Search Results for author: Si Chen

Found 37 papers, 10 papers with code

StaPep: an open-source tool for the structure prediction and feature extraction of hydrocarbon-stapled peptides

1 code implementation28 Feb 2024 Zhe Wang, Jianping Wu, Mengjun Zheng, Chenchen Geng, Borui Zhen, Wei zhang, Hui Wu, Zhengyang Xu, Gang Xu, Si Chen, Xiang Li

Many tools exist for extracting structural and physiochemical descriptors from linear peptides to predict their properties, but similar tools for hydrocarbon-stapled peptides are lacking. Here, we present StaPep, a Python-based toolkit designed for generating 2D/3D structures and calculating 21 distinct features for hydrocarbon-stapled peptides. The current version supports hydrocarbon-stapled peptides containing 2 non-standard amino acids (norleucine and 2-aminoisobutyric acid) and 6 nonnatural anchoring residues (S3, S5, S8, R3, R5 and R8). Then we established a hand-curated dataset of 201 hydrocarbon-stapled peptides and 384 linear peptides with sequence information and experimental membrane permeability, to showcase StaPep's application in artificial intelligence projects. A machine learning-based predictor utilizing above calculated features was developed with AUC of 0. 85, for identifying cell-penetrating hydrocarbon-stapled peptides. StaPep's pipeline spans data retrieval, cleaning, structure generation, molecular feature calculation, and machine learning model construction for hydrocarbon-stapled peptides. The source codes and dataset are freely available on Github: https://github. com/dahuilangda/stapep_package.

Retrieval

High-Order Structure Based Middle-Feature Learning for Visible-Infrared Person Re-Identification

1 code implementation13 Dec 2023 Liuxiang Qiu, Si Chen, Yan Yan, Jing-Hao Xue, Da-Han Wang, Shunzhi Zhu

Existing VI-ReID methods ignore high-order structure information of features while being relatively difficult to learn a reasonable common feature space due to the large modality discrepancy between VIS and IR images.

Person Re-Identification

Learning to Rank for Active Learning via Multi-Task Bilevel Optimization

no code implementations25 Oct 2023 Zixin Ding, Si Chen, Ruoxi Jia, Yuxin Chen

To address these limitations, we propose a novel approach for active learning, which aims to select batches of unlabeled instances through a learned surrogate model for data acquisition.

Active Learning Bilevel Optimization +1

Multi-Scenario Ranking with Adaptive Feature Learning

no code implementations29 Jun 2023 Yu Tian, Bofang Li, Si Chen, Xubin Li, Hongbo Deng, Jian Xu, Bo Zheng, Qian Wang, Chenliang Li

Recently, Multi-Scenario Learning (MSL) is widely used in recommendation and retrieval systems in the industry because it facilitates transfer learning from different scenarios, mitigating data sparsity and reducing maintenance cost.

Retrieval Transfer Learning

Quantitative elemental imaging in eukaryotic algae

no code implementations26 Oct 2022 Stefan Schmollinger, Si Chen, Sabeeha S. Merchant

Accordingly, photosynthetic eukaryotes are of great interest for biotechnological exploitation, carbon sequestration and bioremediation, with many of the applications involving various trace elements and consequently affecting their quota and intracellular distribution.

SEEK: model extraction attack against hybrid secure inference protocols

no code implementations14 Sep 2022 Si Chen, Junfeng Fan

Security concerns about a machine learning model used in a prediction-as-a-service include the privacy of the model, the query and the result.

Model extraction

Learn-to-Decompose: Cascaded Decomposition Network for Cross-Domain Few-Shot Facial Expression Recognition

1 code implementation16 Jul 2022 Xinyi Zou, Yan Yan, Jing-Hao Xue, Si Chen, Hanzi Wang

Extensive experiments on both in-the-lab and in-the-wild compound expression datasets demonstrate the superiority of our proposed CDNet against several state-of-the-art FSL methods.

cross-domain few-shot learning Facial Expression Recognition +1

Using EBGAN for Anomaly Intrusion Detection

no code implementations21 Jun 2022 Yi Cui, Wenfeng Shen, Jian Zhang, Weijia Lu, Chuang Liu, Lin Sun, Si Chen

The generator in IDS-EBGAN is responsible for converting the original malicious network traffic in the training set into adversarial malicious examples.

Intrusion Detection

Turning a Curse into a Blessing: Enabling In-Distribution-Data-Free Backdoor Removal via Stabilized Model Inversion

no code implementations14 Jun 2022 Si Chen, Yi Zeng, Jiachen T. Wang, Won Park, Xun Chen, Lingjuan Lyu, Zhuoqing Mao, Ruoxi Jia

Our work is the first to provide a thorough understanding of leveraging model inversion for effective backdoor removal by addressing key questions about reconstructed samples' properties, perceptual similarity, and the potential presence of backdoor triggers.

Just Fine-tune Twice: Selective Differential Privacy for Large Language Models

1 code implementation15 Apr 2022 Weiyan Shi, Ryan Shea, Si Chen, Chiyuan Zhang, Ruoxi Jia, Zhou Yu

Utilizing the fact that sensitive information in language data tends to be sparse, Shi et al. (2021) formalized a DP notion extension called Selective Differential Privacy (SDP) to protect only the sensitive tokens defined by a policy function.

Stage-Aware Feature Alignment Network for Real-Time Semantic Segmentation of Street Scenes

no code implementations8 Mar 2022 Xi Weng, Yan Yan, Si Chen, Jing-Hao Xue, Hanzi Wang

In this paper, we present a novel Stage-aware Feature Alignment Network (SFANet) based on the encoder-decoder structure for real-time semantic segmentation of street scenes.

Real-Time Semantic Segmentation Segmentation

Label-Only Model Inversion Attacks via Boundary Repulsion

1 code implementation CVPR 2022 Mostafa Kahla, Si Chen, Hoang Anh Just, Ruoxi Jia

In this paper, we introduce an algorithm, Boundary-Repelling Model Inversion (BREP-MI), to invert private training data using only the target model's predicted labels.

Face Recognition

When Facial Expression Recognition Meets Few-Shot Learning: A Joint and Alternate Learning Framework

no code implementations18 Jan 2022 Xinyi Zou, Yan Yan, Jing-Hao Xue, Si Chen, Hanzi Wang

To alleviate the problem of limited base classes in our FER task, we propose a novel Emotion Guided Similarity Network (EGS-Net), consisting of an emotion branch and a similarity branch, based on a two-stage learning framework.

cross-domain few-shot learning Facial Expression Recognition +1

ModelPred: A Framework for Predicting Trained Model from Training Data

1 code implementation24 Nov 2021 Yingyan Zeng, Jiachen T. Wang, Si Chen, Hoang Anh Just, Ran Jin, Ruoxi Jia

In this work, we propose ModelPred, a framework that helps to understand the impact of changes in training data on a trained model.

Data Valuation Memorization

Adversarial Unlearning of Backdoors via Implicit Hypergradient

3 code implementations ICLR 2022 Yi Zeng, Si Chen, Won Park, Z. Morley Mao, Ming Jin, Ruoxi Jia

Particularly, its performance is more robust to the variation on triggers, attack settings, poison ratio, and clean data size.

Zero-Round Active Learning

no code implementations14 Jul 2021 Si Chen, Tianhao Wang, Ruoxi Jia

Our algorithm does not rely on any feedback from annotators in the target domain and hence, can be used to perform zero-round active learning or warm-start existing multi-round active learning strategies.

Active Learning Domain Adaptation

Learning Spatial-Semantic Relationship for Facial Attribute Recognition With Limited Labeled Data

no code implementations CVPR 2021 Ying Shu, Yan Yan, Si Chen, Jing-Hao Xue, Chunhua Shen, Hanzi Wang

First, three auxiliary tasks, consisting of a Patch Rotation Task (PRT), a Patch Segmentation Task (PST), and a Patch Classification Task (PCT), are jointly developed to learn the spatial-semantic relationship from large-scale unlabeled facial data.

Attribute Facial Attribute Classification +1

One-Round Active Learning

no code implementations23 Apr 2021 Tianhao Wang, Si Chen, Ruoxi Jia

In this work, we initiate the study of one-round active learning, which aims to select a subset of unlabeled data points that achieve the highest model performance after being labeled with only the information from initially labeled data points.

Active Learning

Sequential Recommendation in Online Games with Multiple Sequences, Tasks and User Levels

no code implementations13 Feb 2021 Si Chen, Yuqiu Qian, Hui Li, Chen Lin

We leverage Graph Neural Network and multi-task learning to design M$^3$Rec in order to model the complex information in the heterogeneous sequential recommendation scenario of Tencent Games.

Multi-Task Learning Sequential Recommendation

Knowledge-Enriched Distributional Model Inversion Attacks

2 code implementations ICCV 2021 Si Chen, Mostafa Kahla, Ruoxi Jia, Guo-Jun Qi

We present a novel inversion-specific GAN that can better distill knowledge useful for performing attacks on private models from public data.

Object-Adaptive LSTM Network for Real-time Visual Tracking with Adversarial Data Augmentation

no code implementations7 Feb 2020 Yihan Du, Yan Yan, Si Chen, Yang Hua

This strategy efficiently filters out some irrelevant proposals and avoids the redundant computation for feature extraction, which enables our method to operate faster than conventional classification-based tracking methods.

Computational Efficiency Data Augmentation +3

Adaptive Deep Metric Embeddings for Person Re-Identification under Occlusions

no code implementations7 Feb 2020 Wanxiang Yang, Yan Yan, Si Chen

In this paper, we propose a novel person ReID method, which learns the spatial dependencies between the local regions and extracts the discriminative feature representation of the pedestrian image based on Long Short-Term Memory (LSTM), dealing with the problem of occlusions.

Person Re-Identification

Joint Deep Learning of Facial Expression Synthesis and Recognition

no code implementations6 Feb 2020 Yan Yan, Ying Huang, Si Chen, Chunhua Shen, Hanzi Wang

Firstly, a facial expression synthesis generative adversarial network (FESGAN) is pre-trained to generate facial images with different facial expressions.

Facial Expression Recognition Facial Expression Recognition (FER) +1

The Global Convergence Analysis of the Bat Algorithm Using a Markovian Framework and Dynamical System Theory

no code implementations27 Mar 2019 Si Chen, Guo-Hua Peng, Xing-Shi He, Xin-She Yang

In order to prove the convergence of the bat algorithm, we have built a Markov model for the algorithm and proved that the state sequence of the bat population forms a finite homogeneous Markov chain, satisfying the global convergence criteria.

Multi-task Learning of Cascaded CNN for Facial Attribute Classification

no code implementations3 May 2018 Ni Zhuang, Yan Yan, Si Chen, Hanzi Wang

In order to address the above problems, we propose a novel multi-task learning of cas- caded convolutional neural network method, termed MCFA, for predicting multiple facial attributes simultaneously.

Attribute Classification +5

Multi-label Learning Based Deep Transfer Neural Network for Facial Attribute Classification

no code implementations3 May 2018 Ni Zhuang, Yan Yan, Si Chen, Hanzi Wang, Chunhua Shen

To address the above problem, we propose a novel deep transfer neural network method based on multi-label learning for facial attribute classification, termed FMTNet, which consists of three sub-networks: the Face detection Network (FNet), the Multi-label learning Network (MNet) and the Transfer learning Network (TNet).

Attribute Classification +6

Quadratic Projection Based Feature Extraction with Its Application to Biometric Recognition

no code implementations25 Mar 2016 Yan Yan, Hanzi Wang, Si Chen, Xiaochun Cao, David Zhang

This paper presents a novel quadratic projection based feature extraction framework, where a set of quadratic matrices is learned to distinguish each class from all other classes.

Deep Tracking: Visual Tracking Using Deep Convolutional Networks

no code implementations13 Dec 2015 Meera Hahn, Si Chen, Afshin Dehghan

In this paper, we study a discriminatively trained deep convolutional network for the task of visual tracking.

Visual Tracking

Cannot find the paper you are looking for? You can Submit a new open access paper.