62 Result(s)
within
Chapter
Conference Paper
Fan** Li
English
Data Mining and Knowledge Discovery
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Chapter and Conference Paper
A Lightweight Text Classification Model Based on Label Embedding Attentive Mechanism
This paper presents a lightweight model based on the self-attention mechanism for text classification tasks. In our model, we incorporate auxiliary information of the label through the label embedding method, ...
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Chapter and Conference Paper
MeFormer: Generating Radiology Reports via Memory Enhanced Pretraining Transformer
Writing a radiology image report is a very time-consuming and tedious task. Using AI to generate the report is an efficient approach, but there are still two significant challenges. First, the model requires t...
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Chapter and Conference Paper
Patch Mix Augmentation with Dual Encoders for Meta-Learning
Meta-learning aims to learn models that can make quick adaptations to new tasks. However, due to the lack of data, the further improvement of meta-learning can be severely constrained. Since, data augmentation...
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Chapter and Conference Paper
Efficient Subhypergraph Containment Queries on Hypergraph Databases
In the real world, many complex systems consist of a large number of interacting groups of entities. A hypergraph consists of vertices and hyperedges that can connect multiple vertices. Since hypergraphs can e...
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Chapter and Conference Paper
IncreGNN: Incremental Graph Neural Network Learning by Considering Node and Parameter Importance
Graph Neural Network (GNN) has shown powerful learning and reasoning ability. However, graphs in the real world generally exist dynamically, i.e., the topological structure of graphs is constantly evolving ove...
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Chapter and Conference Paper
WAE \(_{-}\) RN: Integrating Wasserstein Autoencoder and Relational Network for Text Sequence
One challenge in Natural Language Processing (NLP) area is to learn semantic representation in different contexts. Recent works on pre-trained language model have received great attentions and have been proven...
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Chapter and Conference Paper
Efficient Closeness Centrality Computation for Dynamic Graphs
As a classic metric, closeness centrality can measure the importance of a node in a graph by its proximity to the other nodes. However, exactly calculating closeness centrality of all nodes is significantly ti...
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Chapter and Conference Paper
Spatiotemporal Evolution Simulation of Volcanic Ash Cloud from Remote Sensing Image
Aiming at the dynamic monitoring and diffusion forecasting of volcanic ash cloud, this paper presents a new spatiotemporal evolution simulation method of volcanic ash cloud from the satellite remote sensing im...
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Chapter and Conference Paper
Tracking Algorithm Based on Dual Residual Network and Kernel Correlation Filters
Visual target tracking is a target detection task for a period of t...
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Chapter and Conference Paper
Robust Multi-view Features Fusion Method Based on CNMF
Multi-view feature fusion should be expected to mine implicit nature relationships among multiple views and effectively combine the data presented by multiple views to obtain the new feature representation of ...
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Chapter and Conference Paper
Unsupervised Ensemble Learning Based on Graph Embedding for Image Clustering
Manifold learning has attracted more and more attention in machine learning for past decades. Unsupervised Large Graph Embedding (ULGE), which performs well on the large-scale data, has been proposed for manif...
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Chapter and Conference Paper
Laplace Exponential Family PCA
Considering numerous types of data, this paper discusses application of PCA to exponential family distributions. Reviewing the probabilistic basis of PCA, we propose a model using Laplace approximation, which...
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Chapter and Conference Paper
Exploring Latent Bundles from Social Behaviors for Personalized Ranking
Users in social networks usually have different interpersonal relationships and various social roles. It is common that a user will synthesize all of his/her roles before taking any action. Understanding how p...
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Chapter and Conference Paper
Modeling Complementary Relationships of Cross-Category Products for Personal Ranking
The category of the product acts as the label of the product. It also exemplifies users various needs and tastes. In the existing recommender systems, the focus is on similar products recommendation with littl...
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Chapter and Conference Paper
Iterative Local Hyperlinear Learning Based Relief for Feature Weight Estimation
Feature weighting is considered as an important machine learning approach to deal with the problem of estimating the quality of attributes for pattern classification applications. Local Hyperlinear Learning ba...
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Chapter and Conference Paper
An Altered Kernel Transformation for Time Series Classification
Motivated by the great efficiency of dynamic time war** (DTW) for time series similarity measure, a Gaussian DTW (GDTW) kernel has been developed for time series classification. This paper proposes an altere...
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Chapter and Conference Paper
Context Enhanced Word Vectors for Sentiment Analysis
Word vectors have become very important features for sentiment analysis. The aim of this paper is to encode sentimental context into pre-trained word vectors for sentiment analysis. The negation and intensity ...
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Chapter and Conference Paper
Consensus Based Distributed Reinforcement Learning for Nonconvex Economic Power Dispatch in Microgrids
A common assumption for economic power dispatch (EPD) is a perfect knowledge of cost functions. However, this assumption can be violated in cases when it is too difficult to establish an accurate model of the ...
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Chapter and Conference Paper
Co-clustering with Manifold and Double Sparse Representation
Clustering is a fundamental tool that has been applied in dealing with huge volumes of text documents and images. For extracting relevant information from the enormous volumes of available data, some co-cluste...
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Chapter and Conference Paper
Location-Based Top-k Term Querying over Sliding Window
In part due to the proliferation of GPS-equipped mobile devices, massive svolumes of geo-tagged streaming text messages are becoming available on social media. It is of great interest to discover most frequent...
