Search Results for author: Shuang Liu

Found 32 papers, 8 papers with code

Generalization Bound and New Algorithm for Clean-Label Backdoor Attack

1 code implementation2 Jun 2024 Lijia Yu, Shuang Liu, Yibo Miao, Xiao-Shan Gao, Lijun Zhang

The generalization bound is a crucial theoretical tool for assessing the generalizability of learning methods and there exist vast literatures on generalizability of normal learning, adversarial learning, and data poisoning.

Backdoor Attack Data Poisoning +1

Game-Theoretic Unlearnable Example Generator

1 code implementation31 Jan 2024 Shuang Liu, Yihan Wang, Xiao-Shan Gao

Unlearnable example attacks are data poisoning attacks aiming to degrade the clean test accuracy of deep learning by adding imperceptible perturbations to the training samples, which can be formulated as a bi-level optimization problem.

Data Poisoning

Data-Dependent Stability Analysis of Adversarial Training

no code implementations6 Jan 2024 Yihan Wang, Shuang Liu, Xiao-Shan Gao

Stability analysis is an essential aspect of studying the generalization ability of deep learning, as it involves deriving generalization bounds for stochastic gradient descent-based training algorithms.

Data Poisoning Generalization Bounds

A Review on Machine Theory of Mind

no code implementations21 Mar 2023 Yuanyuan Mao, Shuang Liu, Pengshuai Zhao, Qin Ni, Xin Lin, Liang He

Beliefs, desires, and intentions are the early abilities of infants and the foundation of human cognitive ability, as well as for machine with ToM.


Wukong-Reader: Multi-modal Pre-training for Fine-grained Visual Document Understanding

no code implementations19 Dec 2022 Haoli Bai, Zhiguang Liu, Xiaojun Meng, Wentao Li, Shuang Liu, Nian Xie, Rongfu Zheng, Liangwei Wang, Lu Hou, Jiansheng Wei, Xin Jiang, Qun Liu

While various vision-language pre-training objectives are studied in existing solutions, the document textline, as an intrinsic granularity in VDU, has seldom been explored so far.

Contrastive Learning document understanding +2

Micro-Vibration Modes Reconstruction Based on Micro-Doppler Coincidence Imaging

no code implementations30 Aug 2022 Shuang Liu, Chenjin Deng, Chaoran Wang, Zunwang Bo, Shensheng Han, Zihuai Lin

To reconstruct the spatial distribution of micro vibrations, this paper proposes a new method based on a coincidence imaging system.

Achieve Optimal Adversarial Accuracy for Adversarial Deep Learning using Stackelberg Game

no code implementations17 Jul 2022 Xiao-Shan Gao, Shuang Liu, Lijia Yu

Game theory has been used to answer some of the basic questions about adversarial deep learning such as the existence of a classifier with optimal robustness and the existence of optimal adversarial samples for a given class of classifiers.

Improving Policy Optimization with Generalist-Specialist Learning

1 code implementation26 Jun 2022 Zhiwei Jia, Xuanlin Li, Zhan Ling, Shuang Liu, Yiran Wu, Hao Su

Generalization in deep reinforcement learning over unseen environment variations usually requires policy learning over a large set of diverse training variations.

Imitation Learning

Provably Efficient Kernelized Q-Learning

no code implementations21 Apr 2022 Shuang Liu, Hao Su

We propose and analyze a kernelized version of Q-learning.


Unified Line and Paragraph Detection by Graph Convolutional Networks

no code implementations17 Mar 2022 Shuang Liu, Renshen Wang, Michalis Raptis, Yasuhisa Fujii

We formulate the task of detecting lines and paragraphs in a document into a unified two-level clustering problem.

Clustering Text Detection

Symmetry-aware Neural Architecture for Embodied Visual Navigation

no code implementations17 Dec 2021 Shuang Liu, Takayuki Okatani

We then propose a network design for the actor and the critic to inherently attain these symmetries.

Reinforcement Learning (RL) Visual Navigation

A Comprehensive Study on Learning-Based PE Malware Family Classification Methods

1 code implementation29 Oct 2021 Yixuan Ma, Shuang Liu, Jiajun Jiang, Guanhong Chen, Keqiu Li

PE malware family classification has gained great attention and a large number of approaches have been proposed.

Classification Malware Classification

Task Guided Compositional Representation Learning for ZDA

no code implementations13 Sep 2021 Shuang Liu, Mete Ozay

To this end, we propose a method for task-guided ZDA (TG-ZDA) which employs multi-branch deep neural networks to learn feature representations exploiting their domain invariance and shareability properties.

Domain Adaptation Image Classification +1

GQE-PRF: Generative Query Expansion with Pseudo-Relevance Feedback

no code implementations13 Aug 2021 Minghui Huang, Dong Wang, Shuang Liu, Meizhen Ding

To leverage the strength of text generation for information retrieval, in this article, we propose a novel approach which effectively integrates text generation models into PRF-based query expansion.

Information Retrieval Retrieval +1

Person Re-Identification Using Heterogeneous Local Graph Attention Networks

no code implementations CVPR 2021 Zhong Zhang, Haijia Zhang, Shuang Liu

Specifically, we first construct the completed local graph using local features, and we resort to the attention mechanism to aggregate the local features in the learning process of inter-local relation and intra-local relation so as to emphasize the importance of different local features.

Graph Attention Person Re-Identification +1

SE-ECGNet: A Multi-scale Deep Residual Network with Squeeze-and-Excitation Module for ECG Signal Classification

1 code implementation10 Dec 2020 Haozhen Zhang, Wei Zhao, Shuang Liu

The classification of electrocardiogram (ECG) signals, which takes much time and suffers from a high rate of misjudgment, is recognized as an extremely challenging task for cardiologists.

Classification General Classification

Rotational dynamics of bottom-heavy rods in turbulence from experiments and numerical simulations

1 code implementation10 Dec 2020 Linfeng Jiang, Cheng Wang, Shuang Liu, Chao Sun, Enrico Calzavarini

We successfully perform the three-dimensional tracking in a turbulent fluid flow of small asymmetrical particles that are neutrally-buoyant and bottom-heavy, i. e., they have a non-homogeneous mass distribution along their symmetry axis.

Fluid Dynamics

Regret Bounds for Discounted MDPs

no code implementations12 Feb 2020 Shuang Liu, Hao Su

We give motivations and derive lower and upper bounds for such measures.

Q-Learning Reinforcement Learning (RL)

There is Limited Correlation between Coverage and Robustness for Deep Neural Networks

no code implementations14 Nov 2019 Yizhen Dong, Peixin Zhang, Jingyi Wang, Shuang Liu, Jun Sun, Jianye Hao, Xinyu Wang, Li Wang, Jin Song Dong, Dai Ting

In this work, we conduct an empirical study to evaluate the relationship between coverage, robustness and attack/defense metrics for DNN.

Face Recognition Malware Detection

Pre-training as Batch Meta Reinforcement Learning with tiMe

no code implementations25 Sep 2019 Quan Vuong, Shuang Liu, Minghua Liu, Kamil Ciosek, Hao Su, Henrik Iskov Christensen

Combining ideas from Batch RL and Meta RL, we propose tiMe, which learns distillation of multiple value functions and MDP embeddings from only existing data.

Meta Reinforcement Learning reinforcement-learning +1

The Inductive Bias of Restricted f-GANs

no code implementations12 Sep 2018 Shuang Liu, Kamalika Chaudhuri

Generative adversarial networks are a novel method for statistical inference that have achieved much empirical success; however, the factors contributing to this success remain ill-understood.

Inductive Bias

Falsification of Cyber-Physical Systems Using Deep Reinforcement Learning

no code implementations1 May 2018 Takumi Akazaki, Shuang Liu, Yoriyuki Yamagata, Yihai Duan, Jianye Hao

With the rapid development of software and distributed computing, Cyber-Physical Systems (CPS) are widely adopted in many application areas, e. g., smart grid, autonomous automobile.

Distributed Computing reinforcement-learning +1

A vision based system for underwater docking

no code implementations12 Dec 2017 Shuang Liu, Mete Ozay, Takayuki Okatani, Hongli Xu, Kai Sun, Yang Lin

In the experiments, we first evaluate performance of the proposed detection module on UDID and its deformed variations.

Pose Estimation Position

Approximation and Convergence Properties of Generative Adversarial Learning

no code implementations NeurIPS 2017 Shuang Liu, Olivier Bousquet, Kamalika Chaudhuri

In this paper, we address these questions in a broad and unified setting by defining a notion of adversarial divergences that includes a number of recently proposed objective functions.

A Parallel algorithm for $\mathcal{X}$-Armed bandits

no code implementations26 Oct 2015 Cheng Chen, Shuang Liu, Zhihua Zhang, Wu-Jun Li

To deal with these large-scale data sets, we study a distributed setting of $\mathcal{X}$-armed bandits, where $m$ players collaborate to find the maximum of the unknown function.

Regret vs. Communication: Distributed Stochastic Multi-Armed Bandits and Beyond

no code implementations14 Apr 2015 Shuang Liu, Cheng Chen, Zhihua Zhang

When the time horizon is unknown, we measure the frequency of communication through a new notion called the density of the communication set, and give an exact characterization of the interplay between regret and communication.

Multi-Armed Bandits

Cross-View Action Recognition via a Continuous Virtual Path

no code implementations CVPR 2013 Zhong Zhang, Chunheng Wang, Baihua Xiao, Wen Zhou, Shuang Liu, Cunzhao Shi

In this paper, we propose a novel method for cross-view action recognition via a continuous virtual path which connects the source view and the target view.

Action Recognition Temporal Action Localization

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