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09/11/2023
Fully-Connected Spatial-Temporal Graph for Multivariate Time Series Data
Multivariate Time-Series (MTS) data is crucial in various application fi...
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09/11/2023
Graph Contextual Contrasting for Multivariate Time Series Classification
Contrastive learning, as a self-supervised learning paradigm, becomes po...
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09/06/2023
Energy stable and maximum bound principle preserving schemes for the Q-tensor flow of liquid crystals
In this paper, we propose two efficient fully-discrete schemes for Q-ten...
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08/21/2023
Efficient Joint Optimization of Layer-Adaptive Weight Pruning in Deep Neural Networks
In this paper, we propose a novel layer-adaptive weight-pruning approach...
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08/18/2023
Unlimited Knowledge Distillation for Action Recognition in the Dark
Dark videos often lose essential information, which causes the knowledge...
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07/14/2023
Source-Free Domain Adaptation with Temporal Imputation for Time Series Data
Source-free domain adaptation (SFDA) aims to adapt a pretrained model fr...
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07/07/2023
Distilling Universal and Joint Knowledge for Cross-Domain Model Compression on Time Series Data
For many real-world time series tasks, the computational complexity of p...
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07/06/2023
On efficient linear and fully decoupled finite difference method for wormhole propagation with heat transmission process on staggered grids
In this paper, we construct an efficient linear and fully decoupled fini...
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05/15/2023
SemiGNN-PPI: Self-Ensembling Multi-Graph Neural Network for Efficient and Generalizable Protein-Protein Interaction Prediction
Protein-protein interactions (PPIs) are crucial in various biological pr...
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05/13/2023
A Federated Learning-based Industrial Health Prognostics for Heterogeneous Edge Devices using Matched Feature Extraction
Data-driven industrial health prognostics require rich training data to ...
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05/07/2023
Shall We Trust All Relational Tuples by Open Information Extraction? A Study on Speculation Detection
Open Information Extraction (OIE) aims to extract factual relational tup...
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05/05/2023
Open Information Extraction via Chunks
Open Information Extraction (OIE) aims to extract relational tuples from...
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04/22/2023
A novel energy-optimal scalar auxiliary variable (EOP-SAV) approach for gradient flows
In recent years, the scalar auxiliary variable (SAV) approach has become...
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03/18/2023
Confidence Attention and Generalization Enhanced Distillation for Continuous Video Domain Adaptation
Continuous Video Domain Adaptation (CVDA) is a scenario where a source m...
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03/18/2023
Augmenting and Aligning Snippets for Few-Shot Video Domain Adaptation
For video models to be transferred and applied seamlessly across video t...
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03/01/2023
Efficient and accurate exponential SAV algorithms with relaxation for dissipative system
In this paper, we construct two kinds of exponential SAV approach with r...
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02/13/2023
Label-efficient Time Series Representation Learning: A Review
The scarcity of labeled data is one of the main challenges of applying d...
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01/04/2023
Error estimate of a consistent splitting GSAV scheme for the Navier-Stokes equations
We carry out a rigorous error analysis of the first-order semi-discrete ...
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12/05/2022
Syntactic Multi-view Learning for Open Information Extraction
Open Information Extraction (OpenIE) aims to extract relational tuples f...
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12/03/2022
CoTMix: Contrastive Domain Adaptation for Time-Series via Temporal Mixup
Unsupervised Domain Adaptation (UDA) has emerged as a powerful solution ...
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11/17/2022
Video Unsupervised Domain Adaptation with Deep Learning: A Comprehensive Survey
Video analysis tasks such as action recognition have received increasing...
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10/06/2022
A novel Lagrange Multiplier approach with relaxation for gradient flows
In this paper, we propose a novel Lagrange Multiplier approach, named ze...
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08/13/2022
Self-supervised Contrastive Representation Learning for Semi-supervised Time-Series Classification
Learning time-series representations when only unlabeled data or few lab...
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08/10/2022
EXTERN: Leveraging Endo-Temporal Regularization for Black-box Video Domain Adaptation
To enable video models to be applied seamlessly across video tasks in di...
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05/08/2022
A Survey on AI Sustainability: Emerging Trends on Learning Algorithms and Research Challenges
Artificial Intelligence (AI) is a fast-growing research and development ...
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05/02/2022
Type-aware Embeddings for Multi-Hop Reasoning over Knowledge Graphs
Multi-hop reasoning over real-life knowledge graphs (KGs) is a highly ch...
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04/13/2022
Highly efficient exponential scalar auxiliary variable approaches with relaxation (RE-SAV) for gradient flows
For the past few years, scalar auxiliary variable (SAV) and SAV-type app...
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03/30/2022
Slow-varying Dynamics Assisted Temporal Capsule Network for Machinery Remaining Useful Life Estimation
Capsule network (CapsNet) acts as a promising alternative to the typical...
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03/15/2022
ADATIME: A Benchmarking Suite for Domain Adaptation on Time Series Data
Unsupervised domain adaptation methods aim to generalize well on unlabel...
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02/19/2022
Going Deeper into Recognizing Actions in Dark Environments: A Comprehensive Benchmark Study
While action recognition (AR) has gained large improvements with the int...
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11/29/2021
Self-supervised Autoregressive Domain Adaptation for Time Series Data
Unsupervised domain adaptation (UDA) has successfully addressed the doma...
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08/15/2021
Two Eyes Are Better Than One: Exploiting Binocular Correlation for Diabetic Retinopathy Severity Grading
Diabetic retinopathy (DR) is one of the most common eye conditions among...
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08/01/2021
A Decentralized Federated Learning Framework via Committee Mechanism with Convergence Guarantee
Federated learning allows multiple participants to collaboratively train...
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07/09/2021
Adversarial Domain Adaptation with Self-Training for EEG-based Sleep Stage Classification
Sleep staging is of great importance in the diagnosis and treatment of s...
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06/30/2021
A Conditional Splitting Framework for Efficient Constituency Parsing
We introduce a generic seq2seq parsing framework that casts constituency...
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06/26/2021
Time-Series Representation Learning via Temporal and Contextual Contrasting
Learning decent representations from unlabeled time-series data with tem...
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06/16/2021
Multilinear Dirichlet Processes
Dependent Dirichlet processes (DDP) have been widely applied to model da...
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06/15/2021
CODA: Constructivism Learning for Instance-Dependent Dropout Architecture Construction
Dropout is attracting intensive research interest in deep learning as an...
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05/23/2021
RST Parsing from Scratch
We introduce a novel top-down end-to-end formulation of document-level d...
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05/10/2021
DocOIE: A Document-level Context-Aware Dataset for OpenIE
Open Information Extraction (OpenIE) aims to extract structured relation...
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04/01/2021
Stability and error analysis of IMEX SAV schemes for the magneto-hydrodynamic equations
We construct and analyze first- and second-order implicit-explicit (IMEX...
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02/17/2021
DO-GAN: A Double Oracle Framework for Generative Adversarial Networks
In this paper, we propose a new approach to train Generative Adversarial...
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02/06/2021
FFConv: Fast Factorized Neural Network Inference on Encrypted Data
Homomorphic Encryption (HE), allowing computations on encrypted data (ci...
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10/29/2020
Sea-Net: Squeeze-And-Excitation Attention Net For Diabetic Retinopathy Grading
Diabetes is one of the most common disease in individuals. Diabetic reti...
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10/19/2020
A highly efficient and accurate exponential semi-implicit scalar auxiliary variable (ESI-SAV) approach for dissipative system
The scalar auxiliary variable (SAV) approach is a very popular and effic...
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09/20/2020
On fully decoupled MSAV schemes for the Cahn-Hilliard-Navier-Stokes model of Two-Phase Incompressible Flows
We construct first- and second-order time discretization schemes for the...
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07/20/2020
Attention Sequence to Sequence Model for Machine Remaining Useful Life Prediction
Accurate estimation of remaining useful life (RUL) of industrial equipme...
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06/24/2020
Differentiable Window for Dynamic Local Attention
We propose Differentiable Window, a new neural module and general purpos...
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06/24/2020
Efficient Constituency Parsing by Pointing
We propose a novel constituency parsing model that casts the parsing pro...
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05/17/2020
