2.6k citations · 4.4k across the 31 of their papers we have counts for
34 papers
Centralized Network Utility Maximization with Accelerated Gradient Method
Ying Tian, Zhiliang Wang, Xia Yin +3
Network utility maximization (NUM) is a well-studied problem for network traffic management and resource allocation. Because of the inherent decentralization and complexity of netw…
Multi-Label Noise Transition Matrix Estimation with Label Correlations: Theory and Algorithm
Shikun Li, Xiaobo Xia, Hansong Zhang +2
Noisy multi-label learning has garnered increasing attention due to the challenges posed by collecting large-scale accurate labels, making noisy labels a more practical alternative…
StoryBench: A Multifaceted Benchmark for Continuous Story Visualization
Emanuele Bugliarello, Hernan Moraldo, Ruben Villegas +7
Generating video stories from text prompts is a complex task. In addition to having high visual quality, videos need to realistically adhere to a sequence of text prompts whilst be…
NEON: Living Needs Prediction System in Meituan
Xiaochong Lan, Chen Gao, Shiqi Wen +6
Living needs refer to the various needs in human's daily lives for survival and well-being, including food, housing, entertainment, etc. On life service platforms that connect user…
Lipschitz Singularities in Diffusion Models
Zhantao Yang, Ruili Feng, Han Zhang +8
Diffusion models, which employ stochastic differential equations to sample images through integrals, have emerged as a dominant class of generative models. However, the rationality…
Dimensions of some LCD BCH codes
Hanglong Zhang, Xiwang Cao
In this paper, we investigate the first few largest coset leaders modulo where and is an odd prime power, and give the dimensions of some LCD BCH co…
A tight upper bound on the number of non-zero weights of a constacyclic code
Hanglong Zhang, Xiwang Cao
For a simple-root -constacyclic code over , let and be the subgroups of the automorphism group of …
Diversify Your Vision Datasets with Automatic Diffusion-Based Augmentation
Lisa Dunlap, Alyssa Umino, Han Zhang +3
Many fine-grained classification tasks, like rare animal identification, have limited training data and consequently classifiers trained on these datasets often fail to generalize…
Small area estimation for composite indicators: the case of multidimensional poverty incidence
Alejandra Arias-Salazar, Andrés Gutiérrez, Xavier Mancero +3
This paper proposes a methodology to obtain estimates in small domains when the target is a composite indicator. These indicators are of utmost importance for studying multidimensi…
Delayed and Indirect Impacts of Link Recommendations
Han Zhang, Shangen Lu, Yixin Wang +1
The impacts of link recommendations on social networks are challenging to evaluate, and so far they have been studied in limited settings. Observational studies are restricted in t…
Evolution of Filter Bubbles and Polarization in News Recommendation
Han Zhang, Ziwei Zhu, James Caverlee
Recent work in news recommendation has demonstrated that recommenders can over-expose users to articles that support their pre-existing opinions. However, most existing work focuse…
FineDance: A Fine-grained Choreography Dataset for 3D Full Body Dance Generation
Ronghui Li, Junfan Zhao, Yachao Zhang +5
Generating full-body and multi-genre dance sequences from given music is a challenging task, due to the limitations of existing datasets and the inherent complexity of the fine-gra…
Uncertainty Sentence Sampling by Virtual Adversarial Perturbation
Hanshan Zhang, Zhen Zhang, Hongfei Jiang +1
Active learning for sentence understanding attempts to reduce the annotation cost by identifying the most informative examples. Common methods for active learning use either uncert…
Hierarchical Graph Convolutional Network Built by Multiscale Atlases for Brain Disorder Diagnosis Using Functional Connectivity
Mianxin Liu, Han Zhang, Feng Shi +1
Functional connectivity network (FCN) data from functional magnetic resonance imaging (fMRI) is increasingly used for the diagnoses of brain disorders. However, state-of-the-art st…
Statistically Consistent Inverse Optimal Control for Linear-Quadratic Tracking with Random Time Horizon
Han Zhang, Axel Ringh, Weihan Jiang +2
The goal of Inverse Optimal Control (IOC) is to identify the underlying objective function based on observed optimal trajectories. It provides a powerful framework to model expert'…
Unified smoke and fire detection in an evolutionary framework with self-supervised progressive data augment
Hang Zhang, Su Yang, Hongyong Wang +2
Few researches have studied simultaneous detection of smoke and flame accompanying fires due to their different physical natures that lead to uncertain fluid patterns. In this stud…
ERNIE-ViLG: Unified Generative Pre-training for Bidirectional Vision-Language Generation
Han Zhang, Weichong Yin, Yewei Fang +7
Conventional methods for the image-text generation tasks mainly tackle the naturally bidirectional generation tasks separately, focusing on designing task-specific frameworks to im…
Brain Network Construction and Classification Toolbox (BrainNetClass)
Zhen Zhou, Xiaobo Chen, Yu Zhang +5
Brain functional network has become an increasingly used approach in understanding brain functions and diseases. Many network construction methods have been developed, whereas the…
ERNIE: Enhanced Representation through Knowledge Integration
Yu Sun, Shuohuan Wang, Yukun Li +7
We present a novel language representation model enhanced by knowledge called ERNIE (Enhanced Representation through kNowledge IntEgration). Inspired by the masking strategy of BER…
Signal Demodulation with Machine Learning Methods for Physical Layer Visible Light Communications: Prototype Platform, Open Dataset and Algorithms
Shuai Ma, Jiahui Dai, Songtao Lu +4
In this paper, we investigate the design and implementation of machine learning (ML) based demodulation methods in the physical layer of visible light communication (VLC) systems.…
Deep Learning for Signal Demodulation in Physical Layer Wireless Communications: Prototype Platform, Open Dataset, and Analytics
Hongmei Wang, Zhenzhen Wu, Shuai Ma +4
In this paper, we investigate deep learning (DL)-enabled signal demodulation methods and establish the first open dataset of real modulated signals for wireless communication syste…
A Unified Mammogram Analysis Method via Hybrid Deep Supervision
Rongzhao Zhang, Han Zhang, Albert C. S. Chung
Automatic mammogram classification and mass segmentation play a critical role in a computer-aided mammogram screening system. In this work, we present a unified mammogram analysis…
Deep Chronnectome Learning via Full Bidirectional Long Short-Term Memory Networks for MCI Diagnosis
Weizheng Yan, Han Zhang, Jing Sui +1
Brain functional connectivity (FC) extracted from resting-state fMRI (RS-fMRI) has become a popular approach for disease diagnosis, where discriminating subjects with mild cognitiv…
Self-Attention Generative Adversarial Networks
Han Zhang, Ian Goodfellow, Dimitris Metaxas +1
In this paper, we propose the Self-Attention Generative Adversarial Network (SAGAN) which allows attention-driven, long-range dependency modeling for image generation tasks. Tradit…