Search Results for author: Xin Gao

Found 89 papers, 32 papers with code

Unsupervised Mitigating Gender Bias by Character Components: A Case Study of Chinese Word Embedding

no code implementations NAACL (GeBNLP) 2022 Xiuying Chen, Mingzhe Li, Rui Yan, Xin Gao, Xiangliang Zhang

Word embeddings learned from massive text collections have demonstrated significant levels of discriminative biases. However, debias on the Chinese language, one of the most spoken languages, has been less explored. Meanwhile, existing literature relies on manually created supplementary data, which is time- and energy-consuming. In this work, we propose the first Chinese Gender-neutral word Embedding model (CGE) based on Word2vec, which learns gender-neutral word embeddings without any labeled data. Concretely, CGE utilizes and emphasizes the rich feminine and masculine information contained in radicals, i. e., a kind of component in Chinese characters, during the training procedure. This consequently alleviates discriminative gender biases. Experimental results on public benchmark datasets show that our unsupervised method outperforms the state-of-the-art supervised debiased word embedding models without sacrificing the functionality of the embedding model.

Word Embeddings

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

Language-specific Effects on Automatic Speech Recognition Errors for World Englishes

no code implementations COLING 2022 June Choe, Yiran Chen, May Pik Yu Chan, Aini Li, Xin Gao, Nicole Holliday

Despite recent advancements in automated speech recognition (ASR) technologies, reports of unequal performance across speakers of different demographic groups abound.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +2

Animate Anyone: Consistent and Controllable Image-to-Video Synthesis for Character Animation

no code implementations28 Nov 2023 Li Hu, Xin Gao, Peng Zhang, Ke Sun, Bang Zhang, Liefeng Bo

Character Animation aims to generating character videos from still images through driving signals.

PepLand: a large-scale pre-trained peptide representation model for a comprehensive landscape of both canonical and non-canonical amino acids

no code implementations8 Nov 2023 Ruochi Zhang, Haoran Wu, Yuting Xiu, Kewei Li, Ningning Chen, Yu Wang, Yan Wang, Xin Gao, Fengfeng Zhou

In recent years, the scientific community has become increasingly interested on peptides with non-canonical amino acids due to their superior stability and resistance to proteolytic degradation.

CryoAlign: feature-based method for global and local 3D alignment of EM density maps

no code implementations17 Sep 2023 Bintao He, Fa Zhang, Chenjie Feng, Jianyi Yang, Xin Gao, Renmin Han

Advances on cryo-electron imaging technologies have led to a rapidly increasing number of density maps.

Automated Bioinformatics Analysis via AutoBA

1 code implementation6 Sep 2023 Juexiao Zhou, Bin Zhang, Xiuying Chen, Haoyang Li, Xiaopeng Xu, Siyuan Chen, Xin Gao

With the fast-growing and evolving omics data, the demand for streamlined and adaptable tools to handle the analysis continues to grow.

Language Modelling Large Language Model

Discovering Mental Health Research Topics with Topic Modeling

no code implementations25 Aug 2023 Xin Gao, Cem Sazara

In this study, our goal is to identify general trends in the field and pinpoint high-impact research topics by analyzing a large dataset of mental health research papers.

SkipcrossNets: Adaptive Skip-cross Fusion for Road Detection

no code implementations24 Aug 2023 Xinyu Zhang, Yan Gong, Zhiwei Li, Xin Gao, Dafeng Jin, Jun Li, Huaping Liu

Multi-modal fusion is increasingly being used for autonomous driving tasks, as images from different modalities provide unique information for feature extraction.

Autonomous Driving

PE-YOLO: Pyramid Enhancement Network for Dark Object Detection

3 code implementations20 Jul 2023 Xiangchen Yin, Zhenda Yu, Zetao Fei, Wenjun Lv, Xin Gao

Current object detection models have achieved good results on many benchmark datasets, detecting objects in dark conditions remains a large challenge.

object-detection Object Detection

Path to Medical AGI: Unify Domain-specific Medical LLMs with the Lowest Cost

1 code implementation19 Jun 2023 Juexiao Zhou, Xiuying Chen, Xin Gao

Medical artificial general intelligence (AGI) is an emerging field that aims to develop systems specifically designed for medical applications that possess the ability to understand, learn, and apply knowledge across a wide range of tasks and domains.

Improving the Robustness of Summarization Systems with Dual Augmentation

1 code implementation1 Jun 2023 Xiuying Chen, Guodong Long, Chongyang Tao, Mingzhe Li, Xin Gao, Chengqi Zhang, Xiangliang Zhang

The other factor is in the latent space, where the attacked inputs bring more variations to the hidden states.

Data Augmentation

DeSAM: Decoupling Segment Anything Model for Generalizable Medical Image Segmentation

1 code implementation1 Jun 2023 Yifan Gao, Wei Xia, Dingdu Hu, Xin Gao

In fully automatic mode, the presence of inevitable poor prompts (such as points outside the mask or boxes significantly larger than the mask) can significantly mislead mask generation.

Domain Generalization Image Segmentation +3

A Topic-aware Summarization Framework with Different Modal Side Information

no code implementations19 May 2023 Xiuying Chen, Mingzhe Li, Shen Gao, Xin Cheng, Qiang Yang, Qishen Zhang, Xin Gao, Xiangliang Zhang

To address these two challenges, we first propose a unified topic encoder, which jointly discovers latent topics from the document and various kinds of side information.

Contrastive Learning

Informative Data Selection with Uncertainty for Multi-modal Object Detection

no code implementations23 Apr 2023 Xinyu Zhang, Zhiwei Li, Zhenhong Zou, Xin Gao, Yijin Xiong, Dafeng Jin, Jun Li, Huaping Liu

To quantify the correlation in multi-modal information, we model the uncertainty, as the inverse of data information, in different modalities and embed it in the bounding box generation.

Informativeness object-detection +1

SkinGPT-4: An Interactive Dermatology Diagnostic System with Visual Large Language Model

1 code implementation21 Apr 2023 Juexiao Zhou, Xiaonan He, Liyuan Sun, Jiannan Xu, Xiuying Chen, Yuetan Chu, Longxi Zhou, Xingyu Liao, Bin Zhang, Xin Gao

Skin and subcutaneous diseases rank high among the leading contributors to the global burden of nonfatal diseases, impacting a considerable portion of the population.

Language Modelling Large Language Model

Learning towards Selective Data Augmentation for Dialogue Generation

no code implementations17 Mar 2023 Xiuying Chen, Mingzhe Li, Jiayi Zhang, Xiaoqiang Xia, Chen Wei, Jianwei Cui, Xin Gao, Xiangliang Zhang, Rui Yan

As it is cumbersome and expensive to acquire a huge amount of data for training neural dialog models, data augmentation is proposed to effectively utilize existing training samples.

Data Augmentation Dialogue Generation +1

Audit to Forget: A Unified Method to Revoke Patients' Private Data in Intelligent Healthcare

1 code implementation20 Feb 2023 Juexiao Zhou, Haoyang Li, Xingyu Liao, Bin Zhang, Wenjia He, Zhongxiao Li, Longxi Zhou, Xin Gao

Revoking personal private data is one of the basic human rights, which has already been sheltered by several privacy-preserving laws in many countries.

Privacy Preserving

Personalized and privacy-preserving federated heterogeneous medical image analysis with PPPML-HMI

1 code implementation20 Feb 2023 Juexiao Zhou, Longxi Zhou, Di Wang, Xiaopeng Xu, Haoyang Li, Yuetan Chu, Wenkai Han, Xin Gao

However, there are few open-source frameworks for federated heterogeneous medical image analysis with personalization and privacy protection simultaneously without the demand to modify the existing model structures or to share any private data.

Privacy Preserving

Drug Synergistic Combinations Predictions via Large-Scale Pre-Training and Graph Structure Learning

no code implementations14 Jan 2023 Zhihang Hu, Qinze Yu, Yucheng Guo, Taifeng Wang, Irwin King, Xin Gao, Le Song, Yu Li

While previous methods reported fair performance, their models usually do not take advantage of multi-modal data and they are unable to handle new drugs or cell lines.

Graph structure learning

Multi-Target Landmark Detection with Incomplete Images via Reinforcement Learning and Shape Prior

no code implementations13 Jan 2023 Kaiwen Wan, Lei LI, Dengqiang Jia, Shangqi Gao, Wei Qian, Yingzhi Wu, Huandong Lin, Xiongzheng Mu, Xin Gao, Sijia Wang, Fuping Wu, Xiahai Zhuang

This is particularly evident for the learning-based multi-target landmark detection, where algorithms could be misleading to learn primarily the variation of background due to the varying FOV, failing the detection of targets.

Reinforcement Learning (RL)

Follow the Timeline! Generating Abstractive and Extractive Timeline Summary in Chronological Order

1 code implementation2 Jan 2023 Xiuying Chen, Mingzhe Li, Shen Gao, Zhangming Chan, Dongyan Zhao, Xin Gao, Xiangliang Zhang, Rui Yan

Nowadays, time-stamped web documents related to a general news query floods spread throughout the Internet, and timeline summarization targets concisely summarizing the evolution trajectory of events along the timeline.

Document Summarization Timeline Summarization +1

Towards Efficient and Domain-Agnostic Evasion Attack with High-dimensional Categorical Inputs

no code implementations13 Dec 2022 Hongyan Bao, Yufei Han, Yujun Zhou, Xin Gao, Xiangliang Zhang

Our work targets at searching feasible adversarial perturbation to attack a classifier with high-dimensional categorical inputs in a domain-agnostic setting.

AdvCat: Domain-Agnostic Robustness Assessment for Cybersecurity-Critical Applications with Categorical Inputs

no code implementations13 Dec 2022 Helene Orsini, Hongyan Bao, Yujun Zhou, Xiangrui Xu, Yufei Han, Longyang Yi, Wei Wang, Xin Gao, Xiangliang Zhang

Machine Learning-as-a-Service systems (MLaaS) have been largely developed for cybersecurity-critical applications, such as detecting network intrusions and fake news campaigns.

Adversarial Robustness Fake News Detection +1

Scientific Paper Extractive Summarization Enhanced by Citation Graphs

no code implementations8 Dec 2022 Xiuying Chen, Mingzhe Li, Shen Gao, Rui Yan, Xin Gao, Xiangliang Zhang

We first propose a Multi-granularity Unsupervised Summarization model (MUS) as a simple and low-cost solution to the task.

Extractive Summarization Link Prediction

Prediction of Geometric Transformation on Cardiac MRI via Convolutional Neural Network

1 code implementation12 Nov 2022 Xin Gao

In our work, we propose to learn features in medical images by training ConvNets to recognize the geometric transformation applied to images and present a simple self-supervised task that can easily predict the geometric transformation.

Towards Improving Faithfulness in Abstractive Summarization

1 code implementation4 Oct 2022 Xiuying Chen, Mingzhe Li, Xin Gao, Xiangliang Zhang

The evaluation of factual consistency also shows that our model generates more faithful summaries than baselines.

Abstractive Text Summarization Language Modelling +1

Machine Learning on generalized Complete Intersection Calabi-Yau Manifolds

no code implementations21 Sep 2022 Wei Cui, Xin Gao, Juntao Wang

Generalized Complete Intersection Calabi-Yau Manifold (gCICY) is a new construction of Calabi-Yau manifolds established recently.

Learning Towards the Largest Margins

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

One of the main challenges for feature representation in deep learning-based classification is the design of appropriate loss functions that exhibit strong discriminative power.

Face Verification imbalanced classification +1

Prototype-Anchored Learning for Learning with Imperfect Annotations

no code implementations23 Jun 2022 Xiong Zhou, Xianming Liu, Deming Zhai, Junjun Jiang, Xin Gao, Xiangyang Ji

We verify the effectiveness of PAL on class-imbalanced learning and noise-tolerant learning by extensive experiments on synthetic and real-world datasets.

Target-aware Abstractive Related Work Generation with Contrastive Learning

1 code implementation26 May 2022 Xiuying Chen, Hind Alamro, Mingzhe Li, Shen Gao, Rui Yan, Xin Gao, Xiangliang Zhang

The related work section is an important component of a scientific paper, which highlights the contribution of the target paper in the context of the reference papers.

Contrastive Learning TAG

Context Attention Network for Skeleton Extraction

no code implementations24 May 2022 Zixuan Huang, Yunfeng Wang, Zhiwen Chen, Xin Gao, Ruili Feng, Xiaobo Li

Skeleton extraction is a task focused on providing a simple representation of an object by extracting the skeleton from the given binary or RGB image.

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 implementation CVPR 2022 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 Vocal Bursts Intensity Prediction

Towards artificial general intelligence via a multimodal foundation model

1 code implementation27 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 overcome this limitation and take a solid step towards artificial general intelligence (AGI), we develop a foundation model pre-trained with huge multimodal data, which can be quickly adapted for various downstream cognitive tasks.

Image Classification Reading Comprehension +2

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.

Image Segmentation Knowledge Distillation +2

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.

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.

Retrieval Text Retrieval

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 Object Detection

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

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

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.

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.

BIG-bench Machine Learning 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 Segmentation +1

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 +2

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.

Clustering 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

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.

feature selection graph construction +2

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.

feature selection

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 +2

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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