research
∙
08/28/2023
Large Graph Models: A Perspective
Large models have emerged as the most recent groundbreaking achievements...
share
research
∙
06/28/2023
Graph Interpolation via Fast Fused-Gromovization
Graph data augmentation has proven to be effective in enhancing the gene...
research
∙
05/05/2023
DisenBooth: Disentangled Parameter-Efficient Tuning for Subject-Driven Text-to-Image Generation
Given a small set of images of a specific subject, subject-driven text-t...
research
∙
05/03/2023
DELTA: Direct Embedding Enhancement and Leverage Truncated Conscious Attention for Recommendation System
Click-Through Rate (CTR) prediction is the most critical task in product...
research
∙
04/09/2023
Adversarially Robust Neural Architecture Search for Graph Neural Networks
Graph Neural Networks (GNNs) obtain tremendous success in modeling relat...
research
∙
02/06/2023
Curriculum Graph Machine Learning: A Survey
Graph machine learning has been extensively studied in both academia and...
research
∙
11/21/2022
Disentangled Representation Learning
Disentangled Representation Learning (DRL) aims to learn a model capable...
research
∙
10/28/2022
Domain Generalization through the Lens of Angular Invariance
Domain generalization (DG) aims at generalizing a classifier trained on ...
research
∙
08/31/2022
NeurIPS'22 Cross-Domain MetaDL competition: Design and baseline results
We present the design and baseline results for a new challenge in the Ch...
research
∙
08/13/2022
Revisiting Adversarial Attacks on Graph Neural Networks for Graph Classification
Graph neural networks (GNNs) have achieved tremendous success in the tas...
research
∙
06/18/2022
NAS-Bench-Graph: Benchmarking Graph Neural Architecture Search
Graph neural architecture search (GraphNAS) has recently aroused conside...
research
∙
06/15/2022
A Comprehensive Survey on Deep Clustering: Taxonomy, Challenges, and Future Directions
Clustering is a fundamental machine learning task which has been widely ...
research
∙
06/15/2022
Lessons learned from the NeurIPS 2021 MetaDL challenge: Backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification
Although deep neural networks are capable of achieving performance super...
research
∙
04/21/2022
Arbitrary Bit-width Network: A Joint Layer-Wise Quantization and Adaptive Inference Approach
Conventional model quantization methods use a fixed quantization scheme ...
research
∙
04/07/2022
Learning to Solve Travelling Salesman Problem with Hardness-adaptive Curriculum
Various neural network models have been proposed to tackle combinatorial...
research
∙
03/16/2022
Mixed-Precision Neural Network Quantization via Learned Layer-wise Importance
The exponentially large discrete search space in mixed-precision quantiz...
research
∙
03/10/2022
A Closer Look at Debiased Temporal Sentence Grounding in Videos: Dataset, Metric, and Approach
Temporal Sentence Grounding in Videos (TSGV), which aims to ground a nat...
research
∙
02/24/2022
Fully Self-Supervised Learning for Semantic Segmentation
In this work, we present a fully self-supervised framework for semantic ...
research
∙
02/16/2022
Out-Of-Distribution Generalization on Graphs: A Survey
Graph machine learning has been extensively studied in both academia and...
research
∙
01/04/2022
Self-directed Machine Learning
Conventional machine learning (ML) relies heavily on manual design from ...
research
∙
01/04/2022
Automated Graph Machine Learning: Approaches, Libraries and Directions
Graph machine learning has been extensively studied in both academic and...
research
∙
12/23/2021
Revisiting Transformation Invariant Geometric Deep Learning: Are Initial Representations All You Need?
Geometric deep learning, i.e., designing neural networks to handle the u...
research
∙
12/07/2021
OOD-GNN: Out-of-Distribution Generalized Graph Neural Network
Graph neural networks (GNNs) have achieved impressive performance when t...
research
∙
12/02/2021
Controllable Video Captioning with an Exemplar Sentence
In this paper, we investigate a novel and challenging task, namely contr...
research
∙
12/02/2021
Syntax Customized Video Captioning by Imitating Exemplar Sentences
Enhancing the diversity of sentences to describe video contents is an im...
research
∙
11/03/2021
Conditional Attention Networks for Distilling Knowledge Graphs in Recommendation
Knowledge graph is generally incorporated into recommender systems to im...
research
∙
09/16/2021
A Survey on Temporal Sentence Grounding in Videos
Temporal sentence grounding in videos(TSGV), which aims to localize one ...
research
∙
06/11/2021
Online Continual Adaptation with Active Self-Training
Models trained with offline data often suffer from continual distributio...
research
∙
05/26/2021
Adversarial Attack Framework on Graph Embedding Models with Limited Knowledge
With the success of the graph embedding model in both academic and indus...
research
∙
05/06/2021
Multimedia Edge Computing
In this paper, we investigate the recent studies on multimedia edge comp...
research
∙
04/11/2021
AutoGL: A Library for Automated Graph Learning
Recent years have witnessed an upsurge of research interests and applica...
research
∙
03/01/2021
Automated Machine Learning on Graphs: A Survey
Machine learning on graphs has been extensively studied in both academic...
research
∙
02/22/2021
MetaDelta: A Meta-Learning System for Few-shot Image Classification
Meta-learning aims at learning quickly on novel tasks with limited data ...
research
∙
01/22/2021
A Closer Look at Temporal Sentence Grounding in Videos: Datasets and Metrics
Despite Temporal Sentence Grounding in Videos (TSGV) has realized impres...
research
∙
12/07/2020
STSIR: Spatial Temporal Pandemic Model with Mobility Data
With the outbreak of COVID-19, how to mitigate and suppress its spread i...
research
∙
10/25/2020
A Comprehensive Survey on Curriculum Learning
Curriculum learning (CL) is a training strategy that trains a machine le...
research
∙
09/14/2020
Implicit Graph Neural Networks
Graph Neural Networks (GNNs) are widely used deep learning models that l...
research
∙
09/05/2020
A Simple and General Graph Neural Network with Stochastic Message Passing
Graph neural networks (GNNs) are emerging machine learning models on gra...
research
∙
06/08/2020
Eigen-GNN: A Graph Structure Preserving Plug-in for GNNs
Graph Neural Networks (GNNs) are emerging machine learning models on gra...
research
∙
03/16/2020
Spectral Graph Attention Network
Variants of Graph Neural Networks (GNNs) for representation learning hav...
research
∙
01/02/2020
Deep Learning for Learning Graph Representations
Mining graph data has become a popular research topic in computer scienc...
research
∙
10/31/2019
Semantic Conditioned Dynamic Modulation for Temporal Sentence Grounding in Videos
Temporal sentence grounding in videos aims to detect and localize one ta...
research
∙
10/31/2019
Learning Disentangled Representations for Recommendation
User behavior data in recommender systems are driven by the complex inte...
research
∙
10/25/2019
Hardware-aware One-Shot Neural Architecture Search in Coordinate Ascent Framework
Designing accurate and efficient convolutional neural architectures for ...
research
∙
10/11/2019
Multi-modal Deep Analysis for Multimedia
With the rapid development of Internet and multimedia services in the pa...
research
∙
09/17/2019
AdaCompress: Adaptive Compression for Online Computer Vision Services
With the growth of computer vision based applications and services, an e...
research
∙
08/12/2019
Sentence Specified Dynamic Video Thumbnail Generation
With the tremendous growth of videos over the Internet, video thumbnails...
research
∙
08/04/2019
A Restricted Black-box Adversarial Framework Towards Attacking Graph Embedding Models
With the great success of graph embedding model on both academic and ind...
research
∙
08/04/2019
The General Black-box Attack Method for Graph Neural Networks
With the great success of Graph Neural Networks (GNNs) towards represent...
research
∙
05/24/2019
