b'Tao Sun'

research

∙ 05/23/2023

Temporal Contrastive Learning for Spiking Neural Networks

Biologically inspired spiking neural networks (SNNs) have garnered consi...

0 Haonan Qiu, et al. ∙

research

∙ 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...

0 Taofeng Xie, et al. ∙

research

∙ 04/20/2023

Efficient Uncertainty Estimation in Spiking Neural Networks via MC-dropout

Spiking neural networks (SNNs) have gained attention as models of sparse...

0 Tao Sun, et al. ∙

research

∙ 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...

0 Tao Sun, et al. ∙

research

∙ 02/14/2023

Hybrid Spiking Neural Network Fine-tuning for Hippocampus Segmentation

Over the past decade, artificial neural networks (ANNs) have made tremen...

0 Ye Yue, et al. ∙

research

∙ 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...

0 Peng Qiao, et al. ∙

research

∙ 11/22/2022

Backdoor Cleansing with Unlabeled Data

Due to the increasing computational demand of Deep Neural Networks (DNNs...

0 Lu Pang, et al. ∙

research

∙ 10/12/2022

Individualized Conditioning and Negative Distances for Speaker Separation

Speaker separation aims to extract multiple voices from a mixed signal. ...

0 Tao Sun, et al. ∙

research

∙ 08/26/2022

Local Context-Aware Active Domain Adaptation

Active Domain Adaptation (ADA) queries the label of selected target samp...

4 Tao Sun, et al. ∙

research

∙ 08/26/2022

Domain Adaptation with Adversarial Training on Penultimate Activations

Enhancing model prediction confidence on unlabeled target data is an imp...

7 Tao Sun, et al. ∙

research

∙ 08/11/2022

Adaptive and Implicit Regularization for Matrix Completion

The explicit low-rank regularization, e.g., nuclear norm regularization,...

33 Zhemin Li, et al. ∙

research

∙ 07/18/2022

Prior Knowledge Guided Unsupervised Domain Adaptation

The waive of labels in the target domain makes Unsupervised Domain Adapt...

6 Tao Sun, et al. ∙

research

∙ 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...

32 Tao Sun, et al. ∙

research

∙ 05/25/2022

Spotlights: Probing Shapes from Spherical Viewpoints

Recent years have witnessed the surge of learned representations that di...

3 Jiaxin Wei, et al. ∙

research

∙ 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 ...

14 Ran Cheng, et al. ∙

research

∙ 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...

7 Boqing Zhu, et al. ∙

research

∙ 04/16/2022

Safe Self-Refinement for Transformer-based Domain Adaptation

Unsupervised Domain Adaptation (UDA) aims to leverage a label-rich sourc...

3 Tao Sun, et al. ∙

research

∙ 12/08/2021

SASG: Sparsification with Adaptive Stochastic Gradients for Communication-efficient Distributed Learning

Stochastic optimization algorithms implemented on distributed computing ...

0 Xiaoge Deng, et al. ∙

research

∙ 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...

14 Tao Sun, et al. ∙

research

∙ 10/04/2021

Deep Learning Approach Protecting Privacy in Camera-Based Critical Applications

Many critical applications rely on cameras to capture video footage for ...

14 Gautham Ramajayam, et al. ∙

research

∙ 07/01/2021

On the Practicality of Deterministic Epistemic Uncertainty

A set of novel approaches for estimating epistemic uncertainty in deep n...

4 Janis Postels, et al. ∙

research

∙ 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...

0 Ekaterina Krymova, et al. ∙

research

∙ 04/23/2021

Decentralized Federated Averaging

Federated averaging (FedAvg) is a communication efficient algorithm for ...

11 Tao Sun, et al. ∙

research

∙ 02/02/2021

Stability and Generalization of the Decentralized Stochastic Gradient Descent

The stability and generalization of stochastic gradient-based methods pr...

23 Tao Sun, et al. ∙

research

∙ 01/30/2021

Inertial Proximal Deep Learning Alternating Minimization for Efficient Neutral Network Training

In recent years, the Deep Learning Alternating Minimization (DLAM), whic...

2 Linbo Qiao, et al. ∙

research

∙ 12/31/2020

Three-quarter Sibling Regression for Denoising Observational Data

Many ecological studies and conservation policies are based on field obs...

1 Shiv Shankar, et al. ∙

research

∙ 11/24/2020

REPAINT: Knowledge Transfer in Deep Actor-Critic Reinforcement Learning

Accelerating the learning processes for complex tasks by leveraging prev...

12 Yunzhe Tao, et al. ∙

research

∙ 07/30/2020

End-to-end Full Projector Compensation

Full projector compensation aims to modify a projector input image to co...

2 Bingyao Huang, et al. ∙

research

∙ 06/12/2020

FedGAN: Federated Generative Adversarial Networks for Distributed Data

We propose Federated Generative Adversarial Network (FedGAN) for trainin...

0 Mohammad Rasouli, et al. ∙

research

∙ 06/12/2020

FedGAN: Federated Generative AdversarialNetworks for Distributed Data

We propose Federated Generative Adversarial Network (FedGAN) for trainin...

0 Mohammad Rasouli, et al. ∙

research

∙ 02/20/2020

Adaptive Temporal Difference Learning with Linear Function Approximation

This paper revisits the celebrated temporal difference (TD) learning alg...

15 Tao Sun, et al. ∙

research

∙ 01/02/2020

Zero-Shot Reinforcement Learning with Deep Attention Convolutional Neural Networks

Simulation-to-simulation and simulation-to-real world transfer of neural...

0 Sahika Genc, et al. ∙

research

∙ 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...

14 Bharathan Balaji, et al. ∙

research

∙ 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...

0 Tao Sun, et al. ∙

research

∙ 09/23/2019

Decentralized Markov Chain Gradient Descent

Decentralized stochastic gradient method emerges as a promising solution...

0 Tao Sun, et al. ∙

research

∙ 07/27/2019

Dilated FCN: Listening Longer to Hear Better

Deep neural network solutions have emerged as a new and powerful paradig...

0 Shuyu Gong, et al. ∙

research

∙ 07/27/2019

Inertial nonconvex alternating minimizations for the image deblurring

In image processing, Total Variation (TV) regularization models are comm...

4 Tao Sun, et al. ∙

research

∙ 07/23/2019

Heavy-ball Algorithms Always Escape Saddle Points

Nonconvex optimization algorithms with random initialization have attrac...

0 Tao Sun, et al. ∙

research

∙ 05/04/2019

Leveraging Crowdsourced GPS Data for Road Extraction from Aerial Imagery

Deep learning is revolutionizing the mapping industry. Under lightweight...

10 Tao Sun, et al. ∙

research

∙ 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...

0 Tao Sun, et al. ∙

research

∙ 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 ...

0 Tao Sun, et al. ∙

research

∙ 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...

0 Tao Sun, et al. ∙

research

∙ 11/27/2018

Quality-Aware Multimodal Saliency Detection via Deep Reinforcement Learning

Incorporating various modes of information into the machine learning pro...

0 Xiao Wang, et al. ∙

research

∙ 11/22/2018

Markov Chain Block Coordinate Descent

The method of block coordinate gradient descent (BCD) has been a powerfu...

0 Tao Sun, et al. ∙

research

∙ 11/05/2018

Non-ergodic Convergence Analysis of Heavy-Ball Algorithms

In this paper, we revisit the convergence of the Heavy-ball method, and ...

0 Tao Sun, et al. ∙

research

∙ 09/12/2018

On Markov Chain Gradient Descent

Stochastic gradient methods are the workhorse (algorithms) of large-scal...

8 Tao Sun, et al. ∙

research

∙ 09/11/2018

An Efficient ADMM-Based Algorithm to Nonconvex Penalized Support Vector Machines

Support vector machines (SVMs) with sparsity-inducing nonconvex penaltie...

0 Lei Guan, et al. ∙

research

∙ 05/25/2018

LAG: Lazily Aggregated Gradient for Communication-Efficient Distributed Learning

This paper presents a new class of gradient methods for distributed mach...

0 Tianyi Chen, et al. ∙

research

∙ 01/23/2018

On the complexity of convex inertial proximal algorithms

The inertial proximal gradient algorithm is efficient for the composite ...

0 Tao Sun, et al. ∙

research

∙ 09/12/2017

A convergence frame for inexact nonconvex and nonsmooth algorithms and its applications to several iterations

In this paper, we consider the convergence of an abstract inexact noncon...

0 Tao Sun, et al. ∙

Tao Sun

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