Search Results for author: Lei Jiang

Found 31 papers, 7 papers with code

Aspect Is Not You Need: No-aspect Differential Sentiment Framework for Aspect-based Sentiment Analysis

no code implementations NAACL 2022 Jiahao Cao, Rui Liu, Huailiang Peng, Lei Jiang, Xu Bai

Then we propose a differential sentiment loss instead of the cross-entropy loss to better classify the sentiments by distinguishing the different distances between sentiments.

Aspect-Based Sentiment Analysis Contrastive Learning +1

Dynamic Nonlinear Mixup with Distance-based Sample Selection

no code implementations COLING 2022 Shaokang Zhang, Lei Jiang, Jianlong Tan

In this paper, we propose the dynamic nonlinear mixup with distance-based sample selection, which not only generates multiple sample pairs based on the distance between each sample but also enlarges the space of synthetic samples.

Data Augmentation

SSL-Cleanse: Trojan Detection and Mitigation in Self-Supervised Learning

no code implementations16 Mar 2023 Mengxin Zheng, Jiaqi Xue, Xun Chen, Lei Jiang, Qian Lou

By using a pre-trained SSL image encoder and training a downstream classifier on top of it, impressive performance can be achieved on various tasks with very little labeled data.

Self-Supervised Learning

SePaint: Semantic Map Inpainting via Multinomial Diffusion

no code implementations5 Mar 2023 Zheng Chen, Deepak Duggirala, David Crandall, Lei Jiang, Lantao Liu

Prediction beyond partial observations is crucial for robots to navigate in unknown environments because it can provide extra information regarding the surroundings beyond the current sensing range or resolution.


Multi-Feature Integration for Perception-Dependent Examination-Bias Estimation

1 code implementation27 Feb 2023 Xiaoshu Chen, Xiangsheng Li, Kunliang Wei, Bin Hu, Lei Jiang, Zeqian Huang, Zhanhui Kang

Eliminating examination bias accurately is pivotal to apply click-through data to train an unbiased ranking model.

QTrojan: A Circuit Backdoor Against Quantum Neural Networks

no code implementations16 Feb 2023 Cheng Chu, Lei Jiang, Martin Swany, Fan Chen

We propose a circuit-level backdoor attack, \textit{QTrojan}, against Quantum Neural Networks (QNNs) in this paper.

Backdoor Attack Data Poisoning

Cross-Network Social User Embedding with Hybrid Differential Privacy Guarantees

no code implementations4 Sep 2022 Jiaqian Ren, Lei Jiang, Hao Peng, Lingjuan Lyu, Zhiwei Liu, Chaochao Chen, Jia Wu, Xu Bai, Philip S. Yu

Integrating multiple online social networks (OSNs) has important implications for many downstream social mining tasks, such as user preference modelling, recommendation, and link prediction.

Link Prediction Network Embedding +1

TrojViT: Trojan Insertion in Vision Transformers

no code implementations27 Aug 2022 Mengxin Zheng, Qian Lou, Lei Jiang

The success of ViTs motivates adversaries to perform backdoor attacks on ViTs.

Backdoor Attack

ATPL: Mutually enhanced adversarial training and pseudo labeling for unsupervised domain adaptation

no code implementations Knowledge-Based Systems 2022 Changan Yi, Haotian Chen, Yonghui Xu, Yong liu, Lei Jiang, Haishu Tan

Accordingly, ATPL will use the pseudo-labeled information to improve the adversarial training process, which can guarantee the feature transferability by generating adversarial data to fill in the domain gap.

Unsupervised Domain Adaptation

Gradient Mask: Lateral Inhibition Mechanism Improves Performance in Artificial Neural Networks

no code implementations14 Aug 2022 Lei Jiang, Yongqing Liu, Shihai Xiao, Yansong Chua

Furthermore, we demonstrate analytically how lateral inhibition in artificial neural networks improves the quality of propagated gradients.

Data Augmentation

Self-Supervised Pretraining for Differentially Private Learning

1 code implementation14 Jun 2022 Arash Asadian, Evan Weidner, Lei Jiang

When facing the lack of public datasets, we show the features generated by SSP on only one single image enable a private classifier to obtain much better utility than the non-learned handcrafted features under the same privacy budget.

Image Classification

Evidential Temporal-aware Graph-based Social Event Detection via Dempster-Shafer Theory

no code implementations24 May 2022 Jiaqian Ren, Lei Jiang, Hao Peng, Zhiwei Liu, Jia Wu, Philip S. Yu

To incorporate temporal information into the message passing scheme, we introduce a novel temporal-aware aggregator which assigns weights to neighbours according to an adaptive time exponential decay formula.

Event Detection

Point Cloud Semantic Segmentation using Multi Scale Sparse Convolution Neural Network

no code implementations3 May 2022 Yunzheng Su, Lei Jiang, Jie Cao

In recent years, with the development of computing resources and LiDAR, point cloud semantic segmentation has attracted many researchers.

Point Cloud Segmentation Semantic Segmentation

Transferring Knowledge Distillation for Multilingual Social Event Detection

1 code implementation6 Aug 2021 Jiaqian Ren, Hao Peng, Lei Jiang, Jia Wu, Yongxin Tong, Lihong Wang, Xu Bai, Bo wang, Qiang Yang

Experiments on both synthetic and real-world datasets show the framework to be highly effective at detection in both multilingual data and in languages where training samples are scarce.

Cross-Lingual Word Embeddings Event Detection +2

HEMET: A Homomorphic-Encryption-Friendly Privacy-Preserving Mobile Neural Network Architecture

no code implementations31 May 2021 Qian Lou, Lei Jiang

Recently Homomorphic Encryption (HE) is used to implement Privacy-Preserving Neural Networks (PPNNs) that perform inferences directly on encrypted data without decryption.

Privacy Preserving

SAFENet: A Secure, Accurate and Fast Neural Network Inference

no code implementations ICLR 2021 Qian Lou, Yilin Shen, Hongxia Jin, Lei Jiang

A cryptographic neural network inference service is an efficient way to allow two parties to execute neural network inference without revealing either party’s data or model.

Falcon: Fast Spectral Inference on Encrypted Data

no code implementations NeurIPS 2020 Qian Lou, Wen-jie Lu, Cheng Hong, Lei Jiang

We observed that HENNs have to pay significant computing overhead on rotations, and each of rotations is $\sim 10\times$ more expensive than homomorphic multiplications between ciphertext and plaintext.

CryptoGRU: Low Latency Privacy-Preserving Text Analysis With GRU

no code implementations EMNLP 2021 Bo Feng, Qian Lou, Lei Jiang, Geoffrey C. Fox

Although prior secure networks combine homomorphic encryption (HE) and garbled circuit (GC) to preserve users' privacy, naively adopting the HE and GC hybrid technique to implement RNNs suffers from long inference latency due to slow activation functions.

Privacy Preserving

Helix: Algorithm/Architecture Co-design for Accelerating Nanopore Genome Base-calling

no code implementations4 Aug 2020 Qian Lou, Sarath Janga, Lei Jiang

From architecture perspective, we propose a low-power SOT-MRAM-based ADC array to process analog-to-digital conversion operations and improve power efficiency of prior DNN PIMs.

Kernel Learning for High-Resolution Time-Frequency Distribution

1 code implementation1 Jul 2020 Lei Jiang, Haijian Zhang, Lei Yu, Guang Hua

To break the current limitation, we propose a data-driven kernel learning model directly based on Wigner-Ville distribution (WVD).

AutoPrivacy: Automated Layer-wise Parameter Selection for Secure Neural Network Inference

no code implementations NeurIPS 2020 Qian Lou, Song Bian, Lei Jiang

Prior HPPNNs over-pessimistically select huge HE parameters to maintain large noise budgets, since they use the same set of HE parameters for an entire network and ignore the error tolerance capability of a network.

Privacy Preserving

Robust Time-Frequency Reconstruction by Learning Structured Sparsity

no code implementations30 Apr 2020 Lei Jiang, Haijian Zhang, Lei Yu

Time-frequency distributions (TFDs) play a vital role in providing descriptive analysis of non-stationary signals involved in realistic scenarios.

Cross-stained Segmentation from Renal Biopsy Images Using Multi-level Adversarial Learning

1 code implementation20 Feb 2020 Ke Mei, Chuang Zhu, Lei Jiang, Jun Liu, Yuanyuan Qiao

Experimental results on glomeruli segmentation from renal biopsy images indicate that our network is able to improve segmentation performance on target type of stained images and use unlabeled data to achieve similar accuracy to labeled data.

Improving Natural Language Understanding by Reverse Mapping Bytepair Encoding

no code implementations CONLL 2019 Chaodong Tong, Huailiang Peng, Qiong Dai, Lei Jiang, Jianghua Huang

We propose a method called reverse mapping bytepair encoding, which maps named-entity information and other word-level linguistic features back to subwords during the encoding procedure of bytepair encoding (BPE).

Natural Language Understanding RTE +1

SHE: A Fast and Accurate Deep Neural Network for Encrypted Data

1 code implementation NeurIPS 2019 Qian Lou, Lei Jiang

Since the LTFHE ReLU activations, max poolings, shifts and accumulations have small multiplicative depth overhead, SHE can implement much deeper network architectures with more convolutional and activation layers.


AutoQ: Automated Kernel-Wise Neural Network Quantization

no code implementations ICLR 2020 Qian Lou, Feng Guo, Lantao Liu, Minje Kim, Lei Jiang

Recent network quantization techniques quantize each weight kernel in a convolutional layer independently for higher inference accuracy, since the weight kernels in a layer exhibit different variances and hence have different amounts of redundancy.

AutoML Quantization

Pose Invariant 3D Face Reconstruction

no code implementations13 Nov 2018 Lei Jiang, Xiao-Jun Wu, Josef Kittler

Our method solves the problem of face reconstruction of a single image of a traditional method in a large pose, works on arbitrary Pose and Expressions, greatly improves the accuracy of reconstruction.

3D Face Reconstruction

DeepN-JPEG: A Deep Neural Network Favorable JPEG-based Image Compression Framework

no code implementations14 Mar 2018 Zihao Liu, Tao Liu, Wujie Wen, Lei Jiang, Jie Xu, Yanzhi Wang, Gang Quan

To reduce the data storage and transfer overhead in smart resource-limited Internet-of-Thing (IoT) systems, effective data compression is a "must-have" feature before transferring real-time produced dataset for training or classification.

Data Compression General Classification +2

PT-Spike: A Precise-Time-Dependent Single Spike Neuromorphic Architecture with Efficient Supervised Learning

no code implementations14 Mar 2018 Tao Liu, Lei Jiang, Yier Jin, Gang Quan, Wujie Wen

One of the most exciting advancements in AI over the last decade is the wide adoption of ANNs, such as DNN and CNN, in many real-world applications.

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