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08/24/2023
Understanding Container-based Services under Software Aging: Dependability and Performance Views
Container technology, as the key enabler behind microservice architectur...
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08/24/2023
Towards Semi-Markov Model-based Dependability Evaluation of VM-based Multi-Domain Service Function Chain
In NFV networks, service functions (SFs) can be deployed on virtual mach...
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06/16/2023
Parameter-efficient is not sufficient: Exploring Parameter, Memory, and Time Efficient Adapter Tuning for Dense Predictions
Pre-training fine-tuning is a prevalent paradigm in computer vision ...
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06/13/2023
Time-aware Graph Structure Learning via Sequence Prediction on Temporal Graphs
Temporal Graph Learning, which aims to model the time-evolving nature of...
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04/19/2023
AdapterGNN: Efficient Delta Tuning Improves Generalization Ability in Graph Neural Networks
Fine-tuning pre-trained models has recently yielded remarkable performan...
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01/26/2022
An Automated Question-Answering Framework Based on Evolution Algorithm
Building a deep learning model for a Question-Answering (QA) task requir...
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01/02/2022
Decoding Nonbinary LDPC Codes via Proximal-ADMM Approach (include convergence proofs)
In this paper, we focus on decoding nonbinary low-density parity-check (...
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10/07/2021
Creating Training Sets via Weak Indirect Supervision
Creating labeled training sets has become one of the major roadblocks in...
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10/03/2021
Graph Pointer Neural Networks
Graph Neural Networks (GNNs) have shown advantages in various graph-base...
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09/05/2021
Attentive Knowledge-aware Graph Convolutional Networks with Collaborative Guidance for Recommendation
To alleviate data sparsity and cold-start problems of traditional recomm...
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07/19/2021
Adaptive Transfer Learning on Graph Neural Networks
Graph neural networks (GNNs) is widely used to learn a powerful represen...
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03/13/2021
Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting
Multivariate time-series forecasting plays a crucial role in many real-w...
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03/07/2021
Syntax-BERT: Improving Pre-trained Transformers with Syntax Trees
Pre-trained language models like BERT achieve superior performances in v...
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10/19/2020
Proximal-ADMM Decoder for Nonbinary LDPC Codes
In this paper, we develop an efficient decoder via the proximal alternat...
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10/14/2020
AutoADR: Automatic Model Design for Ad Relevance
Large-scale pre-trained models have attracted extensive attention in the...
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09/04/2020
Multivariate Time-series Anomaly Detection via Graph Attention Network
Anomaly detection on multivariate time-series is of great importance in ...
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04/08/2020
LadaBERT: Lightweight Adaptation of BERT through Hybrid Model Compression
BERT is a cutting-edge language representation model pre-trained by a la...
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04/08/2020
Improving BERT with Self-Supervised Attention
One of the most popular paradigms of applying large, pre-trained NLP mod...
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12/23/2019
TextNAS: A Neural Architecture Search Space tailored for Text Representation
Learning text representation is crucial for text classification and othe...
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11/21/2019
Customized Graph Embedding: Tailoring the Embedding Vector to a Specific Application
The graph is a natural representation of data in a variety of real-world...
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10/28/2019
Efficient QP-ADMM Decoder for Binary LDPC Codes and Its Performance Analysis
This paper presents an efficient quadratic programming (QP) decoder via ...
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01/23/2019
