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08/18/2023
Towards Understanding the Generalizability of Delayed Stochastic Gradient Descent
Stochastic gradient descent (SGD) performed in an asynchronous manner pl...
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08/17/2023
MV-ROPE: Multi-view Constraints for Robust Category-level Object Pose and Size Estimation
We propose a novel framework for RGB-based category-level 6D object pose...
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08/07/2023
DSformer: A Double Sampling Transformer for Multivariate Time Series Long-term Prediction
Multivariate time series long-term prediction, which aims to predict the...
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07/23/2023
Scale jump-aware pose graph relaxation for monocular SLAM with re-initializations
Pose graph relaxation has become an indispensable addition to SLAM enabl...
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06/15/2023
Network Architecture Design toward Convergence of Mobile Applications and Networks
With the quick proliferation of extended reality (XR) services, the mobi...
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05/23/2023
Temporal Contrastive Learning for Spiking Neural Networks
Biologically inspired spiking neural networks (SNNs) have garnered consi...
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05/06/2023
Synthesizing PET images from High-field and Ultra-high-field MR images Using Joint Diffusion Attention Model
MRI and PET are crucial diagnostic tools for brain diseases, as they pro...
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04/20/2023
Efficient Uncertainty Estimation in Spiking Neural Networks via MC-dropout
Spiking neural networks (SNNs) have gained attention as models of sparse...
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03/27/2023
Mask and Restore: Blind Backdoor Defense at Test Time with Masked Autoencoder
Deep neural networks are vulnerable to backdoor attacks, where an advers...
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02/14/2023
Hybrid Spiking Neural Network Fine-tuning for Hippocampus Segmentation
Over the past decade, artificial neural networks (ANNs) have made tremen...
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01/29/2023
Towards Vision Transformer Unrolling Fixed-Point Algorithm: a Case Study on Image Restoration
The great success of Deep Neural Networks (DNNs) has inspired the algori...
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11/22/2022
Backdoor Cleansing with Unlabeled Data
Due to the increasing computational demand of Deep Neural Networks (DNNs...
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10/12/2022
Individualized Conditioning and Negative Distances for Speaker Separation
Speaker separation aims to extract multiple voices from a mixed signal. ...
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08/26/2022
Local Context-Aware Active Domain Adaptation
Active Domain Adaptation (ADA) queries the label of selected target samp...
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08/26/2022
Domain Adaptation with Adversarial Training on Penultimate Activations
Enhancing model prediction confidence on unlabeled target data is an imp...
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08/11/2022
Adaptive and Implicit Regularization for Matrix Completion
The explicit low-rank regularization, e.g., nuclear norm regularization,...
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07/18/2022
Prior Knowledge Guided Unsupervised Domain Adaptation
The waive of labels in the target domain makes Unsupervised Domain Adapt...
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06/16/2022
SHIFT: A Synthetic Driving Dataset for Continuous Multi-Task Domain Adaptation
Adapting to a continuously evolving environment is a safety-critical cha...
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05/25/2022
Spotlights: Probing Shapes from Spherical Viewpoints
Recent years have witnessed the surge of learned representations that di...
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05/12/2022
S3E-GNN: Sparse Spatial Scene Embedding with Graph Neural Networks for Camera Relocalization
Camera relocalization is the key component of simultaneous localization ...
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04/28/2022
Unsupervised Voice-Face Representation Learning by Cross-Modal Prototype Contrast
We present an approach to learn voice-face representations from the talk...
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04/16/2022
Safe Self-Refinement for Transformer-based Domain Adaptation
Unsupervised Domain Adaptation (UDA) aims to leverage a label-rich sourc...
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12/08/2021
SASG: Sparsification with Adaptive Stochastic Gradients for Communication-efficient Distributed Learning
Stochastic optimization algorithms implemented on distributed computing ...
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10/18/2021
Training Deep Neural Networks with Adaptive Momentum Inspired by the Quadratic Optimization
Heavy ball momentum is crucial in accelerating (stochastic) gradient-bas...
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10/04/2021
Deep Learning Approach Protecting Privacy in Camera-Based Critical Applications
Many critical applications rely on cameras to capture video footage for ...
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07/01/2021
On the Practicality of Deterministic Epistemic Uncertainty
A set of novel approaches for estimating epistemic uncertainty in deep n...
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06/18/2021
Trend estimation and short-term forecasting of COVID-19 cases and deaths worldwide
Since the beginning of the COVID-19 pandemic, many dashboards have emerg...
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04/23/2021
Decentralized Federated Averaging
Federated averaging (FedAvg) is a communication efficient algorithm for ...
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02/02/2021
Stability and Generalization of the Decentralized Stochastic Gradient Descent
The stability and generalization of stochastic gradient-based methods pr...
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01/30/2021
Inertial Proximal Deep Learning Alternating Minimization for Efficient Neutral Network Training
In recent years, the Deep Learning Alternating Minimization (DLAM), whic...
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12/31/2020
Three-quarter Sibling Regression for Denoising Observational Data
Many ecological studies and conservation policies are based on field obs...
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11/24/2020
REPAINT: Knowledge Transfer in Deep Actor-Critic Reinforcement Learning
Accelerating the learning processes for complex tasks by leveraging prev...
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07/30/2020
End-to-end Full Projector Compensation
Full projector compensation aims to modify a projector input image to co...
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06/12/2020
FedGAN: Federated Generative Adversarial Networks for Distributed Data
We propose Federated Generative Adversarial Network (FedGAN) for trainin...
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06/12/2020
FedGAN: Federated Generative AdversarialNetworks for Distributed Data
We propose Federated Generative Adversarial Network (FedGAN) for trainin...
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02/20/2020
Adaptive Temporal Difference Learning with Linear Function Approximation
This paper revisits the celebrated temporal difference (TD) learning alg...
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01/02/2020
Zero-Shot Reinforcement Learning with Deep Attention Convolutional Neural Networks
Simulation-to-simulation and simulation-to-real world transfer of neural...
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11/05/2019
DeepRacer: Educational Autonomous Racing Platform for Experimentation with Sim2Real Reinforcement Learning
DeepRacer is a platform for end-to-end experimentation with RL and can b...
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10/11/2019
General Proximal Incremental Aggregated Gradient Algorithms: Better and Novel Results under General Scheme
The incremental aggregated gradient algorithm is popular in network opti...
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09/23/2019
Decentralized Markov Chain Gradient Descent
Decentralized stochastic gradient method emerges as a promising solution...
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07/27/2019
Dilated FCN: Listening Longer to Hear Better
Deep neural network solutions have emerged as a new and powerful paradig...
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07/27/2019
Inertial nonconvex alternating minimizations for the image deblurring
In image processing, Total Variation (TV) regularization models are comm...
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07/23/2019
Heavy-ball Algorithms Always Escape Saddle Points
Nonconvex optimization algorithms with random initialization have attrac...
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05/04/2019
Leveraging Crowdsourced GPS Data for Road Extraction from Aerial Imagery
Deep learning is revolutionizing the mapping industry. Under lightweight...
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02/09/2019
Iteratively reweighted penalty alternating minimization methods with continuation for image deblurring
In this paper, we consider a class of nonconvex problems with linear con...
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01/09/2019
Trace-back Along Capsules and Its Application on Semantic Segmentation
In this paper, we propose a capsule-based neural network model to solve ...
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01/07/2019
Copula-based semiparametric transformation model for bivariate data under general interval censoring
This research is motivated by discovering and underpinning genetic cause...
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11/27/2018
Quality-Aware Multimodal Saliency Detection via Deep Reinforcement Learning
Incorporating various modes of information into the machine learning pro...
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11/22/2018
Markov Chain Block Coordinate Descent
The method of block coordinate gradient descent (BCD) has been a powerfu...
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11/05/2018