b'Yiwen Guo'

research

∙ 09/04/2023

Code Representation Pre-training with Complements from Program Executions

Large language models (LLMs) for natural language processing have been g...

0 Jiabo Huang, et al. ∙

research

∙ 08/31/2023

Ref-Diff: Zero-shot Referring Image Segmentation with Generative Models

Zero-shot referring image segmentation is a challenging task because it ...

0 Minheng Ni, et al. ∙

research

∙ 07/21/2023

Improving Transferability of Adversarial Examples via Bayesian Attacks

This paper presents a substantial extension of our work published at ICL...

0 Qizhang Li, et al. ∙

research

∙ 05/23/2023

Understanding Programs by Exploiting (Fuzzing) Test Cases

Semantic understanding of programs has attracted great attention in the ...

0 Jianyu Zhao, et al. ∙

research

∙ 04/26/2023

Improving Adversarial Transferability via Intermediate-level Perturbation Decay

Intermediate-level attacks that attempt to perturb feature representatio...

0 Qizhang Li, et al. ∙

research

∙ 02/10/2023

Making Substitute Models More Bayesian Can Enhance Transferability of Adversarial Examples

The transferability of adversarial examples across deep neural networks ...

0 Qizhang Li, et al. ∙

research

∙ 11/23/2022

Texts as Images in Prompt Tuning for Multi-Label Image Recognition

Prompt tuning has been employed as an efficient way to adapt large visio...

0 Zixian Guo, et al. ∙

research

∙ 10/14/2022

When Adversarial Training Meets Vision Transformers: Recipes from Training to Architecture

Vision Transformers (ViTs) have recently achieved competitive performanc...

0 Yichuan Mo, et al. ∙

research

∙ 05/23/2022

Collaborative Adversarial Training

The vulnerability of deep neural networks (DNNs) to adversarial examples...

0 Qizhang Li, et al. ∙

research

∙ 03/21/2022

An Intermediate-level Attack Framework on The Basis of Linear Regression

This paper substantially extends our work published at ECCV, in which an...

0 Yiwen Guo, et al. ∙

research

∙ 03/06/2022

On Steering Multi-Annotations per Sample for Multi-Task Learning

The study of multi-task learning has drawn great attention from the comm...

0 Yuanze Li, et al. ∙

research

∙ 12/21/2021

A Theoretical View of Linear Backpropagation and Its Convergence

Backpropagation is widely used for calculating gradients in deep neural ...

0 Ziang Li, et al. ∙

research

∙ 12/21/2021

Learned ISTA with Error-based Thresholding for Adaptive Sparse Coding

The learned iterative shrinkage thresholding algorithm (LISTA) introduce...

0 Ziang Li, et al. ∙

research

∙ 06/30/2021

Robust Coreset for Continuous-and-Bounded Learning (with Outliers)

In this big data era, we often confront large-scale data in many machine...

0 Zixiu Wang, et al. ∙

research

∙ 03/25/2021

Recent Advances in Large Margin Learning

This paper serves as a survey of recent advances in large margin trainin...

0 Yiwen Guo, et al. ∙

research

∙ 03/25/2021

Deepfake Forensics via An Adversarial Game

With the progress in AI-based facial forgery (i.e., deepfake), people ar...

0 Zhi Wang, et al. ∙

research

∙ 12/07/2020

Backpropagating Linearly Improves Transferability of Adversarial Examples

The vulnerability of deep neural networks (DNNs) to adversarial examples...

0 Yiwen Guo, et al. ∙

research

∙ 12/04/2020

Practical No-box Adversarial Attacks against DNNs

The study of adversarial vulnerabilities of deep neural networks (DNNs) ...

0 Qizhang Li, et al. ∙

research

∙ 10/17/2020

LID 2020: The Learning from Imperfect Data Challenge Results

Learning from imperfect data becomes an issue in many industrial applica...

4 Yunchao Wei, et al. ∙

research

∙ 08/20/2020

Yet Another Intermediate-Level Attack

The transferability of adversarial examples across deep neural network (...

3 Qizhang Li, et al. ∙

research

∙ 07/04/2020

On Connections between Regularizations for Improving DNN Robustness

This paper analyzes regularization terms proposed recently for improving...

1 Yiwen Guo, et al. ∙

research

∙ 06/10/2020

Towards Certified Robustness of Metric Learning

Metric learning aims to learn a distance metric such that semantically s...

0 Xiaochen Yang, et al. ∙

research

∙ 11/14/2019

Adversarial Margin Maximization Networks

The tremendous recent success of deep neural networks (DNNs) has sparked...

0 Ziang Yan, et al. ∙

research

∙ 06/11/2019

Subspace Attack: Exploiting Promising Subspaces for Query-Efficient Black-box Attacks

Unlike the white-box counterparts that are widely studied and readily ac...

0 Ziang Yan, et al. ∙

research

∙ 05/06/2019

Differentiable Architecture Search with Ensemble Gumbel-Softmax

For network architecture search (NAS), it is crucial but challenging to ...

0 Jianlong Chang, et al. ∙

research

∙ 05/05/2019

Deep Discriminative Clustering Analysis

Traditional clustering methods often perform clustering with low-level i...

14 Jianlong Chang, et al. ∙

research

∙ 04/19/2019

Deep Likelihood Network for Image Restoration with Multiple Degradations

Convolutional neural networks have been proven very effective in a varie...

0 Yiwen Guo, et al. ∙

research

∙ 10/23/2018

Sparse DNNs with Improved Adversarial Robustness

Deep neural networks (DNNs) are computationally/memory-intensive and vul...

0 Yiwen Guo, et al. ∙

research

∙ 02/23/2018

DeepDefense: Training Deep Neural Networks with Improved Robustness

Despite the efficacy on a variety of computer vision tasks, deep neural ...

0 Ziang Yan, et al. ∙

research

∙ 07/03/2017

Physics Inspired Optimization on Semantic Transfer Features: An Alternative Method for Room Layout Estimation

In this paper, we propose an alternative method to estimate room layouts...

0 Hao Zhao, et al. ∙

research

∙ 06/07/2017

Network Sketching: Exploiting Binary Structure in Deep CNNs

Convolutional neural networks (CNNs) with deep architectures have substa...

0 Yiwen Guo, et al. ∙

research

∙ 02/10/2017

Incremental Network Quantization: Towards Lossless CNNs with Low-Precision Weights

This paper presents incremental network quantization (INQ), a novel meth...

0 Aojun Zhou, et al. ∙

research

∙ 08/16/2016

Dynamic Network Surgery for Efficient DNNs

Deep learning has become a ubiquitous technology to improve machine inte...

0 Yiwen Guo, et al. ∙

Yiwen Guo

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