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07/31/2023
A Benchmark for Understanding Dialogue Safety in Mental Health Support
Dialogue safety remains a pervasive challenge in open-domain human-machi...
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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, ...
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06/12/2023
CARL-G: Clustering-Accelerated Representation Learning on Graphs
Self-supervised learning on graphs has made large strides in achieving g...
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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...
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05/20/2023
Semi-Supervised Graph Imbalanced Regression
Data imbalance is easily found in annotated data when the observations o...
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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 ...
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03/17/2023
Data-Centric Learning from Unlabeled Graphs with Diffusion Model
Graph property prediction tasks are important and numerous. While each t...
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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...
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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...
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10/11/2022
Linkless Link Prediction via Relational Distillation
Graph Neural Networks (GNNs) have been widely used on graph data and hav...
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10/07/2022
Empowering Graph Representation Learning with Test-Time Graph Transformation
As powerful tools for representation learning on graphs, graph neural ne...
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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 ...
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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...
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09/30/2022
MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization
Training graph neural networks (GNNs) on large graphs is complex and ext...
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09/17/2022
Flashlight: Scalable Link Prediction with Effective Decoders
Link prediction (LP) has been recognized as an important task in graph l...
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06/06/2022
Graph Rationalization with Environment-based Augmentations
Rationale is defined as a subset of input features that best explains or...
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05/21/2022
Retrieval-Augmented Multilingual Keyphrase Generation with Retriever-Generator Iterative Training
Keyphrase generation is the task of automatically predicting keyphrases ...
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04/04/2022
Coarse-to-Fine Sparse Sequential Recommendation
Sequential recommendation aims to model dynamic user behavior from histo...
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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 ...
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03/18/2022
Learning Personalized Item-to-Item Recommendation Metric via Implicit Feedback
This paper studies the item-to-item recommendation problem in recommende...
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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 ...
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02/17/2022
Graph Data Augmentation for Graph Machine Learning: A Survey
Data augmentation has recently seen increased interest in graph machine ...
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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...
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09/12/2021
End-to-End Conversational Search for Online Shopping with Utterance Transfer
Successful conversational search systems can present natural, adaptive a...
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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...
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06/03/2021
Counterfactual Graph Learning for Link Prediction
Learning to predict missing links is important for many graph-based appl...
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05/06/2021
Graph-based Multilingual Product Retrieval in E-commerce Search
Nowadays, with many e-commerce platforms conducting global business, e-c...
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04/15/2021
Sentence-Permuted Paragraph Generation
Generating paragraphs of diverse contents is important in many applicati...
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04/01/2021
Cortical Morphometry Analysis based on Worst Transportation Theory
Biomarkers play an important role in early detection and intervention in...
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03/09/2021
Deep Real-Time Decoding of bimanual grip force from EEG fNIRS
Non-invasive cortical neural interfaces have only achieved modest perfor...
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10/20/2020
Early Anomaly Detection by Learning and Forecasting Behavior
Graph anomaly detection systems aim at identifying suspicious accounts o...
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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...
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09/15/2020
Federated Dynamic GNN with Secure Aggregation
Given video data from multiple personal devices or street cameras, can w...
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09/08/2020
Neural Time-Dependent Partial Differential Equation
Partial differential equations (PDEs) play a crucial role in studying a ...
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07/31/2020
Geometric All-Way Boolean Tensor Decomposition
Boolean tensor has been broadly utilized in representing high dimensiona...
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07/31/2020
Denoising individual bias for a fairer binary submatrix detection
Low rank representation of binary matrix is powerful in disentangling sp...
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07/25/2020
Learning Attribute-Structure Co-Evolutions in Dynamic Graphs
Most graph neural network models learn embeddings of nodes in static att...
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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...
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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...
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06/18/2020
Octet: Online Catalog Taxonomy Enrichment with Self-Supervision
Taxonomies have found wide applications in various domains, especially o...
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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...
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06/11/2020
Data Augmentation for Graph Neural Networks
Data augmentation has been widely used to improve generalizability of ma...
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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...
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09/09/2019
MEBF: a fast and efficient Boolean matrix factorization method
Boolean matrix has been used to represent digital information in many fi...
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09/09/2019
Fast And Efficient Boolean Matrix Factorization By Geometric Segmentation
Boolean matrix has been used to represent digital information in many fi...
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06/26/2019
Constructing Information-Lossless Biological Knowledge Graphs from Conditional Statements
Conditions are essential in the statements of biological literature. Wit...
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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...
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03/17/2016