Search Results for author: Xin Gao

Found 53 papers, 18 papers with code

Distance Metric Learning with Joint Representation Diversification

1 code implementation ICML 2020 Xu Chu, Yang Lin, Xiting Wang, Xin Gao, Qi Tong, Hailong Yu, Yasha Wang

Distance metric learning (DML) is to learn a representation space equipped with a metric, such that examples from the same class are closer than examples from different classes with respect to the metric.

Metric Learning

ProNet DB: A proteome-wise database for protein surface property representations and RNA-binding profiles

no code implementations16 May 2022 Junkang Wei, Jin Xiao, Siyuan Chen, Licheng Zong, Xin Gao, Yu Li

The rapid growth in the number of experimental and predicted protein structures and more complicated protein structures challenge users in computational biology for utilizing the structural information and protein surface property representation.

Drug Discovery

Modeling COVID-19 vaccine-induced immunological memory development and its links to antibody level and infectiousness

no code implementations5 Apr 2022 Xin Gao, Jianwei Li, Dianjie Li

By introducing the maximum viral load and recovery time after viral infection, we quantitatively studied the protective effect of vaccines against viral infection.

Weakly Supervised High-Fidelity Clothing Model Generation

1 code implementation14 Dec 2021 Ruili Feng, Cheng Ma, Chengji Shen, Xin Gao, Zhenjiang Liu, Xiaobo Li, Kairi Ou, ZhengJun Zha

The development of online economics arouses the demand of generating images of models on product clothes, to display new clothes and promote sales.

Virtual Try-on

WenLan 2.0: Make AI Imagine via a Multimodal Foundation Model

no code implementations27 Oct 2021 Nanyi Fei, Zhiwu Lu, Yizhao Gao, Guoxing Yang, Yuqi Huo, Jingyuan Wen, Haoyu Lu, Ruihua Song, Xin Gao, Tao Xiang, Hao Sun, Ji-Rong Wen

To resolve this issue, we propose to pre-train our foundation model by self-supervised learning with weak semantic correlation data crawled from the Internet and show that state-of-the-art results can be obtained on a wide range of downstream tasks (both single-modal and cross-modal).

Image Classification Reading Comprehension +2

Learning Towards The Largest Margins

no code implementations ICLR 2022 Xiong Zhou, Xianming Liu, Deming Zhai, Junjun Jiang, Xin Gao, Xiangyang Ji

Specifically, we firstly propose to employ the class margin as the measure of inter-class separability, and the sample margin as the measure of intra-class compactness.

Face Verification imbalanced classification +1

Shape Controllable Virtual Try-on for Underwear Models

no code implementations28 Jul 2021 Xin Gao, Zhenjiang Liu, Zunlei Feng, Chengji Shen, Kairi Ou, Haihong Tang, Mingli Song

Existing 2D image-based virtual try-on methods aim to transfer a target clothing image onto a reference person, which has two main disadvantages: cannot control the size and length precisely; unable to accurately estimate the user's figure in the case of users wearing thick clothes, resulting in inaccurate dressing effect.

Graph Attention Virtual Try-on

Protein-RNA interaction prediction with deep learning: Structure matters

no code implementations26 Jul 2021 Junkang Wei, Siyuan Chen, Licheng Zong, Xin Gao, Yu Li

Protein-RNA interactions are of vital importance to a variety of cellular activities.

Double Similarity Distillation for Semantic Image Segmentation

no code implementations19 Jul 2021 Yingchao Feng, Xian Sun, Wenhui Diao, Jihao Li, Xin Gao

In this paper, motivated by the residual learning and global aggregation, we propose a simple yet general and effective knowledge distillation framework called double similarity distillation (DSD) to improve the classification accuracy of all existing compact networks by capturing the similarity knowledge in pixel and category dimensions, respectively.

Knowledge Distillation Semantic Segmentation

The Reconfiguration Pattern of Individual Brain Metabolic Connectome for Parkinson's Disease Identification

no code implementations29 Apr 2021 Weikai Li, Yongxiang Tang, Zhengxia Wang, Shuo Hu, Xin Gao

We aim to establish an individual metabolic connectome method to characterize the aberrant connectivity patterns and topological alterations of the individual-level brain metabolic connectome and their diagnostic value in PD.

Person Re-Identification by Context-aware Part Attention and Multi-Head Collaborative Learning

no code implementations IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY 2021 Dongming Wu, Mang Ye, Gaojie Lin, Xin Gao, Jianbing Shen

In addition, we propose a novel multi-head collaborative training scheme to improve the performance, which is collaboratively supervised by multiple heads with the same structure but different parameters.

Frame Video-Based Person Re-Identification

A Data-Centric Framework for Composable NLP Workflows

1 code implementation EMNLP 2020 Zhengzhong Liu, Guanxiong Ding, Avinash Bukkittu, Mansi Gupta, Pengzhi Gao, Atif Ahmed, Shikun Zhang, Xin Gao, Swapnil Singhavi, Linwei Li, Wei Wei, Zecong Hu, Haoran Shi, Haoying Zhang, Xiaodan Liang, Teruko Mitamura, Eric P. Xing, Zhiting Hu

Empirical natural language processing (NLP) systems in application domains (e. g., healthcare, finance, education) involve interoperation among multiple components, ranging from data ingestion, human annotation, to text retrieval, analysis, generation, and visualization.

A Framework For Differentiable Discovery Of Graph Algorithms

no code implementations NeurIPS Workshop LMCA 2020 Hanjun Dai, Xinshi Chen, Yu Li, Xin Gao, Le Song

Recently there is a surge of interests in using graph neural networks (GNNs) to learn algorithms.

One-sample Guided Object Representation Disassembling

no code implementations NeurIPS 2020 Zunlei Feng, Yongming He, Xinchao Wang, Xin Gao, Jie Lei, Cheng Jin, Mingli Song

In this paper, we introduce the One-sample Guided Object Representation Disassembling (One-GORD) method, which only requires one annotated sample for each object category to learn disassembled object representation from unannotated images.

Data Augmentation Image Classification

Object sieving and morphological closing to reduce false detections in wide-area aerial imagery

no code implementations28 Oct 2020 Xin Gao, Sundaresh Ram, Jeffrey J. Rodriguez

We use two wide-area aerial videos to compare the performance of five object detection algorithms in the absence and in the presence of our post-processing scheme.

Object Detection

Service Chain Composition with Failures in NFV Systems: A Game-Theoretic Perspective

no code implementations1 Aug 2020 Simeng Bian, Xi Huang, Ziyu Shao, Xin Gao, Yang Yang

In this paper, we formulate the problem of service chain composition in NFV systems with failures as a non-cooperative game.

History-Aware Online Cache Placement in Fog-Assisted IoT Systems: An Integration of Learning and Control

no code implementations1 Aug 2020 Xin Gao, Xi Huang, Yinxu Tang, Ziyu Shao, Yang Yang

Due to uncertainties in practice such as unknown file popularities, cache placement scheme design is still an open problem with unresolved challenges: 1) how to maintain time-averaged storage costs under budgets, 2) how to incorporate online learning to aid cache placement to minimize performance loss (a. k. a.

Networking and Internet Architecture Signal Processing

Green Offloading in Fog-Assisted IoT Systems: An Online Perspective Integrating Learning and Control

no code implementations1 Aug 2020 Xin Gao, Xi Huang, Ziyu Shao, Yang Yang

In this paper, we formulate such a task offloading problem with unknown system dynamics as a combinatorial multi-armed bandit (CMAB) problem with long-term constraints on time-averaged energy consumptions.

Decision Making online learning

Learning to Stop While Learning to Predict

1 code implementation ICML 2020 Xinshi Chen, Hanjun Dai, Yu Li, Xin Gao, Le Song

Similar to algorithms, the optimal depth of a deep architecture may be different for different input instances, either to avoid ``over-thinking'', or because we want to compute less for operations converged already.


Disassembling Object Representations without Labels

no code implementations3 Apr 2020 Zunlei Feng, Xinchao Wang, Yongming He, Yike Yuan, Xin Gao, Mingli Song

In this paper, we study a new representation-learning task, which we termed as disassembling object representations.

General Classification Representation Learning +1

RNA Secondary Structure Prediction By Learning Unrolled Algorithms

1 code implementation ICLR 2020 Xinshi Chen, Yu Li, Ramzan Umarov, Xin Gao, Le Song

The key idea of E2Efold is to directly predict the RNA base-pairing matrix, and use an unrolled algorithm for constrained programming as the template for deep architectures to enforce constraints.

Intermittent Pulling with Local Compensation for Communication-Efficient Federated Learning

no code implementations22 Jan 2020 Haozhao Wang, Zhihao Qu, Song Guo, Xin Gao, Ruixuan Li, Baoliu Ye

A major bottleneck on the performance of distributed Stochastic Gradient Descent (SGD) algorithm for large-scale Federated Learning is the communication overhead on pushing local gradients and pulling global model.

Federated Learning

AdaCare: Explainable Clinical Health Status Representation Learning via Scale-Adaptive Feature Extraction and Recalibration

1 code implementation27 Nov 2019 Liantao Ma, Junyi Gao, Yasha Wang, Chaohe Zhang, Jiangtao Wang, Wenjie Ruan, Wen Tang, Xin Gao, Xinyu Ma

It also models the correlation between clinical features to enhance the ones which strongly indicate the health status and thus can maintain a state-of-the-art performance in terms of prediction accuracy while providing qualitative interpretability.

Representation Learning

ConCare: Personalized Clinical Feature Embedding via Capturing the Healthcare Context

1 code implementation27 Nov 2019 Liantao Ma, Chaohe Zhang, Yasha Wang, Wenjie Ruan, Jiantao Wang, Wen Tang, Xinyu Ma, Xin Gao, Junyi Gao

Predicting the patient's clinical outcome from the historical electronic medical records (EMR) is a fundamental research problem in medical informatics.

Ship Instance Segmentation From Remote Sensing Images Using Sequence Local Context Module

no code implementations22 Apr 2019 Yingchao Feng, Wenhui Diao, Zhonghan Chang, Menglong Yan, Xian Sun, Xin Gao

The performance of object instance segmentation in remote sensing images has been greatly improved through the introduction of many landmark frameworks based on convolutional neural network.

Instance Segmentation Semantic Segmentation

Deep learning in bioinformatics: introduction, application, and perspective in big data era

1 code implementation28 Feb 2019 Yu Li, Chao Huang, Lizhong Ding, Zhongxiao Li, Yijie Pan, Xin Gao

Deep learning, which is especially formidable in handling big data, has achieved great success in various fields, including bioinformatics.

PromID: human promoter prediction by deep learning

no code implementations2 Oct 2018 Ramzan Umarov, Hiroyuki Kuwahara, Yu Li, Xin Gao, Victor Solovyev

In this work we further develop our deep learning approach that was relatively successful to discriminate short promoter and non-promoter sequences.

Hybrid Policies Using Inverse Rewards for Reinforcement Learning

no code implementations27 Sep 2018 Yao Shi, Tian Xia, Guanjun Zhao, Xin Gao

This paper puts forward a broad-spectrum improvement for reinforcement learning algorithms, which combines the policies using original rewards and inverse (negative) rewards.

OpenAI Gym Q-Learning +1

On the Decision Boundary of Deep Neural Networks

1 code implementation16 Aug 2018 Yu Li, Lizhong Ding, Xin Gao

We demonstrate, both theoretically and empirically, that the last weight layer of a neural network converges to a linear SVM trained on the output of the last hidden layer, for both the binary case and the multi-class case with the commonly used cross-entropy loss.

SupportNet: solving catastrophic forgetting in class incremental learning with support data

1 code implementation8 Jun 2018 Yu Li, Zhongxiao Li, Lizhong Ding, Yijie Pan, Chao Huang, Yuhui Hu, Wei Chen, Xin Gao

A plain well-trained deep learning model often does not have the ability to learn new knowledge without forgetting the previously learned knowledge, which is known as catastrophic forgetting.

class-incremental learning Incremental Learning

DLBI: Deep learning guided Bayesian inference for structure reconstruction of super-resolution fluorescence microscopy

1 code implementation20 May 2018 Yu Li, Fan Xu, Fa Zhang, Pingyong Xu, Mingshu Zhang, Ming Fan, Lihua Li, Xin Gao, Renmin Han

Our method combines the strength of deep learning and statistical inference, where deep learning captures the underlying distribution of the fluorophores that are consistent with the observed time-series fluorescent images by exploring local features and correlation along time-axis, and statistical inference further refines the ultrastructure extracted by deep learning and endues physical meaning to the final image.

Bayesian Inference Super-Resolution +2

OPA2Vec: combining formal and informal content of biomedical ontologies to improve similarity-based prediction

1 code implementation29 Apr 2018 Fatima Zohra Smaili, Xin Gao, Robert Hoehndorf

Second, we evaluate our method on predicting gene-disease associations based on phenotype similarity by generating vector representations of genes and diseases using a phenotype ontology, and applying the obtained vectors to predict gene-disease associations.

Semantic Similarity Semantic Textual Similarity

Onto2Vec: joint vector-based representation of biological entities and their ontology-based annotations

1 code implementation31 Jan 2018 Fatima Zohra Smaili, Xin Gao, Robert Hoehndorf

We propose the Onto2Vec method, an approach to learn feature vectors for biological entities based on their annotations to biomedical ontologies.

General Classification

Predicting Discharge Medications at Admission Time Based on Deep Learning

no code implementations4 Nov 2017 Yuan Yang, Pengtao Xie, Xin Gao, Carol Cheng, Christy Li, Hongbao Zhang, Eric Xing

Predicting discharge medications right after a patient being admitted is an important clinical decision, which provides physicians with guidance on what type of medication regimen to plan for and what possible changes on initial medication may occur during an inpatient stay.

RIDDLE: Race and ethnicity Imputation from Disease history with Deep LEarning

1 code implementation6 Jul 2017 Ji-Sung Kim, Xin Gao, Andrey Rzhetsky

Anonymized electronic medical records are an increasingly popular source of research data.


Robust Cost-Sensitive Learning for Recommendation with Implicit Feedback

no code implementations3 Jul 2017 Peng Yang, Peilin Zhao, Xin Gao, Yong liu

Morever, the proposed algorithm can be scaled up to large-sized datasets after a relaxation.

Robust Online Multi-Task Learning with Correlative and Personalized Structures

no code implementations6 Jun 2017 Peng Yang, Peilin Zhao, Xin Gao

Multi-Task Learning (MTL) can enhance a classifier's generalization performance by learning multiple related tasks simultaneously.

Multi-Task Learning online learning

Regularized maximum correntropy machine

no code implementations18 Jan 2015 Jim Jing-Yan Wang, Yunji Wang, Bing-Yi Jing, Xin Gao

To solve this problem, we propose to learn the class label predictors by maximizing the correntropy between the predicted labels and the true labels of the training samples, under the regularized Maximum Correntropy Criteria (MCC) framework.

Learning manifold to regularize nonnegative matrix factorization

no code implementations3 Oct 2014 Jim Jing-Yan Wang, Xin Gao

Recently, manifold regularized NMF used a nearest neighbor graph to regulate the learning of factorization parameter matrices and has shown its advantage over traditional NMF methods for data representation problems.

graph construction Graph Learning +1

Maximum mutual information regularized classification

no code implementations27 Sep 2014 Jim Jing-Yan Wang, Yi Wang, Shiguang Zhao, Xin Gao

In this paper, a novel pattern classification approach is proposed by regularizing the classifier learning to maximize mutual information between the classification response and the true class label.

Classification General Classification

Feature selection and multi-kernel learning for adaptive graph regularized nonnegative matrix factorization

no code implementations Elsevier Ltd 2014 Jim Jing-Yan Wang, Jianhua Z. Huang, Yijun Sun, Xin Gao

To solve these bottlenecks, we propose two novel graph-regularized NMF methods, AGNMFFS and AGNMFMK, by introducing feature selection and multiple-kernel learning to the graph regularized NMF, respectively.

When coding meets ranking: A joint framework based on local learning

no code implementations8 Sep 2014 Jim Jing-Yan Wang, Xuefeng Cui, Ge Yu, Lili Guo, Xin Gao

In this paper, we try to answer these questions by developing the first joint sparse coding and ranking score learning algorithm.

Large Margin Image Set Representation and Classification

no code implementations22 Apr 2014 Jim Jing-Yan Wang, Majed Alzahrani, Xin Gao

In this paper, we propose a novel image set representation and classification method by maximizing the margin of image sets.

Classification Face Recognition +1

Semi-Supervised Sparse Coding

no code implementations26 Nov 2013 Jim Jing-Yan Wang, Xin Gao

Sparse coding approximates the data sample as a sparse linear combination of some basic codewords and uses the sparse codes as new presentations.

Multiple graph regularized protein domain ranking

no code implementations18 Aug 2012 Jim Jing-Yan Wang, Halima Bensmail, Xin Gao

However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods.

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