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08/08/2023
Low-complexity Resource Allocation for User Paired RSMA in Future 6G Wireless Networks
Rate-splitting multiple access (RSMA) uplink requires optimization of de...
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08/06/2023
Food-500 Cap: A Fine-Grained Food Caption Benchmark for Evaluating Vision-Language Models
Vision-language models (VLMs) have shown impressive performance in subst...
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08/02/2023
ADS-Cap: A Framework for Accurate and Diverse Stylized Captioning with Unpaired Stylistic Corpora
Generating visually grounded image captions with specific linguistic sty...
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08/02/2023
Beyond Generic: Enhancing Image Captioning with Real-World Knowledge using Vision-Language Pre-Training Model
Current captioning approaches tend to generate correct but "generic" des...
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05/11/2023
Numerical Stability for Differential Equations with Memory
In this work, we systematically investigate linear multi-step methods fo...
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04/03/2023
Laplace-fPINNs: Laplace-based fractional physics-informed neural networks for solving forward and inverse problems of subdiffusion
The use of Physics-informed neural networks (PINNs) has shown promise in...
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12/03/2022
Distribution Fitting for Combating Mode Collapse in GANs
Mode collapse is still a major unsolved problem in generative adversaria...
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11/30/2022
Measuring the Competitive Pressure of Academic Journals and the Competitive Intensity within Subjects
A journal's impact and similarity with rivals is closely related to its ...
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11/22/2022
Bayesian Inversion with Neural Operator (BINO) for Modeling Subdiffusion: Forward and Inverse Problems
Fractional diffusion equations have been an effective tool for modeling ...
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10/18/2022
Probing Cross-modal Semantics Alignment Capability from the Textual Perspective
In recent years, vision and language pre-training (VLP) models have adva...
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09/19/2022
MMF3: Neural Code Summarization Based on Multi-Modal Fine-Grained Feature Fusion
Background: Code summarization automatically generates the corresponding...
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08/13/2022
GEDI: A Graph-based End-to-end Data Imputation Framework
Data imputation is an effective way to handle missing data, which is com...
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06/18/2022
Off-Network Communications For Future Railway Mobile Communication Systems: Challenges and Opportunities
GSM-R is predicted to be obsoleted by 2030, and a suitable successor is ...
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05/27/2022
OpenCalib: A Multi-sensor Calibration Toolbox for Autonomous Driving
Accurate sensor calibration is a prerequisite for multi-sensor perceptio...
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05/07/2022
Unified Chinese License Plate Detection and Recognition with High Efficiency
Recently, deep learning-based methods have reached an excellent performa...
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04/12/2022
Cognitive Radio Inspired Uplink Rate-Splitting Multiple Access
With the exponential increase of the number of devices in the communicat...
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07/08/2021
MOD-Net: A Machine Learning Approach via Model-Operator-Data Network for Solving PDEs
In this paper, we propose a model-operator-data network (MOD-Net) for so...
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05/25/2021
An Upper Limit of Decaying Rate with Respect to Frequency in Deep Neural Network
Deep neural network (DNN) usually learns the target function from low to...
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03/23/2021
Unsupervised domain adaptation via coarse-to-fine feature alignment method using contrastive learning
Previous feature alignment methods in Unsupervised domain adaptation(UDA...
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03/02/2021
Network Pruning via Resource Reallocation
Channel pruning is broadly recognized as an effective approach to obtain...
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01/30/2021
Linear Frequency Principle Model to Understand the Absence of Overfitting in Neural Networks
Why heavily parameterized neural networks (NNs) do not overfit the data ...
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12/06/2020
Fourier-domain Variational Formulation and Its Well-posedness for Supervised Learning
A supervised learning problem is to find a function in a hypothesis func...
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10/15/2020
On the exact computation of linear frequency principle dynamics and its generalization
Recent works show an intriguing phenomenon of Frequency Principle (F-Pri...
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07/29/2020
Feedback Capacities of Gaussian Multiple-Access Wiretap Channels
The feedback capacities of the Gaussian multiple-access channel (GMAC) a...
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07/15/2020
Phase diagram for two-layer ReLU neural networks at infinite-width limit
How neural network behaves during the training over different choices of...
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06/29/2020
Path Integral Based Convolution and Pooling for Graph Neural Networks
Graph neural networks (GNNs) extends the functionality of traditional ne...
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04/11/2020
Inter-Region Affinity Distillation for Road Marking Segmentation
We study the problem of distilling knowledge from a large deep teacher n...
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03/03/2020
What's the relationship between CNNs and communication systems?
The interpretability of Convolutional Neural Networks (CNNs) is an impor...
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01/30/2020
Recent development in kinetic theory of granular materials: analysis and numerical methods
Over the past decades, kinetic description of granular materials has rec...
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12/30/2019
Defending from adversarial examples with a two-stream architecture
In recent years, deep learning has shown impressive performance on many ...
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11/21/2019
Decentralized Consensus Optimization Based on Parallel Random Walk
The alternating direction method of multipliers (ADMM) has recently been...
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09/25/2019
HaarPooling: Graph Pooling with Compressive Haar Basis
Deep Graph Neural Networks (GNNs) are instrumental in graph classificati...
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09/17/2019
STELA: A Real-Time Scene Text Detector with Learned Anchor
To achieve high coverage of target boxes, a normal strategy of conventio...
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08/29/2019
Focus-Enhanced Scene Text Recognition with Deformable Convolutions
Recently, scene text recognition methods based on deep learning have spr...
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08/02/2019
Learning Lightweight Lane Detection CNNs by Self Attention Distillation
Training deep models for lane detection is challenging due to the very s...
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07/10/2019
Haar Transforms for Graph Neural Networks
Graph Neural Networks (GNNs) have become a topic of intense research rec...
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06/21/2019
Theory of the Frequency Principle for General Deep Neural Networks
Along with fruitful applications of Deep Neural Networks (DNNs) to reali...
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05/31/2019
When Full Duplex Wireless Meets Non-Orthogonal Multiple Access: Opportunities and Challenges
Non-orthogonal multiple access (NOMA) is a promising radio access techno...
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05/24/2019
Explicitizing an Implicit Bias of the Frequency Principle in Two-layer Neural Networks
It remains a puzzle that why deep neural networks (DNNs), with more para...
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05/19/2019
A type of generalization error induced by initialization in deep neural networks
How different initializations and loss functions affect the learning of ...
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04/24/2019
PAN: Path Integral Based Convolution for Deep Graph Neural Networks
Convolution operations designed for graph-structured data usually utiliz...
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03/22/2019
Joint 3D Face Reconstruction and Dense Face Alignment from A Single Image with 2D-Assisted Self-Supervised Learning
3D face reconstruction from a single 2D image is a challenging problem w...
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02/25/2019
A Dual Symmetric Gauss-Seidel Alternating Direction Method of Multipliers for Hyperspectral Sparse Unmixing
Since sparse unmixing has emerged as a promising approach to hyperspectr...
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01/21/2019
Generating Text Sequence Images for Recognition
Recently, methods based on deep learning have dominated the field of tex...
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01/19/2019
Frequency Principle: Fourier Analysis Sheds Light on Deep Neural Networks
We study the training process of Deep Neural Networks (DNNs) from the Fo...
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01/17/2019
Enhance the Motion Cues for Face Anti-Spoofing using CNN-LSTM Architecture
Spatio-temporal information is very important to capture the discriminat...
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01/17/2019
Deep Transfer Across Domains for Face Anti-spoofing
A practical face recognition system demands not only high recognition pe...
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01/17/2019
Learning Generalizable and Identity-Discriminative Representations for Face Anti-Spoofing
Face anti-spoofing (a.k.a presentation attack detection) has drawn growi...
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12/21/2018
NADPEx: An on-policy temporally consistent exploration method for deep reinforcement learning
Reinforcement learning agents need exploratory behaviors to escape from ...
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11/07/2018
