b'Tong Zhao'

research

∙ 07/31/2023

A Benchmark for Understanding Dialogue Safety in Mental Health Support

Dialogue safety remains a pervasive challenge in open-domain human-machi...

0 Huachuan Qiu, et al. ∙

research

∙ 07/31/2023

MRA-GNN: Minutiae Relation-Aware Model over Graph Neural Network for Fingerprint Embedding

Deep learning has achieved remarkable results in fingerprint embedding, ...

0 Yapeng Su, et al. ∙

research

∙ 06/12/2023

CARL-G: Clustering-Accelerated Representation Learning on Graphs

Self-supervised learning on graphs has made large strides in achieving g...

0 William Shiao, et al. ∙

research

∙ 06/02/2023

Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All?

Recent studies on Graph Neural Networks(GNNs) provide both empirical and...

20 Haitao Mao, et al. ∙

research

∙ 05/20/2023

Semi-Supervised Graph Imbalanced Regression

Data imbalance is easily found in annotated data when the observations o...

0 Gang Liu, et al. ∙

research

∙ 03/28/2023

Efficient Deep Learning of Robust, Adaptive Policies using Tube MPC-Guided Data Augmentation

The deployment of agile autonomous systems in challenging, unstructured ...

0 Tong Zhao, et al. ∙

research

∙ 03/17/2023

Data-Centric Learning from Unlabeled Graphs with Diffusion Model

Graph property prediction tasks are important and numerous. While each t...

0 Gang Liu, et al. ∙

research

∙ 10/20/2022

Double precision is not necessary for LSQR for solving discrete linear ill-posed problems

The growing availability and usage of low precision foating point format...

0 Haibo Li, et al. ∙

research

∙ 10/19/2022

Backward error analysis of the Lanczos bidiagonalization with reorthogonalization

The k-step Lanczos bidiagonalization reduces a matrix A∈ℝ^m× n into a bi...

0 Haibo Li, et al. ∙

research

∙ 10/11/2022

Linkless Link Prediction via Relational Distillation

Graph Neural Networks (GNNs) have been widely used on graph data and hav...

9 Zhichun Guo, et al. ∙

research

∙ 10/07/2022

Empowering Graph Representation Learning with Test-Time Graph Transformation

As powerful tools for representation learning on graphs, graph neural ne...

28 Wei Jin, et al. ∙

research

∙ 10/06/2022

Grape: Knowledge Graph Enhanced Passage Reader for Open-domain Question Answering

A common thread of open-domain question answering (QA) models employs a ...

0 Mingxuan Ju, et al. ∙

research

∙ 10/05/2022

Multi-task Self-supervised Graph Neural Networks Enable Stronger Task Generalization

Self-supervised learning (SSL) for graph neural networks (GNNs) has attr...

0 Mingxuan Ju, et al. ∙

research

∙ 09/30/2022

MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization

Training graph neural networks (GNNs) on large graphs is complex and ext...

0 Xiaotian Han, et al. ∙

research

∙ 09/17/2022

Flashlight: Scalable Link Prediction with Effective Decoders

Link prediction (LP) has been recognized as an important task in graph l...

0 Yiwei Wang, et al. ∙

research

∙ 06/06/2022

Graph Rationalization with Environment-based Augmentations

Rationale is defined as a subset of input features that best explains or...

0 Gang Liu, et al. ∙

research

∙ 05/21/2022

Retrieval-Augmented Multilingual Keyphrase Generation with Retriever-Generator Iterative Training

Keyphrase generation is the task of automatically predicting keyphrases ...

0 Yifan Gao, et al. ∙

research

∙ 04/04/2022

Coarse-to-Fine Sparse Sequential Recommendation

Sequential recommendation aims to model dynamic user behavior from histo...

0 Jiacheng Li, et al. ∙

research

∙ 03/28/2022

HetuMoE: An Efficient Trillion-scale Mixture-of-Expert Distributed Training System

As giant dense models advance quality but require large-scale expensive ...

0 Xiaonan Nie, et al. ∙

research

∙ 03/18/2022

Learning Personalized Item-to-Item Recommendation Metric via Implicit Feedback

This paper studies the item-to-item recommendation problem in recommende...

0 Trong Nghia Hoang, et al. ∙

research

∙ 03/14/2022

Diversifying Content Generation for Commonsense Reasoning with Mixture of Knowledge Graph Experts

Generative commonsense reasoning (GCR) in natural language is to reason ...

0 Wenhao Yu, et al. ∙

research

∙ 02/17/2022

Graph Data Augmentation for Graph Machine Learning: A Survey

Data augmentation has recently seen increased interest in graph machine ...

0 Tong Zhao, et al. ∙

research

∙ 02/12/2022

RETE: Retrieval-Enhanced Temporal Event Forecasting on Unified Query Product Evolutionary Graph

With the increasing demands on e-commerce platforms, numerous user actio...

0 Ruijie Wang, et al. ∙

research

∙ 09/12/2021

End-to-End Conversational Search for Online Shopping with Utterance Transfer

Successful conversational search systems can present natural, adaptive a...

0 Liqiang Xiao, et al. ∙

research

∙ 09/01/2021

Spatially and Robustly Hybrid Mixture Regression Model for Inference of Spatial Dependence

In this paper, we propose a Spatial Robust Mixture Regression model to i...

0 Wennan Chang, et al. ∙

research

∙ 06/03/2021

Counterfactual Graph Learning for Link Prediction

Learning to predict missing links is important for many graph-based appl...

0 Tong Zhao, et al. ∙

research

∙ 05/06/2021

Graph-based Multilingual Product Retrieval in E-commerce Search

Nowadays, with many e-commerce platforms conducting global business, e-c...

6 Hanqing Lu, et al. ∙

research

∙ 04/15/2021

Sentence-Permuted Paragraph Generation

Generating paragraphs of diverse contents is important in many applicati...

0 Wenhao Yu, et al. ∙

research

∙ 04/01/2021

Cortical Morphometry Analysis based on Worst Transportation Theory

Biomarkers play an important role in early detection and intervention in...

0 Min Zhang, et al. ∙

research

∙ 03/09/2021

Deep Real-Time Decoding of bimanual grip force from EEG fNIRS

Non-invasive cortical neural interfaces have only achieved modest perfor...

0 Pablo Ortega, et al. ∙

research

∙ 10/20/2020

Early Anomaly Detection by Learning and Forecasting Behavior

Graph anomaly detection systems aim at identifying suspicious accounts o...

0 Tong Zhao, et al. ∙

research

∙ 10/05/2020

A Unified View on Graph Neural Networks as Graph Signal Denoising

Graph Neural Networks (GNNs) have risen to prominence in learning repres...

0 Yao Ma, et al. ∙

research

∙ 09/15/2020

Federated Dynamic GNN with Secure Aggregation

Given video data from multiple personal devices or street cameras, can w...

0 Meng Jiang, et al. ∙

research

∙ 09/08/2020

Neural Time-Dependent Partial Differential Equation

Partial differential equations (PDEs) play a crucial role in studying a ...

16 Yihao Hu, et al. ∙

research

∙ 07/31/2020

Geometric All-Way Boolean Tensor Decomposition

Boolean tensor has been broadly utilized in representing high dimensiona...

5 Changlin Wan, et al. ∙

research

∙ 07/31/2020

Denoising individual bias for a fairer binary submatrix detection

Low rank representation of binary matrix is powerful in disentangling sp...

3 Changlin Wan, et al. ∙

research

∙ 07/25/2020

Learning Attribute-Structure Co-Evolutions in Dynamic Graphs

Most graph neural network models learn embeddings of nodes in static att...

0 Daheng Wang, et al. ∙

research

∙ 06/24/2020

AutoKnow: Self-Driving Knowledge Collection for Products of Thousands of Types

Can one build a knowledge graph (KG) for all products in the world? Know...

12 Xin Luna Dong, et al. ∙

research

∙ 06/22/2020

MultiImport: Inferring Node Importance in a Knowledge Graph from Multiple Input Signals

Given multiple input signals, how can we infer node importance in a know...

20 Namyong Park, et al. ∙

research

∙ 06/18/2020

Octet: Online Catalog Taxonomy Enrichment with Self-Supervision

Taxonomies have found wide applications in various domains, especially o...

0 Yuning Mao, et al. ∙

research

∙ 06/17/2020

Canonicalizing Open Knowledge Bases with Multi-Layered Meta-Graph Neural Network

Noun phrases and relational phrases in Open Knowledge Bases are often no...

0 Tianwen Jiang, et al. ∙

research

∙ 06/11/2020

Data Augmentation for Graph Neural Networks

Data augmentation has been widely used to improve generalizability of ma...

0 Tong Zhao, et al. ∙

research

∙ 06/11/2020

A Probabilistic Model with Commonsense Constraints for Pattern-based Temporal Fact Extraction

Textual patterns (e.g., Country's president Person) are specified and/or...

0 Yang Zhou, et al. ∙

research

∙ 09/09/2019

MEBF: a fast and efficient Boolean matrix factorization method

Boolean matrix has been used to represent digital information in many fi...

4 Changlin Wan, et al. ∙

research

∙ 09/09/2019

Fast And Efficient Boolean Matrix Factorization By Geometric Segmentation

Boolean matrix has been used to represent digital information in many fi...

0 Changlin Wan, et al. ∙

research

∙ 06/26/2019

Constructing Information-Lossless Biological Knowledge Graphs from Conditional Statements

Conditions are essential in the statements of biological literature. Wit...

0 Tianwen Jiang, et al. ∙

research

∙ 05/21/2019

Estimating Node Importance in Knowledge Graphs Using Graph Neural Networks

How can we estimate the importance of nodes in a knowledge graph (KG)? A...

6 Namyong Park, et al. ∙

research

∙ 03/17/2016

Saliency Detection with Spaces of Background-based Distribution

In this letter, an effective image saliency detection method is proposed...

0 Tong Zhao, et al. ∙

Tong Zhao

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