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09/19/2023
Revisiting and Improving Retrieval-Augmented Deep Assertion Generation
Unit testing validates the correctness of the unit under test and has be...
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08/16/2023
TEST: Text Prototype Aligned Embedding to Activate LLM's Ability for Time Series
This work summarizes two strategies for completing time-series (TS) task...
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01/27/2023
Data Volume-aware Computation Task Scheduling for Smart Grid Data Analytic Applications
Emerging smart grid applications analyze large amounts of data collected...
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01/23/2023
Online Network Slicing for Real Time Applications in Large-scale Satellite Networks
In this work, we investigate resource allocation strategy for real time ...
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12/11/2022
A model-data asymptotic-preserving neural network method based on micro-macro decomposition for gray radiative transfer equations
We propose a model-data asymptotic-preserving neural network(MD-APNN) me...
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11/12/2022
Enhancing Resource Utilization of Non-terrestrial Networks Using Temporal Graph-based Deterministic Routing
Non-terrestrial networks (NTNs) are expected to provide continuous and u...
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10/06/2022
Continuous Diagnosis and Prognosis by Controlling the Update Process of Deep Neural Networks
Continuous diagnosis and prognosis are essential for intensive care pati...
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09/23/2022
Optimal Job Scheduling and Bandwidth Augmentation in Hybrid Data Center Networks
Optimizing data transfers is critical for improving job performance in d...
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08/14/2022
Confidence-Guided Learning Process for Continuous Classification of Time Series
In the real world, the class of a time series is usually labeled at the ...
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03/20/2022
Optical Flow for Video Super-Resolution: A Survey
Video super-resolution is currently one of the most active research topi...
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02/24/2022
Slow-Fast Visual Tempo Learning for Video-based Action Recognition
Action visual tempo characterizes the dynamics and the temporal scale of...
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02/08/2022
Joint-bone Fusion Graph Convolutional Network for Semi-supervised Skeleton Action Recognition
In recent years, graph convolutional networks (GCNs) play an increasingl...
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08/31/2021
GRP-FED: Addressing Client Imbalance in Federated Learning via Global-Regularized Personalization
Since data is presented long-tailed in reality, it is challenging for Fe...
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05/02/2021
TE-ESN: Time Encoding Echo State Network for Prediction Based on Irregularly Sampled Time Series Data
Prediction based on Irregularly Sampled Time Series (ISTS) is of wide co...
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12/30/2020
Robustness Testing of Language Understanding in Dialog Systems
Most language understanding models in dialog systems are trained on a sm...
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12/05/2020
A Review of Designs and Applications of Echo State Networks
Recurrent Neural Networks (RNNs) have demonstrated their outstanding abi...
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10/23/2020
A Review of Deep Learning Methods for Irregularly Sampled Medical Time Series Data
Irregularly sampled time series (ISTS) data has irregular temporal inter...
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05/27/2019
MINA: Multilevel Knowledge-Guided Attention for Modeling Electrocardiography Signals
Electrocardiography (ECG) signals are commonly used to diagnose various ...
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05/15/2019
Time-Varying Downlink Channel Tracking for Quantized Massive MIMO Networks
This paper proposes a Bayesian downlink channel estimation algorithm for...
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09/06/2018
RDPD: Rich Data Helps Poor Data via Imitation
In many situations, we have both rich- and poor- data environments: in a...
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09/06/2018
GAMENet: Graph Augmented MEmory Networks for Recommending Medication Combination
Recent progress in deep learning is revolutionizing the healthcare domai...
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11/26/2017