b'Liang Zhao'

research

∙ 08/08/2022

SLAM-TKA: Real-time Intra-operative Measurement of Tibial Resection Plane in Conventional Total Knee Arthroplasty

Total knee arthroplasty (TKA) is a common orthopaedic surgery to replace...

Shuai Zhang, et al. ∙

research

∙ 07/25/2022

COSIME: FeFET based Associative Memory for In-Memory Cosine Similarity Search

In a number of machine learning models, an input query is searched acros...

Che-Kai Liu, et al. ∙

research

∙ 07/22/2022

Two-Stage Fine-Tuning: A Novel Strategy for Learning Class-Imbalanced Data

Classification on long-tailed distributed data is a challenging problem,...

Taha ValizadehAslani, et al. ∙

research

∙ 07/19/2022

Controllable Data Generation by Deep Learning: A Review

Designing and generating new data under targeted properties has been att...

Shiyu Wang, et al. ∙

research

∙ 07/07/2022

Blockchain-based Medical Image Sharing and Automated Critical-results Notification: A Novel Framework

In teleradiology, medical images are transmitted to offsite radiologists...

Jiyoun Randolph, et al. ∙

research

∙ 07/03/2022

Saliency-Regularized Deep Multi-Task Learning

Multitask learning is a framework that enforces multiple learning tasks ...

Guangji Bai, et al. ∙

research

∙ 06/27/2022

RES: A Robust Framework for Guiding Visual Explanation

Despite the fast progress of explanation techniques in modern Deep Neura...

Yuyang Gao, et al. ∙

research

∙ 06/24/2022

Deep Generation of Heterogeneous Networks

Heterogeneous graphs are ubiquitous data structures that can inherently ...

Chen Ling, et al. ∙

research

∙ 06/24/2022

Source Localization of Graph Diffusion via Variational Autoencoders for Graph Inverse Problems

Graph diffusion problems such as the propagation of rumors, computer vir...

Chen Ling, et al. ∙

research

∙ 06/18/2022

An Invertible Graph Diffusion Neural Network for Source Localization

Localizing the source of graph diffusion phenomena, such as misinformati...

Junxiang Wang, et al. ∙

research

∙ 05/31/2022

Distributed Graph Neural Network Training with Periodic Historical Embedding Synchronization

Despite the recent success of Graph Neural Networks (GNNs), it remains c...

Zheng Chai, et al. ∙

research

∙ 05/21/2022

Temporal Domain Generalization with Drift-Aware Dynamic Neural Network

Temporal domain generalization is a promising yet extremely challenging ...

Guangji Bai, et al. ∙

research

∙ 03/31/2022

Logit Normalization for Long-tail Object Detection

Real-world data exhibiting skewed distributions pose a serious challenge...

Liang Zhao, et al. ∙

research

∙ 03/29/2022

Task-specific Inconsistency Alignment for Domain Adaptive Object Detection

Detectors trained with massive labeled data often exhibit dramatic perfo...

Liang Zhao, et al. ∙

research

∙ 02/28/2022

Disentangled Spatiotemporal Graph Generative Models

Spatiotemporal graph represents a crucial data structure where the nodes...

Yuanqi Du, et al. ∙

research

∙ 02/28/2022

Interpretable Molecular Graph Generation via Monotonic Constraints

Designing molecules with specific properties is a long-lasting research ...

Yuanqi Du, et al. ∙

research

∙ 02/18/2022

Black-box Node Injection Attack for Graph Neural Networks

Graph Neural Networks (GNNs) have drawn significant attentions over the ...

Mingxuan Ju, et al. ∙

research

∙ 02/06/2022

Aligning Eyes between Humans and Deep Neural Network through Interactive Attention Alignment

While Deep Neural Networks (DNNs) are deriving the major innovations in ...

Yuyang Gao, et al. ∙

research

∙ 01/28/2022

Deep Generative Model for Periodic Graphs

Periodic graphs are graphs consisting of repetitive local structures, su...

Shiyu Wang, et al. ∙

research

∙ 01/06/2022

Efficiently Disentangle Causal Representations

This paper proposes an efficient approach to learning disentangled repre...

Yuanpeng Li, et al. ∙

research

∙ 12/23/2021

Do Multi-Lingual Pre-trained Language Models Reveal Consistent Token Attributions in Different Languages?

During the past several years, a surge of multi-lingual Pre-trained Lang...

Junxiang Wang, et al. ∙

research

∙ 12/22/2021

A Convergent ADMM Framework for Efficient Neural Network Training

As a well-known optimization framework, the Alternating Direction Method...

Junxiang Wang, et al. ∙

research

∙ 12/17/2021

Community-based Layerwise Distributed Training of Graph Convolutional Networks

The Graph Convolutional Network (GCN) has been successfully applied to m...

Hongyi Li, et al. ∙

research

∙ 12/08/2021

Adaptive Kernel Graph Neural Network

Graph neural networks (GNNs) have demonstrated great success in represen...

Mingxuan Ju, et al. ∙

research

∙ 12/01/2021

Zero-Shot Cross-Lingual Machine Reading Comprehension via Inter-Sentence Dependency Graph

We target the task of cross-lingual Machine Reading Comprehension (MRC) ...

Liyan Xu, et al. ∙

research

∙ 11/26/2021

KNAS: Green Neural Architecture Search

Many existing neural architecture search (NAS) solutions rely on downstr...

Jingjing Xu, et al. ∙

research

∙ 10/26/2021

Heterogeneous Temporal Graph Neural Network

Graph neural networks (GNNs) have been broadly studied on dynamic graphs...

Yujie Fan, et al. ∙

research

∙ 08/23/2021

Molecular Design Based on Artificial Neural Networks, Integer Programming and Grid Neighbor Search

A novel framework has recently been proposed for designing the molecular...

Naveed Ahmed Azam, et al. ∙

research

∙ 08/23/2021

Long-term, Short-term and Sudden Event: Trading Volume Movement Prediction with Graph-based Multi-view Modeling

Trading volume movement prediction is the key in a variety of financial ...

Liang Zhao, et al. ∙

research

∙ 07/23/2021

Communication Efficiency in Federated Learning: Achievements and Challenges

Federated Learning (FL) is known to perform Machine Learning tasks in a ...

Osama Shahid, et al. ∙

research

∙ 07/21/2021

Bridging the Gap between Spatial and Spectral Domains: A Theoretical Framework for Graph Neural Networks

During the past decade, deep learning's performance has been widely reco...

Zhiqian Chen, et al. ∙

research

∙ 07/06/2021

An Inverse QSAR Method Based on Linear Regression and Integer Programming

Recently a novel framework has been proposed for designing the molecular...

Jianshen Zhu, et al. ∙

research

∙ 06/11/2021

RefBERT: Compressing BERT by Referencing to Pre-computed Representations

Recently developed large pre-trained language models, e.g., BERT, have a...

Xinyi Wang, et al. ∙

research

∙ 05/21/2021

Direct Simultaneous Multi-Image Registration

This paper presents a novel algorithm that registers a collection of mon...

Zhehua Mao, et al. ∙

research

∙ 05/20/2021

Towards Quantized Model Parallelism for Graph-Augmented MLPs Based on Gradient-Free ADMM framework

The Graph Augmented Multi-layer Perceptron (GA-MLP) model is an attracti...

Junxiang Wang, et al. ∙

research

∙ 05/05/2021

Schematic Memory Persistence and Transience for Efficient and Robust Continual Learning

Continual learning is considered a promising step towards next-generatio...

Yuyang Gao, et al. ∙

research

∙ 03/17/2021

Interpretable Distance Metric Learning for Handwritten Chinese Character Recognition

Handwriting recognition is of crucial importance to both Human Computer ...

Boxiang Dong, et al. ∙

research

∙ 03/17/2021

Cyber Intrusion Detection by Using Deep Neural Networks with Attack-sharing Loss

Cyber attacks pose crucial threats to computer system security, and put ...

Boxiang Dong, et al. ∙

research

∙ 02/22/2021

Sign-regularized Multi-task Learning

Multi-task learning is a framework that enforces different learning task...

Johnny Torres, et al. ∙

research

∙ 01/25/2021

GP: Context-free Grammar Pre-training for Text-to-SQL Parsers

A new method for Text-to-SQL parsing, Grammar Pre-training (GP), is prop...

Liang Zhao, et al. ∙

research

∙ 01/11/2021

FamDroid: Learning-Based Android Malware Family Classification Using Static Analysis

Android is currently the most extensively used smartphone platform in th...

Wenhao fan, et al. ∙

research

∙ 12/25/2020

Study On Coding Tools Beyond Av1

The Alliance for Open Media has recently initiated coding tool explorati...

Xin Zhao, et al. ∙

research

∙ 10/15/2020

Online Decision Trees with Fairness

While artificial intelligence (AI)-based decision-making systems are inc...

Wenbin Zhang, et al. ∙

research

∙ 10/14/2020

Disentangled Dynamic Graph Deep Generation

Deep generative models for graphs have exhibited promising performance i...

Wenbin Zhang, et al. ∙

research

∙ 10/12/2020

FedAT: A Communication-Efficient Federated Learning Method with Asynchronous Tiers under Non-IID Data

Federated learning (FL) involves training a model over massive distribut...

Zheng Chai, et al. ∙

research

∙ 09/28/2020

A new network-base high-level data classification methodology (Quipus) by modeling attribute-attribute interactions

High-level classification algorithms focus on the interactions between i...

Esteban Wilfredo Vilca Zuñiga, et al. ∙

research

∙ 09/28/2020

Graph-based Multi-hop Reasoning for Long Text Generation

Long text generation is an important but challenging task.The main probl...

Liang Zhao, et al. ∙

research

∙ 09/21/2020

A Novel Method for Inference of Acyclic Chemical Compounds with Bounded Branch-height Based on Artificial Neural Networks and Integer Programming

Analysis of chemical graphs is a major research topic in computational m...

Naveed Ahmed Azam, et al. ∙

research

∙ 09/20/2020

Factorized Deep Generative Models for Trajectory Generation with Spatiotemporal-Validity Constraints

Trajectory data generation is an important domain that characterizes the...

Liming Zhang, et al. ∙

research

∙ 09/16/2020

A Network-Based High-Level Data Classification Algorithm Using Betweenness Centrality

Data classification is a major machine learning paradigm, which has been...

Esteban Vilca, et al. ∙

Liang Zhao

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