research
∙
07/28/2023
Multilingual Lexical Simplification via Paraphrase Generation
Lexical simplification (LS) methods based on pretrained language models ...
share
research
∙
06/28/2023
Multi-network Contrastive Learning Based on Global and Local Representations
The popularity of self-supervised learning has made it possible to train...
research
∙
06/16/2023
Clickbait Detection via Large Language Models
Clickbait, which aims to induce users with some surprising and even thri...
research
∙
05/30/2023
Beyond One-Model-Fits-All: A Survey of Domain Specialization for Large Language Models
Large language models (LLMs) have significantly advanced the field of na...
research
∙
05/30/2023
Graph Neural Network for spatiotemporal data: methods and applications
In the era of big data, there has been a surge in the availability of da...
research
∙
05/23/2023
Constructions of Constant Dimension Subspace Codes
Subspace codes have important applications in random network coding. It ...
research
∙
05/14/2023
ParaLS: Lexical Substitution via Pretrained Paraphraser
Lexical substitution (LS) aims at finding appropriate substitutes for a ...
research
∙
05/09/2023
MSVQ: Self-Supervised Learning with Multiple Sample Views and Queues
Self-supervised methods based on contrastive learning have achieved grea...
research
∙
04/30/2023
Multi-directional Sobel operator kernel on GPUs
Sobel is one of the most popular edge detection operators used in image ...
research
∙
04/06/2023
Synthetic Hard Negative Samples for Contrastive Learning
Contrastive learning has emerged as an essential approach for self-super...
research
∙
03/01/2023
Distilled Reverse Attention Network for Open-world Compositional Zero-Shot Learning
Open-World Compositional Zero-Shot Learning (OW-CZSL) aims to recognize ...
research
∙
02/25/2023
Scalable Attribution of Adversarial Attacks via Multi-Task Learning
Deep neural networks (DNNs) can be easily fooled by adversarial attacks ...
research
∙
02/23/2023
Sentence Simplification via Large Language Models
Sentence Simplification aims to rephrase complex sentences into simpler ...
research
∙
02/22/2023
PAD: Towards Principled Adversarial Malware Detection Against Evasion Attacks
Machine Learning (ML) techniques facilitate automating malicious softwar...
research
∙
12/27/2022
Weak Signal Inclusion Under Dependence and Applications in Genome-wide Association Study
Motivated by the inquiries of weak signals in underpowered genome-wide a...
research
∙
11/05/2022
Simple Primitives with Feasibility- and Contextuality-Dependence for Open-World Compositional Zero-shot Learning
The task of Compositional Zero-Shot Learning (CZSL) is to recognize imag...
research
∙
10/14/2022
Generative Adversarial Learning for Trusted and Secure Clustering in Industrial Wireless Sensor Networks
Traditional machine learning techniques have been widely used to establi...
research
∙
10/03/2022
Deep Spatial Domain Generalization
Spatial autocorrelation and spatial heterogeneity widely exist in spatia...
research
∙
08/02/2022
Generative Adversarial Learning for Intelligent Trust Management in 6G Wireless Networks
Emerging six generation (6G) is the integration of heterogeneous wireles...
research
∙
05/03/2022
Disentangled and Side-aware Unsupervised Domain Adaptation for Cross-dataset Subjective Tinnitus Diagnosis
EEG-based tinnitus classification is a valuable tool for tinnitus diagno...
research
∙
05/03/2022
Side-aware Meta-Learning for Cross-Dataset Listener Diagnosis with Subjective Tinnitus
With the development of digital technology, machine learning has paved t...
research
∙
02/23/2022
Prompt-Learning for Short Text Classification
In the short text, the extreme short length, feature sparsity and high a...
research
∙
01/06/2022
Balancing Generalization and Specialization in Zero-shot Learning
Zero-Shot Learning (ZSL) aims to transfer classification capability from...
research
∙
12/05/2021
Boosting Mobile CNN Inference through Semantic Memory
Human brains are known to be capable of speeding up visual recognition o...
research
∙
12/01/2021
Rethink, Revisit, Revise: A Spiral Reinforced Self-Revised Network for Zero-Shot Learning
Current approaches to Zero-Shot Learning (ZSL) struggle to learn general...
research
∙
11/03/2021
An Entropy-guided Reinforced Partial Convolutional Network for Zero-Shot Learning
Zero-Shot Learning (ZSL) aims to transfer learned knowledge from observe...
research
∙
09/01/2021
An Unsupervised Method for Building Sentence Simplification Corpora in Multiple Languages
The availability of parallel sentence simplification (SS) is scarce for ...
research
∙
06/02/2021
DeepCompress: Efficient Point Cloud Geometry Compression
Point clouds are a basic data type that is increasingly of interest as 3...
research
∙
05/26/2021
Cyclic subspace codes via the sum of Sidon spaces
Subspace codes, especially cyclic constant subspace codes, are of great ...
research
∙
04/22/2021
Attribute-Modulated Generative Meta Learning for Zero-Shot Classification
Zero-shot learning (ZSL) aims to transfer knowledge from seen classes to...
research
∙
03/03/2021
Task Aligned Generative Meta-learning for Zero-shot Learning
Zero-shot learning (ZSL) refers to the problem of learning to classify i...
research
∙
10/14/2020
Chinese Lexical Simplification
Lexical simplification has attracted much attention in many languages, w...
research
∙
10/11/2020
Is It Time to Redefine the Classification Task for Deep Neural Networks?
Deep neural networks (DNNs) is demonstrated to be vulnerable to the adve...
research
∙
08/10/2020
Using Multiple Imputation to Classify Potential Outcomes Subgroups
With medical tests becoming increasingly available, concerns about over-...
research
∙
07/04/2020
Weight-dependent Gates for Network Pruning
In this paper, we propose a simple and effective network pruning framewo...
research
∙
06/25/2020
LSBert: A Simple Framework for Lexical Simplification
Lexical simplification (LS) aims to replace complex words in a given sen...
research
∙
05/19/2020
The Impact of Unmeasured Within- and Between-Cluster Confounding on the Bias of Effect Estimators from Fixed Effect, Mixed effect and Instrumental Variable Models
Instrumental variable methods are popular choices in combating unmeasure...
research
∙
05/19/2020
Matching methods for obtaining survival functions to estimate the effect of a time-dependent treatment
In observational studies of survival time featuring a binary time-depend...
research
∙
05/12/2020
Agglomerative Neural Networks for Multi-view Clustering
Conventional multi-view clustering methods seek for a view consensus thr...
research
∙
07/14/2019
A Simple BERT-Based Approach for Lexical Simplification
Lexical simplification (LS) aims to replace complex words in a given sen...
research
∙
06/19/2019
A simple and effective postprocessing method for image classification
Whether it is computer vision, natural language processing or speech rec...
research
∙
01/16/2019
Exploring Communities in Large Profiled Graphs
Given a graph G and a vertex q∈ G, the community search (CS) problem aim...
research
∙
08/07/2018
STTM: A Tool for Short Text Topic Modeling
Along with the emergence and popularity of social communications on the ...
research
∙
10/24/2017
Improving Brain Storm Optimization Algorithm via Simplex Search
Through modeling human's brainstorming process, the brain storm optimiza...
research
∙
03/09/2015