203 citations · 437 across the 28 of their papers we have counts for
28 papers
Compression-Resistant Backdoor Attack against Deep Neural Networks
Mingfu Xue, Xin Wang, Shichang Sun +3
In recent years, many backdoor attacks based on training data poisoning have been proposed. However, in practice, those backdoor attacks are vulnerable to image compressions. When…
A Scalable Deep Reinforcement Learning Model for Online Scheduling Coflows of Multi-Stage Jobs for High Performance Computing
Xin Wang, Hong Shen
Coflow is a recently proposed networking abstraction to help improve the communication performance of data-parallel computing jobs. In multi-stage jobs, each job consists of multip…
HybridGazeNet: Geometric model guided Convolutional Neural Networks for gaze estimation
Shaobo Guo, Xiao Jiang, Zhizhong Su +2
As a critical cue for understanding human intention, human gaze provides a key signal for Human-Computer Interaction(HCI) applications. Appearance-based gaze estimation, which dire…
CAP: Co-Adversarial Perturbation on Weights and Features for Improving Generalization of Graph Neural Networks
Haotian Xue, Kaixiong Zhou, Tianlong Chen +4
Despite the recent advances of graph neural networks (GNNs) in modeling graph data, the training of GNNs on large datasets is notoriously hard due to the overfitting. Adversarial t…
Wanderlust: Online Continual Object Detection in the Real World
Jianren Wang, Xin Wang, Yue Shang-Guan +1
Online continual learning from data streams in dynamic environments is a critical direction in the computer vision field. However, realistic benchmarks and fundamental studies in t…
Orthogonal Graph Neural Networks
Kai Guo, Kaixiong Zhou, Xia Hu +3
Graph neural networks (GNNs) have received tremendous attention due to their superiority in learning node representations. These models rely on message passing and feature transfor…
Robust Attentive Deep Neural Network for Exposing GAN-generated Faces
Hui Guo, Shu Hu, Xin Wang +2
GAN-based techniques that generate and synthesize realistic faces have caused severe social concerns and security problems. Existing methods for detecting GAN-generated faces can p…
Eyes Tell All: Irregular Pupil Shapes Reveal GAN-generated Faces
Hui Guo, Shu Hu, Xin Wang +2
Generative adversary network (GAN) generated high-realistic human faces have been used as profile images for fake social media accounts and are visually challenging to discern from…
Dynamic Multi-scale Convolution for Dialect Identification
Tianlong Kong, Shouyi Yin, Dawei Zhang +6
Time Delay Neural Networks (TDNN)-based methods are widely used in dialect identification. However, in previous work with TDNN application, subtle variant is being neglected in dif…
TML-AP: Adversarial Attacks to Top- Multi-Label Learning
Shu Hu, Lipeng Ke, Xin Wang +1
Top- multi-label learning, which returns the top- predicted labels from an input, has many practical applications such as image annotation, document analysis, and web search…
ReFormer: The Relational Transformer for Image Captioning
Xuewen Yang, Yingru Liu, Xin Wang
Image captioning is shown to be able to achieve a better performance by using scene graphs to represent the relations of objects in the image. The current captioning encoders gener…
DETReg: Unsupervised Pretraining with Region Priors for Object Detection
Amir Bar, Xin Wang, Vadim Kantorov +6
Recent self-supervised pretraining methods for object detection largely focus on pretraining the backbone of the object detector, neglecting key parts of detection architecture. In…
Sum of Ranked Range Loss for Supervised Learning
Shu Hu, Yiming Ying, Xin Wang +1
In forming learning objectives, one oftentimes needs to aggregate a set of individual values to a single output. Such cases occur in the aggregate loss, which combines individual l…
Robust Object Detection via Instance-Level Temporal Cycle Confusion
Xin Wang, Thomas E. Huang, Benlin Liu +4
Building reliable object detectors that are robust to domain shifts, such as various changes in context, viewpoint, and object appearances, is critical for real-world applications.…
Learning by Minimizing the Sum of Ranked Range
Shu Hu, Yiming Ying, Xin Wang +1
In forming learning objectives, one oftentimes needs to aggregate a set of individual values to a single output. Such cases occur in the aggregate loss, which combines individual l…
SWIPENET: Object detection in noisy underwater images
Long Chen, Feixiang Zhou, Shengke Wang +5
In recent years, deep learning based object detection methods have achieved promising performance in controlled environments. However, these methods lack sufficient capabilities to…
The curious case of developmental BERTology: On sparsity, transfer learning, generalization and the brain
Xin Wang
In this essay, we explore a point of intersection between deep learning and neuroscience, through the lens of large language models, transfer learning and network compression. Just…
Learning Continuous-Time Dynamics by Stochastic Differential Networks
Yingru Liu, Yucheng Xing, Xuewen Yang +4
Learning continuous-time stochastic dynamics is a fundamental and essential problem in modeling sporadic time series, whose observations are irregular and sparse in both time and d…
Domain-Aware Dynamic Networks
Tianyuan Zhang, Bichen Wu, Xin Wang +2
Deep neural networks with more parameters and FLOPs have higher capacity and generalize better to diverse domains. But to be deployed on edge devices, the model's complexity has to…
Adaptive Activation Network and Functional Regularization for Efficient and Flexible Deep Multi-Task Learning
Yingru Liu, Xuewen Yang, Dongliang Xie +4
Multi-task learning (MTL) is a common paradigm that seeks to improve the generalization performance of task learning by training related tasks simultaneously. However, it is still…
Data Sanity Check for Deep Learning Systems via Learnt Assertions
Haochuan Lu, Huanlin Xu, Nana Liu +2
Reliability is a critical consideration to DL-based systems. But the statistical nature of DL makes it quite vulnerable to invalid inputs, i.e., those cases that are not considered…
Modeling the Uncertainty in Electronic Health Records: a Bayesian Deep Learning Approach
Riyi Qiu, Yugang Jia, Mirsad Hadzikadic +3
Deep learning models have exhibited superior performance in predictive tasks with the explosively increasing Electronic Health Records (EHR). However, due to the lack of transparen…
Task-Aware Feature Generation for Zero-Shot Compositional Learning
Xin Wang, Fisher Yu, Trevor Darrell +1
Visual concepts (e.g., red apple, big elephant) are often semantically compositional and each element of the compositions can be reused to construct novel concepts (e.g., red eleph…
Recognizing License Plates in Real-Time
Xuewen Yang, Xin Wang
License plate detection and recognition (LPDR) is of growing importance for enabling intelligent transportation and ensuring the security and safety of the cities. However, LPDR fa…