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09/09/2023
Training of Spiking Neural Network joint Curriculum Learning Strategy
Starting with small and simple concepts, and gradually introducing compl...
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07/31/2023
A Pre-trained Data Deduplication Model based on Active Learning
In the era of big data, the issue of data quality has become increasingl...
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05/22/2023
Hi-ResNet: A High-Resolution Remote Sensing Network for Semantic Segmentation
High-resolution remote sensing (HRS) semantic segmentation extracts key ...
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03/20/2023
Revisiting Realistic Test-Time Training: Sequential Inference and Adaptation by Anchored Clustering Regularized Self-Training
Deploying models on target domain data subject to distribution shift req...
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11/27/2022
SegCLIP: Patch Aggregation with Learnable Centers for Open-Vocabulary Semantic Segmentation
Recently, the contrastive language-image pre-training, e.g., CLIP, has d...
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08/29/2022
A Missing Value Filling Model Based on Feature Fusion Enhanced Autoencoder
With the advent of the big data era, the data quality problem is becomin...
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08/20/2022
C^2IMUFS: Complementary and Consensus Learning-based Incomplete Multi-view Unsupervised Feature Selection
Multi-view unsupervised feature selection (MUFS) has been demonstrated a...
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06/11/2022
DRAformer: Differentially Reconstructed Attention Transformer for Time-Series Forecasting
Time-series forecasting plays an important role in many real-world scena...
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04/06/2022
Spatio-Temporal Dynamic Graph Relation Learning for Urban Metro Flow Prediction
Urban metro flow prediction is of great value for metro operation schedu...
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04/05/2022
Incremental Unsupervised Feature Selection for Dynamic Incomplete Multi-view Data
Multi-view unsupervised feature selection has been proven to be efficien...
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02/25/2022
Spatio-Temporal Latent Graph Structure Learning for Traffic Forecasting
Accurate traffic forecasting, the foundation of intelligent transportati...
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02/23/2022
A Differential Attention Fusion Model Based on Transformer for Time Series Forecasting
Time series forecasting is widely used in the fields of equipment life c...
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01/22/2022
HiSTGNN: Hierarchical Spatio-temporal Graph Neural Networks for Weather Forecasting
Weather Forecasting is an attractive challengeable task due to its influ...
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12/14/2021
Unsupervised feature selection via self-paced learning and low-redundant regularization
Much more attention has been paid to unsupervised feature selection nowa...
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12/02/2021
ScaleVLAD: Improving Multimodal Sentiment Analysis via Multi-Scale Fusion of Locally Descriptors
Fusion technique is a key research topic in multimodal sentiment analysi...
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04/18/2021
CLIP4Clip: An Empirical Study of CLIP for End to End Video Clip Retrieval
Video-text retrieval plays an essential role in multi-modal research and...
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12/27/2020
Adaptive Graph-based Generalized Regression Model for Unsupervised Feature Selection
Unsupervised feature selection is an important method to reduce dimensio...
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12/18/2020
Fairness and Accuracy in Federated Learning
In the federated learning setting, multiple clients jointly train a mode...
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09/29/2020
MaP: A Matrix-based Prediction Approach to Improve Span Extraction in Machine Reading Comprehension
Span extraction is an essential problem in machine reading comprehension...
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09/22/2020
GRACE: Gradient Harmonized and Cascaded Labeling for Aspect-based Sentiment Analysis
In this paper, we focus on the imbalance issue, which is rarely studied ...
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05/04/2020
Distributional Discrepancy: A Metric for Unconditional Text Generation
The goal of unconditional text generation is training a model with real ...
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04/11/2020
Efficient Suspected Infected Crowds Detection Based on Spatio-Temporal Trajectories
Virus transmission from person to person is an emergency event facing th...
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03/13/2020
Minor Constraint Disturbances for Deep Semi-supervised Learning
In high-dimensional data space, semi-supervised feature learning based o...
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02/15/2020
UniViLM: A Unified Video and Language Pre-Training Model for Multimodal Understanding and Generation
We propose UniViLM: a Unified Video and Language pre-training Model for ...
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08/31/2019
Learning with Noisy Labels for Sentence-level Sentiment Classification
Deep neural networks (DNNs) can fit (or even over-fit) the training data...
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08/26/2019
Urban flows prediction from spatial-temporal data using machine learning: A survey
Urban spatial-temporal flows prediction is of great importance to traffi...
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06/12/2019
DCEF: Deep Collaborative Encoder Framework for Unsupervised Clustering
Collaborative representation is a popular feature learning approach, whi...
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06/05/2019
DOER: Dual Cross-Shared RNN for Aspect Term-Polarity Co-Extraction
This paper focuses on two related subtasks of aspect-based sentiment ana...
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12/22/2018
Deep Uncertainty Learning: A Machine Learning Approach for Weather Forecasting
This paper uses the weather forecasting as an application background to ...
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12/22/2018
Deep Prediction Interval for Weather Forecasting
Currently there exists a gap between deep learning and the techniques re...
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12/12/2018
Deep Air Quality Forecasting Using Hybrid Deep Learning Framework
Air quality forecasting has been regarded as the key problem of air poll...
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12/05/2018
Self-learning Local Supervision Encoding Framework to Constrict and Disperse Feature Distribution for Clustering
To obtain suitable feature distribution is a difficult task in machine l...
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05/21/2018
Improving Aspect Term Extraction with Bidirectional Dependency Tree Representation
Aspect term extraction is one of the important subtasks in aspect-based ...
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03/06/2018
A Hybrid Method for Traffic Flow Forecasting Using Multimodal Deep Learning
Traffic flow forecasting has been regarded as a key problem of intellige...
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11/22/2017
Three-Stream Convolutional Networks for Video-based Person Re-Identification
This paper aims to develop a new architecture that can make full use of ...
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10/08/2017
Reconstruction of Hidden Representation for Robust Feature Extraction
This paper aims to develop a new and robust approach to feature represen...
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01/10/2017
Predicting Citywide Crowd Flows Using Deep Spatio-Temporal Residual Networks
Forecasting the flow of crowds is of great importance to traffic managem...
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10/06/2016
