Search Results for author: Feng Yan

Found 41 papers, 19 papers with code

A New Method in Facial Registration in Clinics Based on Structure Light Images

no code implementations23 May 2024 Pengfei Li, Ziyue Ma, Hong Wang, Juan Deng, Yan Wang, Zhenyu Xu, Feng Yan, Wenjun Tu, Hong Sha

To abundant traditional image methods with depth information, a method in registering with depth images and traditional clinical images was investigated.

Face Recognition

Communication-Efficient Training Workload Balancing for Decentralized Multi-Agent Learning

1 code implementation1 May 2024 Seyed Mahmoud Sajjadi Mohammadabadi, Lei Yang, Feng Yan, Junshan Zhang

To minimize training time in heterogeneous environments, we present a Communication-Efficient Training Workload Balancing for Decentralized Multi-Agent Learning (ComDML), which balances the workload among agents through a decentralized approach.

CSCO: Connectivity Search of Convolutional Operators

no code implementations26 Apr 2024 Tunhou Zhang, Shiyu Li, Hsin-Pai Cheng, Feng Yan, Hai Li, Yiran Chen

In this paper, we propose CSCO, a novel paradigm that fabricates effective connectivity of convolutional operators with minimal utilization of existing design motifs and further utilizes the discovered wiring to construct high-performing ConvNets.

Data Augmentation Neural Architecture Search

Peeking Behind the Curtains of Residual Learning

no code implementations13 Feb 2024 Tunhou Zhang, Feng Yan, Hai Li, Yiran Chen

The utilization of residual learning has become widespread in deep and scalable neural nets.

Joint Attention-Guided Feature Fusion Network for Saliency Detection of Surface Defects

no code implementations5 Feb 2024 Xiaoheng Jiang, Feng Yan, Yang Lu, Ke Wang, Shuai Guo, Tianzhu Zhang, Yanwei Pang, Jianwei Niu, Mingliang Xu

To address these issues, we propose a joint attention-guided feature fusion network (JAFFNet) for saliency detection of surface defects based on the encoder-decoder network.

Defect Detection Saliency Detection

Grounded SAM: Assembling Open-World Models for Diverse Visual Tasks

1 code implementation25 Jan 2024 Tianhe Ren, Shilong Liu, Ailing Zeng, Jing Lin, Kunchang Li, He Cao, Jiayu Chen, Xinyu Huang, Yukang Chen, Feng Yan, Zhaoyang Zeng, Hao Zhang, Feng Li, Jie Yang, Hongyang Li, Qing Jiang, Lei Zhang

We introduce Grounded SAM, which uses Grounding DINO as an open-set object detector to combine with the segment anything model (SAM).

Segmentation

Speed Up Federated Learning in Heterogeneous Environment: A Dynamic Tiering Approach

1 code implementation9 Dec 2023 Seyed Mahmoud Sajjadi Mohammadabadi, Syed Zawad, Feng Yan, Lei Yang

The dynamic tier scheduler assigns clients to suitable tiers to minimize the overall training time in each round.

 Ranked #1 on Image Classification on CIFAR-10 (training time (s) metric)

Federated Learning Image Classification

DistDNAS: Search Efficient Feature Interactions within 2 Hours

no code implementations1 Nov 2023 Tunhou Zhang, Wei Wen, Igor Fedorov, Xi Liu, Buyun Zhang, Fangqiu Han, Wen-Yen Chen, Yiping Han, Feng Yan, Hai Li, Yiran Chen

To optimize search efficiency, DistDNAS distributes the search and aggregates the choice of optimal interaction modules on varying data dates, achieving over 25x speed-up and reducing search cost from 2 days to 2 hours.

Recommendation Systems

Farthest Greedy Path Sampling for Two-shot Recommender Search

no code implementations31 Oct 2023 Yufan Cao, Tunhou Zhang, Wei Wen, Feng Yan, Hai Li, Yiran Chen

FGPS enhances path diversity to facilitate more comprehensive supernet exploration, while emphasizing path quality to ensure the effective identification and utilization of promising architectures.

Click-Through Rate Prediction Neural Architecture Search

CINFormer: Transformer network with multi-stage CNN feature injection for surface defect segmentation

no code implementations22 Sep 2023 Xiaoheng Jiang, Kaiyi Guo, Yang Lu, Feng Yan, Hao liu, Jiale Cao, Mingliang Xu, DaCheng Tao

To address these issues, we propose a transformer network with multi-stage CNN (Convolutional Neural Network) feature injection for surface defect segmentation, which is a UNet-like structure named CINFormer.

Defect Detection

Global Context Aggregation Network for Lightweight Saliency Detection of Surface Defects

no code implementations22 Sep 2023 Feng Yan, Xiaoheng Jiang, Yang Lu, Lisha Cui, Shupan Li, Jiale Cao, Mingliang Xu, DaCheng Tao

To this end, we develop a Global Context Aggregation Network (GCANet) for lightweight saliency detection of surface defects on the encoder-decoder structure.

Decoder Defect Detection +1

SoccerNet 2023 Challenges Results

2 code implementations12 Sep 2023 Anthony Cioppa, Silvio Giancola, Vladimir Somers, Floriane Magera, Xin Zhou, Hassan Mkhallati, Adrien Deliège, Jan Held, Carlos Hinojosa, Amir M. Mansourian, Pierre Miralles, Olivier Barnich, Christophe De Vleeschouwer, Alexandre Alahi, Bernard Ghanem, Marc Van Droogenbroeck, Abdullah Kamal, Adrien Maglo, Albert Clapés, Amr Abdelaziz, Artur Xarles, Astrid Orcesi, Atom Scott, Bin Liu, Byoungkwon Lim, Chen Chen, Fabian Deuser, Feng Yan, Fufu Yu, Gal Shitrit, Guanshuo Wang, Gyusik Choi, Hankyul Kim, Hao Guo, Hasby Fahrudin, Hidenari Koguchi, Håkan Ardö, Ibrahim Salah, Ido Yerushalmy, Iftikar Muhammad, Ikuma Uchida, Ishay Be'ery, Jaonary Rabarisoa, Jeongae Lee, Jiajun Fu, Jianqin Yin, Jinghang Xu, Jongho Nang, Julien Denize, Junjie Li, Junpei Zhang, Juntae Kim, Kamil Synowiec, Kenji Kobayashi, Kexin Zhang, Konrad Habel, Kota Nakajima, Licheng Jiao, Lin Ma, Lizhi Wang, Luping Wang, Menglong Li, Mengying Zhou, Mohamed Nasr, Mohamed Abdelwahed, Mykola Liashuha, Nikolay Falaleev, Norbert Oswald, Qiong Jia, Quoc-Cuong Pham, Ran Song, Romain Hérault, Rui Peng, Ruilong Chen, Ruixuan Liu, Ruslan Baikulov, Ryuto Fukushima, Sergio Escalera, Seungcheon Lee, Shimin Chen, Shouhong Ding, Taiga Someya, Thomas B. Moeslund, Tianjiao Li, Wei Shen, Wei zhang, Wei Li, Wei Dai, Weixin Luo, Wending Zhao, Wenjie Zhang, Xinquan Yang, Yanbiao Ma, Yeeun Joo, Yingsen Zeng, Yiyang Gan, Yongqiang Zhu, Yujie Zhong, Zheng Ruan, Zhiheng Li, Zhijian Huang, Ziyu Meng

More information on the tasks, challenges, and leaderboards are available on https://www. soccer-net. org.

Action Spotting Camera Calibration +3

ZeRO++: Extremely Efficient Collective Communication for Giant Model Training

1 code implementation16 Jun 2023 Guanhua Wang, Heyang Qin, Sam Ade Jacobs, Connor Holmes, Samyam Rajbhandari, Olatunji Ruwase, Feng Yan, Lei Yang, Yuxiong He

Zero Redundancy Optimizer (ZeRO) has been used to train a wide range of large language models on massive GPUs clusters due to its ease of use, efficiency, and good scalability.

Quantization

Bridging the Gap Between End-to-end and Non-End-to-end Multi-Object Tracking

2 code implementations22 May 2023 Feng Yan, Weixin Luo, Yujie Zhong, Yiyang Gan, Lin Ma

Existing end-to-end Multi-Object Tracking (e2e-MOT) methods have not surpassed non-end-to-end tracking-by-detection methods.

Multi-Object Tracking Video Object Tracking

Multiple Object Tracking Challenge Technical Report for Team MT_IoT

1 code implementation7 Dec 2022 Feng Yan, Zhiheng Li, Weixin Luo, Zequn Jie, Fan Liang, Xiaolin Wei, Lin Ma

This is a brief technical report of our proposed method for Multiple-Object Tracking (MOT) Challenge in Complex Environments.

Ranked #8 on Multi-Object Tracking on DanceTrack (using extra training data)

Human Detection Multi-Object Tracking +2

PIDS: Joint Point Interaction-Dimension Search for 3D Point Cloud

1 code implementation28 Nov 2022 Tunhou Zhang, Mingyuan Ma, Feng Yan, Hai Li, Yiran Chen

In this work, we establish PIDS, a novel paradigm to jointly explore point interactions and point dimensions to serve semantic segmentation on point cloud data.

Neural Architecture Search Robust 3D Semantic Segmentation +1

Energy Efficiency Optimization of Intelligent Reflective Surface-assisted Terahertz-RSMA System

no code implementations21 Nov 2022 Xiaoyu Chen, Feng Yan, Menghan Hu, Zihuai Lin

This paper examines the energy efficiency optimization problem of intelligent reflective surface (IRS)-assisted multi-user rate division multiple access (RSMA) downlink systems under terahertz propagation.

SoccerNet 2022 Challenges Results

7 code implementations5 Oct 2022 Silvio Giancola, Anthony Cioppa, Adrien Deliège, Floriane Magera, Vladimir Somers, Le Kang, Xin Zhou, Olivier Barnich, Christophe De Vleeschouwer, Alexandre Alahi, Bernard Ghanem, Marc Van Droogenbroeck, Abdulrahman Darwish, Adrien Maglo, Albert Clapés, Andreas Luyts, Andrei Boiarov, Artur Xarles, Astrid Orcesi, Avijit Shah, Baoyu Fan, Bharath Comandur, Chen Chen, Chen Zhang, Chen Zhao, Chengzhi Lin, Cheuk-Yiu Chan, Chun Chuen Hui, Dengjie Li, Fan Yang, Fan Liang, Fang Da, Feng Yan, Fufu Yu, Guanshuo Wang, H. Anthony Chan, He Zhu, Hongwei Kan, Jiaming Chu, Jianming Hu, Jianyang Gu, Jin Chen, João V. B. Soares, Jonas Theiner, Jorge De Corte, José Henrique Brito, Jun Zhang, Junjie Li, Junwei Liang, Leqi Shen, Lin Ma, Lingchi Chen, Miguel Santos Marques, Mike Azatov, Nikita Kasatkin, Ning Wang, Qiong Jia, Quoc Cuong Pham, Ralph Ewerth, Ran Song, RenGang Li, Rikke Gade, Ruben Debien, Runze Zhang, Sangrok Lee, Sergio Escalera, Shan Jiang, Shigeyuki Odashima, Shimin Chen, Shoichi Masui, Shouhong Ding, Sin-wai Chan, Siyu Chen, Tallal El-Shabrawy, Tao He, Thomas B. Moeslund, Wan-Chi Siu, Wei zhang, Wei Li, Xiangwei Wang, Xiao Tan, Xiaochuan Li, Xiaolin Wei, Xiaoqing Ye, Xing Liu, Xinying Wang, Yandong Guo, YaQian Zhao, Yi Yu, YingYing Li, Yue He, Yujie Zhong, Zhenhua Guo, Zhiheng Li

The SoccerNet 2022 challenges were the second annual video understanding challenges organized by the SoccerNet team.

Action Spotting Camera Calibration +3

BiFeat: Supercharge GNN Training via Graph Feature Quantization

1 code implementation29 Jul 2022 Yuxin Ma, Ping Gong, Jun Yi, Zhewei Yao, Cheng Li, Yuxiong He, Feng Yan

We identify the main accuracy impact factors in graph feature quantization and theoretically prove that BiFeat training converges to a network where the loss is within $\epsilon$ of the optimal loss of uncompressed network.

Quantization

NASRec: Weight Sharing Neural Architecture Search for Recommender Systems

2 code implementations14 Jul 2022 Tunhou Zhang, Dehua Cheng, Yuchen He, Zhengxing Chen, Xiaoliang Dai, Liang Xiong, Feng Yan, Hai Li, Yiran Chen, Wei Wen

To overcome the data multi-modality and architecture heterogeneity challenges in the recommendation domain, NASRec establishes a large supernet (i. e., search space) to search the full architectures.

Click-Through Rate Prediction Neural Architecture Search +1

SMLT: A Serverless Framework for Scalable and Adaptive Machine Learning Design and Training

no code implementations4 May 2022 Ahsan Ali, Syed Zawad, Paarijaat Aditya, Istemi Ekin Akkus, Ruichuan Chen, Feng Yan

In addition, by providing an end-to-end design, SMLT solves the intrinsic problems in serverless platforms such as the communication overhead, limited function execution duration, need for repeated initialization, and also provides explicit fault tolerance for ML training.

BIG-bench Machine Learning Management +1

SimiGrad: Fine-Grained Adaptive Batching for Large Scale Training using Gradient Similarity Measurement

1 code implementation NeurIPS 2021 Heyang Qin, Samyam Rajbhandari, Olatunji Ruwase, Feng Yan, Lei Yang, Yuxiong He

In this paper, we propose a fully automated and lightweight adaptive batching methodology to enable fine-grained batch size adaption (e. g., at a mini-batch level) that can achieve state-of-the-art performance with record breaking batch sizes.

Computational Efficiency

Demystifying Hyperparameter Optimization in Federated Learning

no code implementations29 Sep 2021 Syed Zawad, Jun Yi, Minjia Zhang, Cheng Li, Feng Yan, Yuxiong He

Such data heterogeneity and privacy requirements bring unique challenges for learning hyperparameter optimization as the training dynamics change across clients even within the same training round and they are difficult to measure due to privacy constraints.

Federated Learning Hyperparameter Optimization +1

Automated Mobile Attention KPConv Networks via A Wide & Deep Predictor

no code implementations29 Sep 2021 Tunhou Zhang, Mingyuan Ma, Feng Yan, Hai Li, Yiran Chen

MAKPConv employs a depthwise kernel to reduce resource consumption and re-calibrates the contribution of kernel points towards each neighbor point via Neighbor-Kernel attention to improve representation power.

3D Point Cloud Classification Feature Engineering +2

Citadel: Protecting Data Privacy and Model Confidentiality for Collaborative Learning with SGX

no code implementations4 May 2021 Chengliang Zhang, Junzhe Xia, Baichen Yang, Huancheng Puyang, Wei Wang, Ruichuan Chen, Istemi Ekin Akkus, Paarijaat Aditya, Feng Yan

This paper presents Citadel, a scalable collaborative ML system that protects the privacy of both data owner and model owner in untrusted infrastructures with the help of Intel SGX.

Federated Learning

The Age of Correlated Features in Supervised Learning based Forecasting

no code implementations27 Feb 2021 MD Kamran Chowdhury Shisher, Heyang Qin, Lei Yang, Feng Yan, Yin Sun

In these applications, a neural network is trained to predict a time-varying target (e. g., solar power), based on multiple correlated features (e. g., temperature, humidity, and cloud coverage).

Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning

no code implementations1 Feb 2021 Syed Zawad, Ahsan Ali, Pin-Yu Chen, Ali Anwar, Yi Zhou, Nathalie Baracaldo, Yuan Tian, Feng Yan

Data heterogeneity has been identified as one of the key features in federated learning but often overlooked in the lens of robustness to adversarial attacks.

Federated Learning

NASGEM: Neural Architecture Search via Graph Embedding Method

no code implementations8 Jul 2020 Hsin-Pai Cheng, Tunhou Zhang, Yixing Zhang, Shi-Yu Li, Feng Liang, Feng Yan, Meng Li, Vikas Chandra, Hai Li, Yiran Chen

To preserve graph correlation information in encoding, we propose NASGEM which stands for Neural Architecture Search via Graph Embedding Method.

Graph Embedding Graph Similarity +3

Learning Low-rank Deep Neural Networks via Singular Vector Orthogonality Regularization and Singular Value Sparsification

1 code implementation20 Apr 2020 Huanrui Yang, Minxue Tang, Wei Wen, Feng Yan, Daniel Hu, Ang Li, Hai Li, Yiran Chen

In this work, we propose SVD training, the first method to explicitly achieve low-rank DNNs during training without applying SVD on every step.

TiFL: A Tier-based Federated Learning System

no code implementations25 Jan 2020 Zheng Chai, Ahsan Ali, Syed Zawad, Stacey Truex, Ali Anwar, Nathalie Baracaldo, Yi Zhou, Heiko Ludwig, Feng Yan, Yue Cheng

To this end, we propose TiFL, a Tier-based Federated Learning System, which divides clients into tiers based on their training performance and selects clients from the same tier in each training round to mitigate the straggler problem caused by heterogeneity in resource and data quantity.

Federated Learning

AutoShrink: A Topology-aware NAS for Discovering Efficient Neural Architecture

1 code implementation21 Nov 2019 Tunhou Zhang, Hsin-Pai Cheng, Zhenwen Li, Feng Yan, Chengyu Huang, Hai Li, Yiran Chen

Specifically, both ShrinkCNN and ShrinkRNN are crafted within 1. 5 GPU hours, which is 7. 2x and 6. 7x faster than the crafting time of SOTA CNN and RNN models, respectively.

Image Classification Neural Architecture Search

EPNAS: Efficient Progressive Neural Architecture Search

no code implementations7 Jul 2019 Yanqi Zhou, Peng Wang, Sercan Arik, Haonan Yu, Syed Zawad, Feng Yan, Greg Diamos

In this paper, we propose Efficient Progressive Neural Architecture Search (EPNAS), a neural architecture search (NAS) that efficiently handles large search space through a novel progressive search policy with performance prediction based on REINFORCE~\cite{Williams. 1992. PG}.

Neural Architecture Search

SwiftNet: Using Graph Propagation as Meta-knowledge to Search Highly Representative Neural Architectures

1 code implementation19 Jun 2019 Hsin-Pai Cheng, Tunhou Zhang, Yukun Yang, Feng Yan, Shi-Yu Li, Harris Teague, Hai Li, Yiran Chen

Designing neural architectures for edge devices is subject to constraints of accuracy, inference latency, and computational cost.

Neural Architecture Search

LEASGD: an Efficient and Privacy-Preserving Decentralized Algorithm for Distributed Learning

no code implementations27 Nov 2018 Hsin-Pai Cheng, Patrick Yu, Haojing Hu, Feng Yan, Shi-Yu Li, Hai Li, Yiran Chen

Distributed learning systems have enabled training large-scale models over large amount of data in significantly shorter time.

Privacy Preserving

Differentiable Fine-grained Quantization for Deep Neural Network Compression

1 code implementation NIPS Workshop CDNNRIA 2018 Hsin-Pai Cheng, Yuanjun Huang, Xuyang Guo, Yifei HUANG, Feng Yan, Hai Li, Yiran Chen

Thus judiciously selecting different precision for different layers/structures can potentially produce more efficient models compared to traditional quantization methods by striking a better balance between accuracy and compression rate.

Neural Network Compression Quantization

EigenNet: A Bayesian hybrid of generative and conditional models for sparse learning

no code implementations NeurIPS 2011 Feng Yan, Yuan Qi

To overcome this limitation, we present a novel hybrid model, EigenNet, that uses the eigenstructures of data to guide variable selection.

Sparse Learning Variable Selection

Parallel Inference for Latent Dirichlet Allocation on Graphics Processing Units

no code implementations NeurIPS 2009 Feng Yan, Ningyi Xu, Yuan Qi

Extensive experiments showed that our parallel inference methods consistently produced LDA models with the same predictive power as sequential training methods did but with 26x speedup for CGS and 196x speedup for CVB on a GPU with 30 multiprocessors; actually the speedup is almost linearly scalable with the number of multiprocessors available.

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