Search
Search Results
-
Generation, augmentation, and alignment: a pseudo-source domain based method for source-free domain adaptation
Source-free domain adaptation (SFDA) aims to train a well-performed model in the target domain given both a trained source model and unlabeled target...
-
An Entity Alignment Method Based on Graph Attention Network with Pre-classification
Entity alignment is the process of identifying entities that point to the same object in different knowledge graphs. Entity alignment is a key step...
-
Locally controllable network based on visual–linguistic relation alignment for text-to-image generation
Since locally controllable text-to-image generation cannot achieve satisfactory results in detail, a novel locally controllable text-to-image...
-
Social network alignment: a bi-layer graph attention neural networks based method
The task of social network alignment is to identify the user nodes which are active in multiple social networks simultaneously, thus the information...
-
Diffusion Transport Alignment
The integration of multimodal data presents a challenge in cases where the study of a given phenomena by different instruments or conditions...
-
Large-Scale Entity Alignment
In this chapter, we focus on the concept of entity alignment at scale and present a new method for addressing this task. The proposed solution is...
-
Unsupervised Deep Cross-Language Entity Alignment
Cross-lingual entity alignment is the task of finding the same semantic entities from different language knowledge graphs. In this paper, we propose...
-
Unsupervised Entity Alignment
State-of-the-art entity alignment solutions tend to rely on labeled data for model training. Additionally, they work under the closed-domain setting...
-
Cross-domain object detection by local to global object-aware feature alignment
Cross-domain object detection has attracted more and more attention recently. It reduces the gap between the two domains, where the source domain is...
-
Quality-aware face alignment using high-resolution spatial dependencies
Although CNN-based face alignment algorithms have got promising results. However, their alignment accuracy are still suffer from faces with severe...
-
Generative adversarial network for unsupervised multi-lingual knowledge graph entity alignment
Entity alignment is an essential process in knowledge graph (KG) fusion, which aims to link entities representing the same real-world object in...
-
SeNSe: embedding alignment via semantic anchors selection
Word embeddings have proven extremely useful across many NLP applications in recent years. Several key linguistic tasks, such as machine translation...
-
School and Teacher Information, Communication and Technology (ICT) readiness across 57 countries: The alignment optimization method
This study investigated the measurement invariance of school and teacher Information, Communication and Technology (ICT) readiness among 57 countries...
-
Long-Tail Entity Alignment
Most entity alignment solutions currently rely on structural information, specifically KG embedding, to align entities. However, in real-life KGs,...
-
A relation enhanced model for temporal knowledge graph alignment
Entity alignment (EA) aims to find entities that point to the same object in multiple knowledge graphs (KGs), i.e., finding equivalent entity pairs....
-
How to measure value alignment in AI
How can we make sure that AI systems align with human values and norms? An important step towards reaching this goal is to develop a method for...
-
Multimodal Entity Alignment
In various tasks related to artificial intelligence, data is often present in multiple forms or modalities. Recently, it has become a popular...
-
Review of Deep Learning-Based Entity Alignment Methods
Entity alignment aims to discover different references to the same entity in different graphs, and it is a key technique for solving graph-related...
-
Global–local Bi-alignment for purer unsupervised domain adaptation
Unsupervised domain adaptation (UDA) aims to extract domain-invariant features. Existing UDA methods mainly utilize a convolutional neural network...
-
Weakly Supervised Entity Alignment
The majority of state-of-the-art entity alignment solutions heavily rely on the labeled data, which are difficult to obtain in practice. Therefore,...