b'Shuai Zhang'

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

∙ 07/21/2022

Incorporating Prior Knowledge into Reinforcement Learning for Soft Tissue Manipulation with Autonomous Grasping Point Selection

Previous soft tissue manipulation studies assumed that the grasping poin...

Xian He, et al. ∙

research

∙ 07/09/2022

Smart Multi-tenant Federated Learning

Federated learning (FL) is an emerging distributed machine learning meth...

Weiming Zhuang, et al. ∙

research

∙ 07/07/2022

Learning and generalization of one-hidden-layer neural networks, going beyond standard Gaussian data

This paper analyzes the convergence and generalization of training a one...

Hongkang Li, et al. ∙

research

∙ 07/03/2022

Chat-to-Design: AI Assisted Personalized Fashion Design

In this demo, we present Chat-to-Design, a new multimodal interaction sy...

Weiming Zhuang, et al. ∙

research

∙ 05/24/2022

Optimizing Performance of Federated Person Re-identification: Benchmarking and Analysis

The increasingly stringent data privacy regulations limit the developmen...

Weiming Zhuang, et al. ∙

research

∙ 05/23/2022

A Fine-grained Interpretability Evaluation Benchmark for Neural NLP

While there is increasing concern about the interpretability of neural m...

Lijie Wang, et al. ∙

research

∙ 04/22/2022

Modelling graph dynamics in fraud detection with "Attention"

At online retail platforms, detecting fraudulent accounts and transactio...

Susie Xi Rao, et al. ∙

research

∙ 04/09/2022

Divergence-aware Federated Self-Supervised Learning

Self-supervised learning (SSL) is capable of learning remarkable represe...

Weiming Zhuang, et al. ∙

research

∙ 04/09/2022

Federated Unsupervised Domain Adaptation for Face Recognition

Given labeled data in a source domain, unsupervised domain adaptation ha...

Weiming Zhuang, et al. ∙

research

∙ 02/17/2022

ADD 2022: the First Audio Deep Synthesis Detection Challenge

Audio deepfake detection is an emerging topic, which was included in the...

Jiangyan Yi, et al. ∙

research

∙ 01/28/2022

Reducing language context confusion for end-to-end code-switching automatic speech recognition

Code-switching is about dealing with alternative languages in the commun...

Shuai Zhang, et al. ∙

research

∙ 01/21/2022

How does unlabeled data improve generalization in self-training? A one-hidden-layer theoretical analysis

Self-training, a semi-supervised learning algorithm, leverages a large a...

Shuai Zhang, et al. ∙

research

∙ 12/22/2021

An Efficient Pruning Process with Locality Aware Exploration and Dynamic Graph Editing for Subgraph Matching

Subgraph matching is a NP-complete problem that extracts isomorphic embe...

Zite Jiang, et al. ∙

research

∙ 10/12/2021

Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Pruned Neural Networks

The lottery ticket hypothesis (LTH) states that learning on a properly p...

Shuai Zhang, et al. ∙

research

∙ 08/14/2021

Joint Optimization in Edge-Cloud Continuum for Federated Unsupervised Person Re-identification

Person re-identification (ReID) aims to re-identify a person from non-ov...

Weiming Zhuang, et al. ∙

research

∙ 08/14/2021

Collaborative Unsupervised Visual Representation Learning from Decentralized Data

Unsupervised representation learning has achieved outstanding performanc...

Weiming Zhuang, et al. ∙

research

∙ 05/19/2021

A Sequence-to-Set Network for Nested Named Entity Recognition

Named entity recognition (NER) is a widely studied task in natural langu...

Zeqi Tan, et al. ∙

research

∙ 05/17/2021

Towards Unsupervised Domain Adaptation for Deep Face Recognition under Privacy Constraints via Federated Learning

Unsupervised domain adaptation has been widely adopted to generalize mod...

Weiming Zhuang, et al. ∙

research

∙ 05/17/2021

EasyFL: A Low-code Federated Learning Platform For Dummies

Academia and industry have developed several platforms to support the po...

Weiming Zhuang, et al. ∙

research

∙ 05/14/2021

Locate and Label: A Two-stage Identifier for Nested Named Entity Recognition

Named entity recognition (NER) is a well-studied task in natural languag...

Yongliang Shen, et al. ∙

research

∙ 04/07/2021

FSR: Accelerating the Inference Process of Transducer-Based Models by Applying Fast-Skip Regularization

Transducer-based models, such as RNN-Transducer and transformer-transduc...

Zhengkun Tian, et al. ∙

research

∙ 04/04/2021

TSNAT: Two-Step Non-Autoregressvie Transformer Models for Speech Recognition

The autoregressive (AR) models, such as attention-based encoder-decoder ...

Zhengkun Tian, et al. ∙

research

∙ 02/17/2021

Switch Spaces: Learning Product Spaces with Sparse Gating

Learning embedding spaces of suitable geometry is critical for represent...

Shuai Zhang, et al. ∙

research

∙ 02/17/2021

Beyond Fully-Connected Layers with Quaternions: Parameterization of Hypercomplex Multiplications with 1/n Parameters

Recent works have demonstrated reasonable success of representation lear...

Aston Zhang, et al. ∙

research

∙ 02/15/2021

Fast End-to-End Speech Recognition via a Non-Autoregressive Model and Cross-Modal Knowledge Transferring from BERT

Attention-based encoder-decoder (AED) models have achieved promising per...

Ye Bai, et al. ∙

research

∙ 12/20/2020

Suspicious Massive Registration Detection via Dynamic Heterogeneous Graph Neural Networks

Massive account registration has raised concerns on risk management in e...

Susie Xi Rao, et al. ∙

research

∙ 12/18/2020

Fast and Efficient Parallel Breadth-First Search with Power-law Graph Transformation

In the big data era, graph computing is widely used to exploit the hidde...

Zite Jiang, et al. ∙

research

∙ 12/14/2020

Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting

Many real-world applications require the prediction of long sequence tim...

Haoyi Zhou, et al. ∙

research

∙ 11/24/2020

xFraud: Explainable Fraud Transaction Detection on Heterogeneous Graphs

At online retail platforms, it is crucial to actively detect risks of fr...

Susie Xi Rao, et al. ∙

research

∙ 11/11/2020

Learning User Representations with Hypercuboids for Recommender Systems

Modeling user interests is crucial in real-world recommender systems. In...

Shuai Zhang, et al. ∙

research

∙ 10/28/2020

Decoupling Pronunciation and Language for End-to-end Code-switching Automatic Speech Recognition

Despite the recent significant advances witnessed in end-to-end (E2E) AS...

Shuai Zhang, et al. ∙

research

∙ 10/18/2020

An Efficient and Balanced Graph Partition Algorithm for the Subgraph-Centric Programming Model on Large-scale Power-law Graphs

The subgraph-centric programming model is a promising approach and has b...

Shuai Zhang, et al. ∙

research

∙ 10/12/2020

MicroRec: Efficient Recommendation Inference by Hardware and Data Structure Solutions

Deep neural networks are widely used in personalized recommendation syst...

Wenqi Jiang, et al. ∙

research

∙ 10/03/2020

Nonconvex Regularization for Network Slimming:Compressing CNNs Even More

In the last decade, convolutional neural networks (CNNs) have evolved to...

Kevin Bui, et al. ∙

research

∙ 09/03/2020

Computational prediction of RNA tertiary structures using machine learning methods

RNAs play crucial and versatile roles in biological processes. Computati...

Bin Huang, et al. ∙

research

∙ 09/02/2020

A Practical Chinese Dependency Parser Based on A Large-scale Dataset

Dependency parsing is a longstanding natural language processing task, w...

Shuai Zhang, et al. ∙

research

∙ 08/26/2020

Performance Optimization for Federated Person Re-identification via Benchmark Analysis

Federated learning is a privacy-preserving machine learning technique th...

Weiming Zhuang, et al. ∙

research

∙ 06/25/2020

Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case

Although graph neural networks (GNNs) have made great progress recently ...

Shuai Zhang, et al. ∙

research

∙ 06/18/2020

Automated Radiological Report Generation For Chest X-Rays With Weakly-Supervised End-to-End Deep Learning

The chest X-Ray (CXR) is the one of the most common clinical exam used t...

Shuai Zhang, et al. ∙

research

∙ 05/16/2020

Spike-Triggered Non-Autoregressive Transformer for End-to-End Speech Recognition

Non-autoregressive transformer models have achieved extremely fast infer...

Zhengkun Tian, et al. ∙

research

∙ 05/11/2020

Listen Attentively, and Spell Once: Whole Sentence Generation via a Non-Autoregressive Architecture for Low-Latency Speech Recognition

Although attention based end-to-end models have achieved promising perfo...

Ye Bai, et al. ∙

research

∙ 04/30/2020

TRP: Trained Rank Pruning for Efficient Deep Neural Networks

To enable DNNs on edge devices like mobile phones, low-rank approximatio...

Yuhui Xu, et al. ∙

research

∙ 02/19/2020

Rnn-transducer with language bias for end-to-end Mandarin-English code-switching speech recognition

Recently, language identity information has been utilized to improve the...

Shuai Zhang, et al. ∙

research

∙ 12/18/2019

Topology Aware Deep Learning for Wireless Network Optimization

Data-driven machine learning approaches have recently been proposed to f...

Shuai Zhang, et al. ∙

research

∙ 12/17/2019

ℓ_0 Regularized Structured Sparsity Convolutional Neural Networks

Deepening and widening convolutional neural networks (CNNs) significantl...

Kevin Bui, et al. ∙

research

∙ 12/06/2019

Synchronous Transformers for End-to-End Speech Recognition

For most of the attention-based sequence-to-sequence models, the decoder...

Zhengkun Tian, et al. ∙

research

∙ 12/04/2019

Integrating Whole Context to Sequence-to-sequence Speech Recognition

Because an attention based sequence-to-sequence speech (Seq2Seq) recogni...

Ye Bai, et al. ∙

research

∙ 10/24/2019

Weakly-Supervised Degree of Eye-Closeness Estimation

Following recent technological advances there is a growing interest in b...

Eyasu Mequanint, et al. ∙

research

∙ 10/09/2019

Traned Rank Pruning for Efficient Deep Neural Networks

To accelerate DNNs inference, low-rank approximation has been widely ado...

Yuhui Xu, et al. ∙

Shuai Zhang

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