Search Results for author: Jingrui He

Found 21 papers, 9 papers with code

DPPIN: A Biological Dataset of Dynamic Protein-Protein Interaction Networks

1 code implementation5 Jul 2021 Dongqi Fu, Jingrui He

Nowadays, many network representation learning algorithms and downstream network mining tasks have already paid attention to dynamic networks or temporal networks, which are more suitable for real-world complex scenarios by modeling evolving patterns and temporal dependencies between node interactions.

Drug Discovery Fraud Detection +3

Multi-facet Contextual Bandits: A Neural Network Perspective

1 code implementation6 Jun 2021 Yikun Ban, Jingrui He, Curtiss B. Cook

In this paper, we study a novel problem of multi-facet bandits involving a group of bandits, each characterizing the users' needs from one unique aspect.

Multi-Armed Bandits Recommendation Systems

Controllable Gradient Item Retrieval

1 code implementation31 May 2021 Haonan Wang, Chang Zhou, Carl Yang, Hongxia Yang, Jingrui He

A better way is to present a sequence of products with increasingly floral attributes based on the white dress, and allow the customer to select the most satisfactory one from the sequence.

Heterogeneous Contrastive Learning

no code implementations19 May 2021 Lecheng Zheng, Yada Zhu, Jingrui He, JinJun Xiong

With the advent of big data across multiple high-impact applications, we are often facing the challenge of complex heterogeneity.

Contrastive Learning

Local Clustering in Contextual Multi-Armed Bandits

no code implementations26 Feb 2021 Yikun Ban, Jingrui He

We study identifying user clusters in contextual multi-armed bandits (MAB).

Multi-Armed Bandits

Deep Co-Attention Network for Multi-View Subspace Learning

1 code implementation15 Feb 2021 Lecheng Zheng, Yu Cheng, Hongxia Yang, Nan Cao, Jingrui He

For example, given the diagnostic result that a model provided based on the X-ray images of a patient at different poses, the doctor needs to know why the model made such a prediction.

Robust Federated Learning for Neural Networks

no code implementations1 Jan 2021 Yao Zhou, Jun Wu, Jingrui He

In federated learning, data is distributed among local clients which collaboratively train a prediction model using secure aggregation.

Federated Learning

Continuous Transfer Learning

no code implementations1 Jan 2021 Jun Wu, Jingrui He

One major challenge associated with continuous transfer learning is the time evolving relatedness of the source domain and the current target domain as the target domain evolves over time.

Transfer Learning

GAN-based Recommendation with Positive-Unlabeled Sampling

no code implementations12 Dec 2020 Yao Zhou, Jianpeng Xu, Jun Wu, Zeinab Taghavi Nasrabadi, Evren Korpeoglu, Kannan Achan, Jingrui He

Recommender systems are popular tools for information retrieval tasks on a large variety of web applications and personalized products.

Information Retrieval Recommendation Systems

Robust Decentralized Learning for Neural Networks

no code implementations18 Sep 2020 Yao Zhou, Jun Wu, Jingrui He

To preserve the privacy of the clients, modern decentralized learning paradigms require each client to maintain a private local training data set and only upload their summarized model updates to the server.

A Visual Analytics Framework for Explaining and Diagnosing Transfer Learning Processes

1 code implementation15 Sep 2020 Yuxin Ma, Arlen Fan, Jingrui He, Arun Reddy Nelakurthi, Ross Maciejewski

Transfer Learning is intended to relax this assumption by modeling relationships between domains, and is often applied in deep learning applications to reduce the demand for labeled data and training time.

Image Classification Transfer Learning

Generic Outlier Detection in Multi-Armed Bandit

no code implementations14 Jul 2020 Yikun Ban, Jingrui He

In this paper, we study the problem of outlier arm detection in multi-armed bandit settings, which finds plenty of applications in many high-impact domains such as finance, healthcare, and online advertising.

Outlier Detection

Continuous Transfer Learning with Label-informed Distribution Alignment

no code implementations5 Jun 2020 Jun Wu, Jingrui He

To bridge this gap, in this paper, we study a novel continuous transfer learning setting with a time evolving target domain.

Transfer Learning

Visual Analytics of Anomalous User Behaviors: A Survey

no code implementations14 May 2019 Yang Shi, Yuyin Liu, Hanghang Tong, Jingrui He, Gang Yan, Nan Cao

The increasing accessibility of data provides substantial opportunities for understanding user behaviors.

Anomaly Detection

Deep Multimodality Model for Multi-task Multi-view Learning

1 code implementation25 Jan 2019 Lecheng Zheng, Yu Cheng, Jingrui He

However, there is no existing deep learning algorithm that jointly models task and view dual heterogeneity, particularly for a data set with multiple modalities (text and image mixed data set or text and video mixed data set, etc.).

General Classification Image Classification +1

Optimizing the Wisdom of the Crowd: Inference, Learning, and Teaching

no code implementations23 Jun 2018 Yao Zhou, Jingrui He

The unprecedented demand for large amount of data has catalyzed the trend of combining human insights with machine learning techniques, which facilitate the use of crowdsourcing to enlist label information both effectively and efficiently.

ImVerde: Vertex-Diminished Random Walk for Learning Network Representation from Imbalanced Data

1 code implementation24 Apr 2018 Jun Wu, Jingrui He, Yongming Liu

Then, based on VDRW, we propose a semi-supervised network representation learning framework named ImVerde for imbalanced networks, in which context sampling uses VDRW and the label information to create node-context pairs, and balanced-batch sampling adopts a simple under-sampling method to balance these pairs in different classes.

Social and Information Networks

Unlearn What You Have Learned: Adaptive Crowd Teaching with Exponentially Decayed Memory Learners

1 code implementation17 Apr 2018 Yao Zhou, Arun Reddy Nelakurthi, Jingrui He

With the increasing demand for large amount of labeled data, crowdsourcing has been used in many large-scale data mining applications.

GenDeR: A Generic Diversified Ranking Algorithm

no code implementations NeurIPS 2012 Jingrui He, Hanghang Tong, Qiaozhu Mei, Boleslaw Szymanski

In this paper, we consider a generic setting where we aim to diversify the top-k ranking list based on an arbitrary relevance function and an arbitrary similarity function among all the examples.

Information Retrieval

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