Search Results for author: Yu Gong

Found 38 papers, 11 papers with code

COMCAT: Towards Efficient Compression and Customization of Attention-Based Vision Models

1 code implementation26 May 2023 Jinqi Xiao, Miao Yin, Yu Gong, Xiao Zang, Jian Ren, Bo Yuan

Attention-based vision models, such as Vision Transformer (ViT) and its variants, have shown promising performance in various computer vision tasks.

Model Compression

Human-machine knowledge hybrid augmentation method for surface defect detection based few-data learning

no code implementations27 Apr 2023 Yu Gong, Xiaoqiao Wang, ChiChun Zhou

Compared to the traditional augmentation method's F1-score of 64. 59%, the proposed method achieved an 18. 22% increase in the best result, demonstrating its feasibility and effectiveness in few-data industrial defect detection.

Defect Detection

HALOC: Hardware-Aware Automatic Low-Rank Compression for Compact Neural Networks

no code implementations20 Jan 2023 Jinqi Xiao, Chengming Zhang, Yu Gong, Miao Yin, Yang Sui, Lizhi Xiang, Dingwen Tao, Bo Yuan

By interpreting automatic rank selection from an architecture search perspective, we develop an end-to-end solution to determine the suitable layer-wise ranks in a differentiable and hardware-aware way.

Low-rank compression Model Compression

Algorithm and Hardware Co-Design of Energy-Efficient LSTM Networks for Video Recognition with Hierarchical Tucker Tensor Decomposition

no code implementations5 Dec 2022 Yu Gong, Miao Yin, Lingyi Huang, Chunhua Deng, Yang Sui, Bo Yuan

Meanwhile, compared with the state-of-the-art tensor decomposed model-oriented hardware TIE, our proposed FDHT-LSTM architecture achieves better performance in throughput, area efficiency and energy efficiency, respectively on LSTM-Youtube workload.

Tensor Decomposition Video Recognition

RankSim: Ranking Similarity Regularization for Deep Imbalanced Regression

1 code implementation30 May 2022 Yu Gong, Greg Mori, Frederick Tung

Data imbalance, in which a plurality of the data samples come from a small proportion of labels, poses a challenge in training deep neural networks.

Inductive Bias regression +2

GIFT: Graph-guIded Feature Transfer for Cold-Start Video Click-Through Rate Prediction

1 code implementation21 Feb 2022 Sihao Hu, Yi Cao, Yu Gong, Zhao Li, Yazheng Yang, Qingwen Liu, Shouling Ji

Specifically, we establish a heterogeneous graph that contains physical and semantic linkages to guide the feature transfer process from warmed-up video to cold-start videos.

Click-Through Rate Prediction

N3H-Core: Neuron-designed Neural Network Accelerator via FPGA-based Heterogeneous Computing Cores

1 code implementation15 Dec 2021 Yu Gong, Zhihan Xu, Zhezhi He, Weifeng Zhang, Xiaobing Tu, Xiaoyao Liang, Li Jiang

From the software perspective, we mathematically and systematically model the latency and resource utilization of the proposed heterogeneous accelerator, regarding varying system design configurations.


MUSE: Feature Self-Distillation with Mutual Information and Self-Information

no code implementations25 Oct 2021 Yu Gong, Ye Yu, Gaurav Mittal, Greg Mori, Mei Chen

Importantly, we argue and empirically demonstrate that MUSE, compared to other feature discrepancy functions, is a more functional proxy to introduce dependency and effectively improve the expressivity of all features in the knowledge distillation framework.

Image Classification Knowledge Distillation +2

Blind Image Quality Assessment for MRI with A Deep Three-dimensional content-adaptive Hyper-Network

no code implementations13 Jul 2021 Kehan Qi, Haoran Li, Chuyu Rong, Yu Gong, Cheng Li, Hairong Zheng, Shanshan Wang

However, the performance of these methods is limited due to the utilization of simple content-non-adaptive network parameters and the waste of the important 3D spatial information of the medical images.

Blind Image Quality Assessment

GRN: Generative Rerank Network for Context-wise Recommendation

no code implementations2 Apr 2021 Yufei Feng, Binbin Hu, Yu Gong, Fei Sun, Qingwen Liu, Wenwu Ou

Specifically, we first design the evaluator, which applies Bi-LSTM and self-attention mechanism to model the contextual information in the labeled final ranking list and predict the interaction probability of each item more precisely.

Recommendation Systems

Variational Selective Autoencoder: Learning from Partially-Observed Heterogeneous Data

no code implementations25 Feb 2021 Yu Gong, Hossein Hajimirsadeghi, JiaWei He, Thibaut Durand, Greg Mori

Learning from heterogeneous data poses challenges such as combining data from various sources and of different types.


Revisit Recommender System in the Permutation Prospective

no code implementations24 Feb 2021 Yufei Feng, Yu Gong, Fei Sun, Junfeng Ge, Wenwu Ou

Afterwards, for the candidate list set, the PRank stage provides a unified permutation-wise ranking criterion named LR metric, which is calculated by the rating scores of elaborately designed permutation-wise model DPWN.

Recommendation Systems Re-Ranking

Safe Coupled Deep Q-Learning for Recommendation Systems

no code implementations8 Jan 2021 Runsheng Yu, Yu Gong, Rundong Wang, Bo An, Qingwen Liu, Wenwu Ou

Firstly, we introduce a novel training scheme with two value functions to maximize the accumulated long-term reward under the safety constraint.

Q-Learning Recommendation Systems +1

Personalized Adaptive Meta Learning for Cold-start User Preference Prediction

no code implementations22 Dec 2020 Runsheng Yu, Yu Gong, Xu He, Bo An, Yu Zhu, Qingwen Liu, Wenwu Ou

Recently, many existing studies regard the cold-start personalized preference prediction as a few-shot learning problem, where each user is the task and recommended items are the classes, and the gradient-based meta learning method (MAML) is leveraged to address this challenge.

Few-Shot Learning

Multi-task MR Imaging with Iterative Teacher Forcing and Re-weighted Deep Learning

no code implementations27 Nov 2020 Kehan Qi, Yu Gong, Xinfeng Liu, Xin Liu, Hairong Zheng, Shanshan Wang

Noises, artifacts, and loss of information caused by the magnetic resonance (MR) reconstruction may compromise the final performance of the downstream applications.

Distant Supervision for E-commerce Query Segmentation via Attention Network

no code implementations9 Nov 2020 Zhao Li, Donghui Ding, Pengcheng Zou, Yu Gong, Xi Chen, Ji Zhang, Jianliang Gao, Youxi Wu, Yucong Duan

The booming online e-commerce platforms demand highly accurate approaches to segment queries that carry the product requirements of consumers.

Balanced Order Batching with Task-Oriented Graph Clustering

no code implementations19 Aug 2020 Lu Duan, Haoyuan Hu, Zili Wu, Guozheng Li, Xinhang Zhang, Yu Gong, Yinghui Xu

In this paper, rather than designing heuristics, we propose an end-to-end learning and optimization framework named Balanced Task-orientated Graph Clustering Network (BTOGCN) to solve the BOBP by reducing it to balanced graph clustering optimization problem.

Deep Clustering Graph Clustering

Laplacian pyramid-based complex neural network learning for fast MR imaging

no code implementations MIDL 2019 Haoyun Liang, Yu Gong, Hoel Kervadec, Jing Yuan, Hairong Zheng, Shanshan Wang

A Laplacian pyramid-based complex neural network, CLP-Net, is proposed to reconstruct high-quality magnetic resonance images from undersampled k-space data.

Variational Selective Autoencoder

no code implementations pproximateinference AABI Symposium 2019 Yu Gong, Hossein Hajimirsadeghi, JiaWei He, Megha Nawhal, Thibaut Durand, Greg Mori

Despite promising progress on unimodal data imputation (e. g. image inpainting), models for multimodal data imputation are far from satisfactory.

Image Inpainting Imputation

Parameter-Transferred Wasserstein Generative Adversarial Network (PT-WGAN) for Low-Dose PET Image Denoising

1 code implementation13 Oct 2019 Yu Gong, Hongming Shan, Yueyang Teng, Ning Tu, Ming Li, Guodong Liang, Ge Wang, Shan-Shan Wang

The contributions of this paper are twofold: i) a PT-WGAN framework is designed to denoise low-dose PET images without compromising structural details, and ii) a task-specific initialization based on transfer learning is developed to train PT-WGAN using trainable parameters transferred from a pretrained model, which significantly improves the training efficiency of PT-WGAN.

Image Denoising Transfer Learning

Conceptualize and Infer User Needs in E-commerce

1 code implementation8 Oct 2019 Xusheng Luo, Yonghua Yang, Kenny Q. Zhu, Yu Gong, Keping Yang

Understanding latent user needs beneath shopping behaviors is critical to e-commercial applications.

A Minimax Game for Instance based Selective Transfer Learning

no code implementations1 Jul 2019 Bo wang, Minghui Qiu, Xisen Wang, Yaliang Li, Yu Gong, Xiaoyi Zeng, Jung Huang, Bo Zheng, Deng Cai, Jingren Zhou

To the best of our knowledge, this is the first to build a minimax game based model for selective transfer learning.

Retrieval Text Retrieval +1

Query-based Interactive Recommendation by Meta-Path and Adapted Attention-GRU

1 code implementation24 Jun 2019 Yu Zhu, Yu Gong, Qingwen Liu, Yingcai Ma, Wenwu Ou, Junxiong Zhu, Beidou Wang, Ziyu Guan, Deng Cai

A novel query-based interactive recommender system is proposed in this paper, where \textbf{personalized questions are accurately generated from millions of automatically constructed questions} in Step 1, and \textbf{the recommendation is ensured to be closely-related to users' feedback} in Step 2.

Recommendation Systems Retrieval

Variational Autoencoders with Jointly Optimized Latent Dependency Structure

no code implementations ICLR 2019 Jiawei He, Yu Gong, Joseph Marino, Greg Mori, Andreas Lehrmann

In particular, we express the latent variable space of a variational autoencoder (VAE) in terms of a Bayesian network with a learned, flexible dependency structure.

Multi-Modal Generative Adversarial Network for Short Product Title Generation in Mobile E-Commerce

no code implementations NAACL 2019 Jian-Guo Zhang, Pengcheng Zou, Zhao Li, Yao Wan, Xiuming Pan, Yu Gong, Philip S. Yu

To address this discrepancy, previous studies mainly consider textual information of long product titles and lacks of human-like view during training and evaluation process.

Query Tracking for E-commerce Conversational Search: A Machine Comprehension Perspective

no code implementations8 Oct 2018 Yunlun Yang, Yu Gong, Xi Chen

With the development of dialog techniques, conversational search has attracted more and more attention as it enables users to interact with the search engine in a natural and efficient manner.

Conversational Search Natural Language Understanding +3

Automatic Generation of Chinese Short Product Titles for Mobile Display

1 code implementation30 Mar 2018 Yu Gong, Xusheng Luo, Kenny Q. Zhu, Wenwu Ou, Zhao Li, Lu Duan

This paper studies the problem of automatically extracting a short title from a manually written longer description of E-commerce products for display on mobile devices.

Extractive Summarization

Representing Verbs as Argument Concepts

no code implementations2 Mar 2018 Yu Gong, Kaiqi Zhao, Kenny Q. Zhu

Verbs play an important role in the understanding of natural language text.

IRGAN: A Minimax Game for Unifying Generative and Discriminative Information Retrieval Models

3 code implementations30 May 2017 Jun Wang, Lantao Yu, Wei-Nan Zhang, Yu Gong, Yinghui Xu, Benyou Wang, Peng Zhang, Dell Zhang

This paper provides a unified account of two schools of thinking in information retrieval modelling: the generative retrieval focusing on predicting relevant documents given a query, and the discriminative retrieval focusing on predicting relevancy given a query-document pair.

Document Ranking Information Retrieval +2

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