 2021 Manyu Zhu, Dongliang He, Xin Li, Chao Li, Fu Li, Xiao Liu, Errui Ding, Zhaoxiang Zhang

Inpainting arbitrary missing regions is challenging because learning valid features for various masked regions is nontrivial.

Image Inpainting

BrainNetGAN: Data augmentation of brain connectivity using generative adversarial network for dementia classification

no code implementations10 Mar 2021 Chao Li, Yiran Wei, Xi Chen, Carola-Bibiane Schonlieb

The proposed BrainNetGAN is a generative adversarial network variant to augment the brain structural connectivity matrices for binary dementia classification tasks.

Classification Data Augmentation +2

Temporal Feature Fusion with Sampling Pattern Optimization for Multi-echo Gradient Echo Acquisition and Image Reconstruction

no code implementations10 Mar 2021 Jinwei Zhang, Hang Zhang, Chao Li, Pascal Spincemaille, Mert Sabuncu, Thanh D. Nguyen, Yi Wang

Quantitative imaging in MRI usually involves acquisition and reconstruction of a series of images at multi-echo time points, which possibly requires more scan time and specific reconstruction technique compared to conventional qualitative imaging.

Image Reconstruction

NeRD: Neural Representation of Distribution for Medical Image Segmentation

no code implementations6 Mar 2021 Hang Zhang, Rongguang Wang, Jinwei Zhang, Chao Li, Gufeng Yang, Pascal Spincemaille, Thanh Nguyen, Yi Wang

We introduce Neural Representation of Distribution (NeRD) technique, a module for convolutional neural networks (CNNs) that can estimate the feature distribution by optimizing an underlying function mapping image coordinates to the feature distribution.

Image Segmentation Lesion Segmentation +1

On the Memory Mechanism of Tensor-Power Recurrent Models

1 code implementation2 Mar 2021 Hejia Qiu, Chao Li, Ying Weng, Zhun Sun, Xingyu He, Qibin Zhao

Tensor-power (TP) recurrent model is a family of non-linear dynamical systems, of which the recurrence relation consists of a p-fold (a. k. a., degree-p) tensor product.

Blockchain-based Transparency Framework for Privacy Preserving Third-party Services

1 code implementation2 Feb 2021 Runhua Xu, Chao Li, James Joshi

We also formally show the security guarantee provided by TAB, and analyze the privacy guarantee and trustworthiness it provides.

Cryptography and Security Networking and Internet Architecture

Measuring Decentralization in Bitcoin and Ethereum using Multiple Metrics and Granularities

2 code implementations26 Jan 2021 Qinwei Lin, Chao Li, Xifeng Zhao, Xianhai Chen

Decentralization has been widely acknowledged as a core virtue of blockchains.

Cryptography and Security Databases

On the Practicality of Differential Privacy in Federated Learning by Tuning Iteration Times

no code implementations11 Jan 2021 Yao Fu, Yipeng Zhou, Di wu, Shui Yu, Yonggang Wen, Chao Li

Then, we theoretically derive: 1) the conditions for the DP based FedAvg to converge as the number of global iterations (GI) approaches infinity; 2) the method to set the number of local iterations (LI) to minimize the negative influence of DP noises.

Federated Learning

Protecting Big Data Privacy Using Randomized Tensor Network Decomposition and Dispersed Tensor Computation

no code implementations4 Jan 2021 Jenn-Bing Ong, Wee-Keong Ng, Ivan Tjuawinata, Chao Li, Jielin Yang, Sai None Myne, Huaxiong Wang, Kwok-Yan Lam, C. -C. Jay Kuo

The distributed tensor representations are dispersed on multiple clouds / fogs or servers / devices with metadata privacy, this provides both distributed trust and management to seamlessly secure big data storage, communication, sharing, and computation.

Dimensionality Reduction Management +1

Adversarial Attack on Deep Cross-Modal Hamming Retrieval

no code implementations ICCV 2021 Chao Li, Shangqian Gao, Cheng Deng, Wei Liu, Heng Huang

Specifically, given a target model, we first construct its substitute model to exploit cross-modal correlations within hamming space, with which we create adversarial examples by limitedly querying from a target model.

Adversarial Attack Cross-Modal Retrieval +2

Improving BERT with Syntax-aware Local Attention

1 code implementation Findings (ACL) 2021 Zhongli Li, Qingyu Zhou, Chao Li, Ke Xu, Yunbo Cao

Pre-trained Transformer-based neural language models, such as BERT, have achieved remarkable results on varieties of NLP tasks.

Machine Translation Pretrained Language Models +3

NN-EMD: Efficiently Training Neural Networks using Encrypted Multi-Sourced Datasets

1 code implementation18 Dec 2020 Runhua Xu, James Joshi, Chao Li

We propose a novel framework, NN-EMD, to train DNN over multiple encrypted datasets collected from multiple sources.

BIG-bench Machine Learning Privacy Preserving

Bayesian optimization assisted unsupervised learning for efficient intra-tumor partitioning in MRI and survival prediction for glioblastoma patients

no code implementations5 Dec 2020 YiFan Li, Chao Li, Stephen Price, Carola-Bibiane Schönlieb, Xi Chen

Although successful in tumor sub-region segmentation and survival prediction, radiomics based on machine learning algorithms, is challenged by its robustness, due to the vague intermediate process and track changes.

BIG-bench Machine Learning Survival Prediction

How Far Does BERT Look At: Distance-based Clustering and Analysis of BERT's Attention

no code implementations COLING 2020 Yue Guan, Jingwen Leng, Chao Li, Quan Chen, Minyi Guo

Recent research on the multi-head attention mechanism, especially that in pre-trained models such as BERT, has shown us heuristics and clues in analyzing various aspects of the mechanism.

Channel Pruning via Multi-Criteria based on Weight Dependency

no code implementations6 Nov 2020 Yangchun Yan, Rongzuo Guo, Chao Li, Kang Yang, Yongjun Xu

However, these methods ignore a small part of weights in the next layer which disappears as the feature map is removed.

Image Classification

An Empirical-cum-Statistical Approach to Power-Performance Characterization of Concurrent GPU Kernels

no code implementations4 Nov 2020 Nilanjan Goswami, Amer Qouneh, Chao Li, Tao Li

Growing deployment of power and energy efficient throughput accelerators (GPU) in data centers demands enhancement of power-performance co-optimization capabilities of GPUs.

Distributed, Parallel, and Cluster Computing Hardware Architecture Graphics

How Far Does BERT Look At:Distance-based Clustering and Analysis of BERT$'$s Attention

no code implementations2 Nov 2020 Yue Guan, Jingwen Leng, Chao Li, Quan Chen, Minyi Guo

Recent research on the multi-head attention mechanism, especially that in pre-trained models such as BERT, has shown us heuristics and clues in analyzing various aspects of the mechanism.

Non-local Meets Global: An Iterative Paradigm for Hyperspectral Image Restoration

1 code implementation24 Oct 2020 wei he, Quanming Yao, Chao Li, Naoto Yokoya, Qibin Zhao, Hongyan zhang, Liangpei Zhang

Non-local low-rank tensor approximation has been developed as a state-of-the-art method for hyperspectral image (HSI) restoration, which includes the tasks of denoising, compressed HSI reconstruction and inpainting.

Denoising Image Restoration

Architectural Implications of Graph Neural Networks

no code implementations2 Sep 2020 Zhihui Zhang, Jingwen Leng, Lingxiao Ma, Youshan Miao, Chao Li, Minyi Guo

Graph neural networks (GNN) represent an emerging line of deep learning models that operate on graph structures.

Joint Generative Learning and Super-Resolution For Real-World Camera-Screen Degradation

no code implementations1 Aug 2020 Guanghao Yin, Shou-qian Sun, Chao Li, Xin Min

Firstly, the downsampling degradation GAN(DD-GAN) is trained to model the degradation and produces more various of LR images, which is validated to be efficient for data augmentation.

Data Augmentation Image Super-Resolution +1

Topology-Change-Aware Volumetric Fusion for Dynamic Scene Reconstruction

no code implementations ECCV 2020 Chao Li, Xiaohu Guo

In the classic volumetric fusion-based framework, a mesh is usually extracted from the TSDF volume as the canonical surface representation to help estimating deformation field.

PFGDF: Pruning Filter via Gaussian Distribution Feature for Deep Neural Networks Acceleration

no code implementations23 Jun 2020 Jianrong Xu, Boyu Diao, Bifeng Cui, Kang Yang, Chao Li, Yongjun Xu

Deep learning has achieved impressive results in many areas, but the deployment of edge intelligent devices is still very slow.

Model Compression

Balancing Efficiency and Flexibility for DNN Acceleration via Temporal GPU-Systolic Array Integration

no code implementations18 Feb 2020 Cong Guo, Yangjie Zhou, Jingwen Leng, Yuhao Zhu, Zidong Du, Quan Chen, Chao Li, Bin Yao, Minyi Guo

We propose Simultaneous Multi-mode Architecture (SMA), a novel architecture design and execution model that offers general-purpose programmability on DNN accelerators in order to accelerate end-to-end applications.

H-OWAN: Multi-distorted Image Restoration with Tensor 1x1 Convolution

no code implementations29 Jan 2020 Zihao Huang, Chao Li, Feng Duan, Qibin Zhao

It is a challenging task to restore images from their variants with combined distortions.

Image Restoration

Hyperspectral Super-Resolution via Coupled Tensor Ring Factorization

no code implementations6 Jan 2020 Wei He, Yong Chen, Naoto Yokoya, Chao Li, Qibin Zhao

In this paper, we propose a new model, named coupled tensor ring factorization (CTRF), for HSR.


Cross-Modal Learning with Adversarial Samples

1 code implementation NeurIPS 2019 Chao Li, Shangqian Gao, Cheng Deng, De Xie, Wei Liu

Extensive experiments on two cross-modal benchmark datasets show that the adversarial examples produced by our CMLA are efficient in fooling a target deep cross-modal hashing network.


Single Image Reflection Removal through Cascaded Refinement

2 code implementations CVPR 2020 Chao Li, Yixiao Yang, Kun He, Stephen Lin, John E. Hopcroft

IBCLN is a cascaded network that iteratively refines the estimates of transmission and reflection layers in a manner that they can boost the prediction quality to each other, and information across steps of the cascade is transferred using an LSTM.

Community Detection Reflection Removal

TruNet: Short Videos Generation from Long Videos via Story-Preserving Truncation

no code implementations14 Oct 2019 Fan Yang, Xiao Liu, Dongliang He, Chuang Gan, Jian Wang, Chao Li, Fu Li, Shilei Wen

In this work, we introduce a new problem, named as {\em story-preserving long video truncation}, that requires an algorithm to automatically truncate a long-duration video into multiple short and attractive sub-videos with each one containing an unbroken story.

Highlight Detection Video Summarization

Hierarchical hidden community detection for protein complex prediction

1 code implementation8 Oct 2019 Chao Li, Kun He, Guangshuai Liu, John E. Hopcroft

Results: We propose a method called HirHide (Hierarchical Hidden Community Detection), which can be combined with traditional community detection methods to enable them to discover hierarchical hidden communities.

Molecular Networks

Image Inpainting with Learnable Bidirectional Attention Maps

1 code implementation ICCV 2019 Chaohao Xie, Shaohui Liu, Chao Li, Ming-Ming Cheng, WangMeng Zuo, Xiao Liu, Shilei Wen, Errui Ding

Most convolutional network (CNN)-based inpainting methods adopt standard convolution to indistinguishably treat valid pixels and holes, making them limited in handling irregular holes and more likely to generate inpainting results with color discrepancy and blurriness.

Image Inpainting

Deep Concept-wise Temporal Convolutional Networks for Action Localization

2 code implementations26 Aug 2019 Xin Li, Tianwei Lin, Xiao Liu, Chuang Gan, WangMeng Zuo, Chao Li, Xiang Long, Dongliang He, Fu Li, Shilei Wen

In this paper, we empirically find that stacking more conventional temporal convolution layers actually deteriorates action classification performance, possibly ascribing to that all channels of 1D feature map, which generally are highly abstract and can be regarded as latent concepts, are excessively recombined in temporal convolution.

Action Classification Action Localization

Gated Convolutional Networks with Hybrid Connectivity for Image Classification

1 code implementation26 Aug 2019 Chuanguang Yang, Zhulin An, Hui Zhu, Xiaolong Hu, Kun Zhang, Kaiqiang Xu, Chao Li, Yongjun Xu

We propose a simple yet effective method to reduce the redundancy of DenseNet by substantially decreasing the number of stacked modules by replacing the original bottleneck by our SMG module, which is augmented by local residual.

Adversarial Defense Classification +2

User independent Emotion Recognition with Residual Signal-Image Network

no code implementations10 Aug 2019 Guanghao Yin, Shou-qian Sun, HUI ZHANG, Dian Yu, Chao Li, Ke-jun Zhang, Ning Zou

To the best of author's knowledge, our method is the first attempt to classify large scale subject-independent emotion with 7962 pieces of EDA signals from 457 subjects.

Emotion Recognition

Best Practices for Learning Domain-Specific Cross-Lingual Embeddings

no code implementations WS 2019 Lena Shakurova, Beata Nyari, Chao Li, Mihai Rotaru

Cross-lingual embeddings aim to represent words in multiple languages in a shared vector space by capturing semantic similarities across languages.

Transfer Learning

Multi-Objective Pruning for CNNs Using Genetic Algorithm

no code implementations2 Jun 2019 Chuanguang Yang, Zhulin An, Chao Li, Boyu Diao, Yongjun Xu

In this work, we propose a heuristic genetic algorithm (GA) for pruning convolutional neural networks (CNNs) according to the multi-objective trade-off among error, computation and sparsity.

Guaranteed Matrix Completion Under Multiple Linear Transformations

no code implementations CVPR 2019 Chao Li, Wei He, Longhao Yuan, Zhun Sun, Qibin Zhao

Low-rank matrix completion (LRMC) is a classical model in both computer vision (CV) and machine learning, and has been successfully applied to various real applications.

Image Inpainting Low-Rank Matrix Completion

Collaborative Spatiotemporal Feature Learning for Video Action Recognition

1 code implementation CVPR 2019 Chao Li, Qiaoyong Zhong, Di Xie, Shiliang Pu

By sharing the convolution kernels of different views, spatial and temporal features are collaboratively learned and thus benefit from each other.

Action Classification Action Recognition +3

Adapting Image Super-Resolution State-of-the-arts and Learning Multi-model Ensemble for Video Super-Resolution

no code implementations7 May 2019 Chao Li, Dongliang He, Xiao Liu, Yukang Ding, Shilei Wen

Recently, image super-resolution has been widely studied and achieved significant progress by leveraging the power of deep convolutional neural networks.

Image Super-Resolution Video Super-Resolution

POG: Personalized Outfit Generation for Fashion Recommendation at Alibaba iFashion

1 code implementation6 May 2019 Wen Chen, Pipei Huang, Jiaming Xu, Xin Guo, Cheng Guo, Fei Sun, Chao Li, Andreas Pfadler, Huan Zhao, Binqiang Zhao

In particular, there exist two requirements for fashion outfit recommendation: the Compatibility of the generated fashion outfits, and the Personalization in the recommendation process.

Multi-Interest Network with Dynamic Routing for Recommendation at Tmall

3 code implementations17 Apr 2019 Chao Li, Zhiyuan Liu, Mengmeng Wu, Yuchi Xu, Pipei Huang, Huan Zhao, Guoliang Kang, Qiwei Chen, Wei Li, Dik Lun Lee

Industrial recommender systems usually consist of the matching stage and the ranking stage, in order to handle the billion-scale of users and items.

Recommendation Systems

Adversarial Defense Through Network Profiling Based Path Extraction

no code implementations CVPR 2019 Yuxian Qiu, Jingwen Leng, Cong Guo, Quan Chen, Chao Li, Minyi Guo, Yuhao Zhu

Recently, researchers have started decomposing deep neural network models according to their semantics or functions.

Adversarial Defense

Shared Predictive Cross-Modal Deep Quantization

no code implementations16 Apr 2019 Erkun Yang, Cheng Deng, Chao Li, Wei Liu, Jie Li, DaCheng Tao

In this paper, we propose a deep quantization approach, which is among the early attempts of leveraging deep neural networks into quantization-based cross-modal similarity search.


CryptoNN: Training Neural Networks over Encrypted Data

1 code implementation15 Apr 2019 Runhua Xu, James B. D. Joshi, Chao Li

To tackle the above issue, we propose a CryptoNN framework that supports training a neural network model over encrypted data by using the emerging functional encryption scheme instead of SMC or HE.

BIG-bench Machine Learning Privacy Preserving

Active Transfer Learning Network: A Unified Deep Joint Spectral-Spatial Feature Learning Model For Hyperspectral Image Classification

no code implementations4 Apr 2019 Cheng Deng, Yumeng Xue, Xianglong Liu, Chao Li, DaCheng Tao

The advantages of our proposed method are threefold: 1) the network can be effectively trained using only limited labeled samples with the help of novel active learning strategies; 2) the network is flexible and scalable enough to function across various transfer situations, including cross-dataset and intra-image; 3) the learned deep joint spectral-spatial feature representation is more generic and robust than many joint spectral-spatial feature representation.

Active Learning General Classification +2

Tensor-Ring Nuclear Norm Minimization and Application for Visual Data Completion

no code implementations21 Mar 2019 Jinshi Yu, Chao Li, Qibin Zhao, Guoxu Zhou

Tensor ring (TR) decomposition has been successfully used to obtain the state-of-the-art performance in the visual data completion problem.

Predicting Research Trends From Arxiv

1 code implementation7 Mar 2019 Steffen Eger, Chao Li, Florian Netzer, Iryna Gurevych

By extrapolation, we predict that these topics will remain lead problems/approaches in their fields in the short- and mid-term.

reinforcement-learning reinforcement Learning +1

Coupled CycleGAN: Unsupervised Hashing Network for Cross-Modal Retrieval

no code implementations6 Mar 2019 Chao Li, Cheng Deng, Lei Wang, De Xie, Xianglong Liu

In recent years, hashing has attracted more and more attention owing to its superior capacity of low storage cost and high query efficiency in large-scale cross-modal retrieval.

Cross-Modal Retrieval Retrieval

Collaborative Spatio-temporal Feature Learning for Video Action Recognition

1 code implementation4 Mar 2019 Chao Li, Qiaoyong Zhong, Di Xie, ShiLiang Pu

By sharing the convolution kernels of different views, spatial and temporal features are collaboratively learned and thus benefit from each other.

Action Recognition Action Recognition In Videos +2

Anomaly Detection for an E-commerce Pricing System

no code implementations25 Feb 2019 Jagdish Ramakrishnan, Elham Shaabani, Chao Li, Mátyás A. Sustik

Our system detects anomalies both in batch and real-time streaming settings, and the items flagged are reviewed and actioned based on priority and business impact.

Model Selection Outlier Detection +1

Non-local Meets Global: An Integrated Paradigm for Hyperspectral Denoising

2 code implementations CVPR 2019 Wei He, Quanming Yao, Chao Li, Naoto Yokoya, Qibin Zhao

This is done by first learning a low-dimensional projection and the related reduced image from the noisy HSI.


Chat More If You Like: Dynamic Cue Words Planning to Flow Longer Conversations

no code implementations19 Nov 2018 Lili Yao, Ruijian Xu, Chao Li, Dongyan Zhao, Rui Yan

To build an open-domain multi-turn conversation system is one of the most interesting and challenging tasks in Artificial Intelligence.

Low-Rank Embedding of Kernels in Convolutional Neural Networks under Random Shuffling

no code implementations31 Oct 2018 Chao Li, Zhun Sun, Jinshi Yu, Ming Hou, Qibin Zhao

We demonstrate this by compressing the convolutional layers via randomly-shuffled tensor decomposition (RsTD) for a standard classification task using CIFAR-10.

General Classification Tensor Decomposition

Effective Path: Know the Unknowns of Neural Network

no code implementations27 Sep 2018 Yuxian Qiu, Jingwen Leng, Yuhao Zhu, Quan Chen, Chao Li, Minyi Guo

Despite their enormous success, there is still no solid understanding of deep neural network’s working mechanism.

Tensor Ring Decomposition with Rank Minimization on Latent Space: An Efficient Approach for Tensor Completion

no code implementations7 Sep 2018 Longhao Yuan, Chao Li, Danilo Mandic, Jianting Cao, Qibin Zhao

In this paper, by exploiting the low-rank structure of the TR latent space, we propose a novel tensor completion method which is robust to model selection.

Model Selection Tensor Decomposition

ArticulatedFusion: Real-time Reconstruction of Motion, Geometry and Segmentation Using a Single Depth Camera

no code implementations ECCV 2018 Chao Li, Zheheng Zhao, Xiaohu Guo

This paper proposes a real-time dynamic scene reconstruction method capable of reproducing the motion, geometry, and segmentation simultaneously given live depth stream from a single RGB-D camera.

Rank Minimization on Tensor Ring: A New Paradigm in Scalable Tensor Decomposition and Completion

no code implementations22 May 2018 Longhao Yuan, Chao Li, Danilo Mandic, Jianting Cao, Qibin Zhao

In low-rank tensor completion tasks, due to the underlying multiple large-scale singular value decomposition (SVD) operations and rank selection problem of the traditional methods, they suffer from high computational cost and high sensitivity of model complexity.

Tensor Decomposition

Beyond Unfolding: Exact Recovery of Latent Convex Tensor Decomposition under Reshuffling

no code implementations22 May 2018 Chao Li, Mohammad Emtiyaz Khan, Zhun Sun, Gang Niu, Bo Han, Shengli Xie, Qibin Zhao

Exact recovery of tensor decomposition (TD) methods is a desirable property in both unsupervised learning and scientific data analysis.

Image Steganography Tensor Decomposition

High Performance Visual Tracking with Circular and Structural Operators

no code implementations23 Apr 2018 Peng Gao, Yipeng Ma, Ke Song, Chao Li, Fei Wang, Liyi Xiao, Yan Zhang

Based on the proposed circular and structural operators, a set of primal confidence score maps can be obtained by circular correlating feature maps with their corresponding structural correlation filters.

Visual Tracking

A Complementary Tracking Model with Multiple Features

no code implementations20 Apr 2018 Peng Gao, Yipeng Ma, Chao Li, Ke Song, Fei Wang, Liyi Xiao

Discriminative Correlation Filters based tracking algorithms exploiting conventional handcrafted features have achieved impressive results both in terms of accuracy and robustness.

Visual Tracking

Large Margin Structured Convolution Operator for Thermal Infrared Object Tracking

no code implementations19 Apr 2018 Peng Gao, Yipeng Ma, Ke Song, Chao Li, Fei Wang, Liyi Xiao

To the best of our knowledge, we are the first to incorporate the advantages of DCF and SOSVM for TIR object tracking.

Thermal Infrared Object Tracking

Self-Supervised Adversarial Hashing Networks for Cross-Modal Retrieval

1 code implementation CVPR 2018 Chao Li, Cheng Deng, Ning li, Wei Liu, Xinbo Gao, DaCheng Tao

In addition, we harness a self-supervised semantic network to discover high-level semantic information in the form of multi-label annotations.

Cross-Modal Retrieval Retrieval

Model Trees for Identifying Exceptional Players in the NHL Draft

1 code implementation23 Feb 2018 Oliver Schulte, Yejia Liu, Chao Li

Successful previous approaches have built a predictive model based on player features, or derived performance predictions from the observed performance of comparable players in a cohort.

Combining Linear Non-Gaussian Acyclic Model with Logistic Regression Model for Estimating Causal Structure from Mixed Continuous and Discrete Data

no code implementations16 Feb 2018 Chao Li, Shohei Shimizu

Most existing causal discovery methods either ignore the discrete data and apply a continuous-valued algorithm or discretize all the continuous data and then apply a discrete Bayesian network approach.

Causal Discovery Model Selection

Generative Adversarial Positive-Unlabelled Learning

no code implementations21 Nov 2017 Ming Hou, Brahim Chaib-Draa, Chao Li, Qibin Zhao

However, given limited P data, the conventional PU models tend to suffer from overfitting when adapted to very flexible deep neural networks.

AutoEncoder Inspired Unsupervised Feature Selection

1 code implementation23 Oct 2017 Kai Han, Yunhe Wang, Chao Zhang, Chao Li, Chao Xu

High-dimensional data in many areas such as computer vision and machine learning tasks brings in computational and analytical difficulty.

BIG-bench Machine Learning

Leveraging Weak Semantic Relevance for Complex Video Event Classification

no code implementations ICCV 2017 Chao Li, Jiewei Cao, Zi Huang, Lei Zhu, Heng Tao Shen

In this paper, we propose a novel approach to automatically maximize the utility of weak semantic annotations (formalized as the semantic relevance of video shots to the target event) to facilitate video event classification.

Classification General Classification

Deep Speaker: an End-to-End Neural Speaker Embedding System

15 code implementations5 May 2017 Chao Li, Xiaokong Ma, Bing Jiang, Xiangang Li, Xuewei Zhang, Xiao Liu, Ying Cao, Ajay Kannan, Zhenyao Zhu

We present Deep Speaker, a neural speaker embedding system that maps utterances to a hypersphere where speaker similarity is measured by cosine similarity.

Speaker Identification Speaker Recognition

Skeleton-based Action Recognition with Convolutional Neural Networks

1 code implementation25 Apr 2017 Chao Li, Qiaoyong Zhong, Di Xie, ShiLiang Pu

Current state-of-the-art approaches to skeleton-based action recognition are mostly based on recurrent neural networks (RNN).

Action Recognition General Classification +1

Optimizing Memory Efficiency for Deep Convolutional Neural Networks on GPUs

no code implementations12 Oct 2016 Chao Li, Yi Yang, Min Feng, Srimat Chakradhar, Huiyang Zhou

Leveraging large data sets, deep Convolutional Neural Networks (CNNs) achieve state-of-the-art recognition accuracy.

Co-Saliency Detection via Looking Deep and Wide

no code implementations CVPR 2015 Dingwen Zhang, Junwei Han, Chao Li, Jingdong Wang

In the proposed framework, the wide and deep information are explored for the object proposal windows extracted in each image, and the co-saliency scores are calculated by integrating the intra-image contrast and intra group consistency via a principled Bayesian formulation.

Co-Salient Object Detection Image Retrieval +1

Canonical Polyadic Decomposition with Auxiliary Information for Brain Computer Interface

no code implementations23 Oct 2014 Junhua Li, Chao Li, Andrzej Cichocki

Unlike vector-based methods that destroy data structure, Canonical Polyadic Decomposition (CPD) aims to process physiological signals in the form of multi-way array, which considers relationships between dimensions and preserves structure information contained by the physiological signal.

Classification EEG +1

Multi-tensor Completion for Estimating Missing Values in Video Data

no code implementations1 Sep 2014 Chao Li, Lili Guo, Andrzej Cichocki

Thus one question raised whether such the relationship can improve the performance of data completion or not?

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