Lichao Sun

Orcid: 0000-0003-1539-7939

Affiliations:
  • Lehigh University, Bethlehem, PA, USA
  • University of Illinois, IL, USA (former)
  • University of Nebraska Lincoln, NE, USA (former)


According to our database1, Lichao Sun authored at least 189 papers between 2016 and 2024.

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Bibliography

2024
Decentralized Federated Learning: A Survey and Perspective.
IEEE Internet Things J., November, 2024

ClassLIE: Structure- and Illumination-Adaptive Classification for Low-Light Image Enhancement.
IEEE Trans. Artif. Intell., September, 2024

Privacy and Robustness in Federated Learning: Attacks and Defenses.
IEEE Trans. Neural Networks Learn. Syst., July, 2024

Hawk: Rapid Android Malware Detection Through Heterogeneous Graph Attention Networks.
IEEE Trans. Neural Networks Learn. Syst., April, 2024

FedGKD: Toward Heterogeneous Federated Learning via Global Knowledge Distillation.
IEEE Trans. Computers, January, 2024

Source Inference Attacks: Beyond Membership Inference Attacks in Federated Learning.
IEEE Trans. Dependable Secur. Comput., 2024

MA-SAM: Modality-agnostic SAM adaptation for 3D medical image segmentation.
Medical Image Anal., 2024

PyGOD: A Python Library for Graph Outlier Detection.
J. Mach. Learn. Res., 2024

Evaluating site-of-care-related racial disparities in kidney graft failure using a novel federated learning framework.
J. Am. Medical Informatics Assoc., 2024

Empirical Perturbation Analysis of Linear System Solvers from a Data Poisoning Perspective.
CoRR, 2024

Evaluation of OpenAI o1: Opportunities and Challenges of AGI.
CoRR, 2024

TTT-Unet: Enhancing U-Net with Test-Time Training Layers for Biomedical Image Segmentation.
CoRR, 2024

Continual Diffuser (CoD): Mastering Continual Offline Reinforcement Learning with Experience Rehearsal.
CoRR, 2024

Biomedical SAM 2: Segment Anything in Biomedical Images and Videos.
CoRR, 2024

Unified-EGformer: Exposure Guided Lightweight Transformer for Mixed-Exposure Image Enhancement.
CoRR, 2024

Bora: Biomedical Generalist Video Generation Model.
CoRR, 2024

Self-Cognition in Large Language Models: An Exploratory Study.
CoRR, 2024

Virtual Context: Enhancing Jailbreak Attacks with Special Token Injection.
CoRR, 2024

UniGen: A Unified Framework for Textual Dataset Generation Using Large Language Models.
CoRR, 2024

Investigating and Defending Shortcut Learning in Personalized Diffusion Models.
CoRR, 2024

ViT-1.58b: Mobile Vision Transformers in the 1-bit Era.
CoRR, 2024

Quantifying AI Psychology: A Psychometrics Benchmark for Large Language Models.
CoRR, 2024

1+1>2: Can Large Language Models Serve as Cross-Lingual Knowledge Aggregators?
CoRR, 2024

ObscurePrompt: Jailbreaking Large Language Models via Obscure Input.
CoRR, 2024

GUI-WORLD: A Dataset for GUI-oriented Multimodal LLM-based Agents.
CoRR, 2024

The Best of Both Worlds: Toward an Honest and Helpful Large Language Model.
CoRR, 2024

Decision Mamba: Reinforcement Learning via Hybrid Selective Sequence Modeling.
CoRR, 2024

Variational Bayes for Federated Continual Learning.
CoRR, 2024

Does Your Neural Code Completion Model Use My Code? A Membership Inference Approach.
CoRR, 2024

Optimization-based Prompt Injection Attack to LLM-as-a-Judge.
CoRR, 2024

Mora: Enabling Generalist Video Generation via A Multi-Agent Framework.
CoRR, 2024

Medical Unlearnable Examples: Securing Medical Data from Unauthorized Traning via Sparsity-Aware Local Masking.
CoRR, 2024

Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models.
CoRR, 2024

GTBench: Uncovering the Strategic Reasoning Limitations of LLMs via Game-Theoretic Evaluations.
CoRR, 2024

Rec-GPT4V: Multimodal Recommendation with Large Vision-Language Models.
CoRR, 2024

I Think, Therefore I am: Awareness in Large Language Models.
CoRR, 2024

The Radiation Oncology NLP Database.
CoRR, 2024

LLM-as-a-Coauthor: The Challenges of Detecting LLM-Human Mixcase.
CoRR, 2024

TrustLLM: Trustworthiness in Large Language Models.
CoRR, 2024

Lecture-style Tutorial: Towards Graph Foundation Models.
Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

From Creation to Clarification: ChatGPT's Journey Through the Fake News Quagmire.
Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

Unveiling the Secrets without Data: Can Graph Neural Networks Be Exploited through Data-Free Model Extraction Attacks?
Proceedings of the 33rd USENIX Security Symposium, 2024

Deep Efficient Private Neighbor Generation for Subgraph Federated Learning.
Proceedings of the 2024 SIAM International Conference on Data Mining, 2024

LLM-as-a-Coauthor: Can Mixed Human-Written and Machine-Generated Text Be Detected?
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2024, 2024

ReTA: Recursively Thinking Ahead to Improve the Strategic Reasoning of Large Language Models.
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

Frequency-Aware GAN for Imperceptible Transfer Attack on 3D Point Clouds.
Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024

Conditional Score-Based Diffusion Model for Cortical Thickness Trajectory Prediction.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

Medical Image Synthesis via Fine-Grained Image-Text Alignment and Anatomy-Pathology Prompting.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

FedSecurity: A Benchmark for Attacks and Defenses in Federated Learning and Federated LLMs.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

In-Context Decision Transformer: Reinforcement Learning via Hierarchical Chain-of-Thought.
Proceedings of the Forty-first International Conference on Machine Learning, 2024


Improving Interpretation Faithfulness for Vision Transformers.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

MLLM-as-a-Judge: Assessing Multimodal LLM-as-a-Judge with Vision-Language Benchmark.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

MetaTool Benchmark for Large Language Models: Deciding Whether to Use Tools and Which to Use.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Virtual Context Enhancing Jailbreak Attacks with Special Token Injection.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

SpecHub: Provable Acceleration to Multi-Draft Speculative Decoding.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

1+1\textgreater2: Can Large Language Models Serve as Cross-Lingual Knowledge Aggregators?
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

CodeIP: A Grammar-Guided Multi-Bit Watermark for Large Language Models of Code.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

Physical Backdoor: Towards Temperature-Based Backdoor Attacks in the Physical World.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

ACT-Diffusion: Efficient Adversarial Consistency Training for One-Step Diffusion Models.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

MetaCloak: Preventing Unauthorized Subject-Driven Text-to-Image Diffusion-Based Synthesis via Meta-Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

AlignBench: Benchmarking Chinese Alignment of Large Language Models.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

Revisiting Gradient Pruning: A Dual Realization for Defending against Gradient Attacks.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Stable Unlearnable Example: Enhancing the Robustness of Unlearnable Examples via Stable Error-Minimizing Noise.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Adversarial Attack and Defense on Graph Data: A Survey.
IEEE Trans. Knowl. Data Eng., August, 2023

Toward Personalized Federated Learning Via Group Collaboration in IIoT.
IEEE Trans. Ind. Informatics, August, 2023

Triadic Closure Sensitive Influence Maximization.
ACM Trans. Knowl. Discov. Data, July, 2023

Personalized Edge Intelligence via Federated Self-Knowledge Distillation.
IEEE Trans. Parallel Distributed Syst., February, 2023

An in-depth study on key nodes in social networks.
Intell. Data Anal., 2023

Efficient Few-Shot Clinical Task Adaptation with Large Language Models.
CoRR, 2023

Holistic Evaluation of GPT-4V for Biomedical Imaging.
CoRR, 2023

Robust Computer Vision in an Ever-Changing World: A Survey of Techniques for Tackling Distribution Shifts.
CoRR, 2023

AlignBench: Benchmarking Chinese Alignment of Large Language Models.
CoRR, 2023

Improving Faithfulness for Vision Transformers.
CoRR, 2023

ACT: Adversarial Consistency Models.
CoRR, 2023

Toward Robust Imperceptible Perturbation against Unauthorized Text-to-image Diffusion-based Synthesis.
CoRR, 2023

EditShield: Protecting Unauthorized Image Editing by Instruction-guided Diffusion Models.
CoRR, 2023

Jailbreaking GPT-4V via Self-Adversarial Attacks with System Prompts.
CoRR, 2023

Multimodal ChatGPT for Medical Applications: an Experimental Study of GPT-4V.
CoRR, 2023

Towards Graph Foundation Models: A Survey and Beyond.
CoRR, 2023

GraphCloak: Safeguarding Task-specific Knowledge within Graph-structured Data from Unauthorized Exploitation.
CoRR, 2023

MetaAgents: Simulating Interactions of Human Behaviors for LLM-based Task-oriented Coordination via Collaborative Generative Agents.
CoRR, 2023

Harnessing the Power of ChatGPT in Fake News: An In-Depth Exploration in Generation, Detection and Explanation.
CoRR, 2023

InstructionGPT-4: A 200-Instruction Paradigm for Fine-Tuning MiniGPT-4.
CoRR, 2023

Evaluating Large Language Models for Radiology Natural Language Processing.
CoRR, 2023

Instruction Mining: High-Quality Instruction Data Selection for Large Language Models.
CoRR, 2023

TrustGPT: A Benchmark for Trustworthy and Responsible Large Language Models.
CoRR, 2023

A Simple Unified Uncertainty-Guided Framework for Offline-to-Online Reinforcement Learning.
CoRR, 2023

FedMLSecurity: A Benchmark for Attacks and Defenses in Federated Learning and LLMs.
CoRR, 2023

Instructed Diffuser with Temporal Condition Guidance for Offline Reinforcement Learning.
CoRR, 2023

DiffusionShield: A Watermark for Copyright Protection against Generative Diffusion Models.
CoRR, 2023

Decentralized Federated Learning: A Survey and Perspective.
CoRR, 2023

BiomedGPT: A Unified and Generalist Biomedical Generative Pre-trained Transformer for Vision, Language, and Multimodal Tasks.
CoRR, 2023

Watermarking Text Data on Large Language Models for Dataset Copyright Protection.
CoRR, 2023

BadGPT: Exploring Security Vulnerabilities of ChatGPT via Backdoor Attacks to InstructGPT.
CoRR, 2023

FreMAE: Fourier Transform Meets Masked Autoencoders for Medical Image Segmentation.
CoRR, 2023

Memory-adaptive Depth-wise Heterogenous Federated Learning.
CoRR, 2023

A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT.
CoRR, 2023

Unlearnable Graph: Protecting Graphs from Unauthorized Exploitation.
CoRR, 2023

Securing Biomedical Images from Unauthorized Training with Anti-Learning Perturbation.
CoRR, 2023

A Comprehensive Survey on Pretrained Foundation Models: A History from BERT to ChatGPT.
CoRR, 2023

Backdoor Attacks to Pre-trained Unified Foundation Models.
CoRR, 2023

Attacking Fake News Detectors via Manipulating News Social Engagement.
Proceedings of the ACM Web Conference 2023, 2023

Scalable Adversarial Attack Algorithms on Influence Maximization.
Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

End-to-End Multimodal Fact-Checking and Explanation Generation: A Challenging Dataset and Models.
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

A Comprehensive Study on Text-attributed Graphs: Benchmarking and Rethinking.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Scalable Fair Influence Maximization.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning Generalizable Agents via Saliency-guided Features Decorrelation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

PASS: Personalized Advertiser-aware Sponsored Search.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Secure Embedding Aggregation for Federated Representation Learning.
Proceedings of the IEEE International Symposium on Information Theory, 2023

RAIN: RegulArization on Input and Network for Black-Box Domain Adaptation.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Transferable Unlearnable Examples.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

SCALE-UP: An Efficient Black-box Input-level Backdoor Detection via Analyzing Scaled Prediction Consistency.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Benchmarking and Analyzing Robust Point Cloud Recognition: Bag of Tricks for Defending Adversarial Examples.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Attacking Neural Networks with Neural Networks: Towards Deep Synchronization for Backdoor Attacks.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

PointCA: Evaluating the Robustness of 3D Point Cloud Completion Models against Adversarial Examples.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

SEAT: Stable and Explainable Attention.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Tackling Data Heterogeneity in Federated Learning with Class Prototypes.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Membership Inference Attacks on Machine Learning: A Survey.
ACM Comput. Surv., January, 2022

Joint Stance and Rumor Detection in Hierarchical Heterogeneous Graph.
IEEE Trans. Neural Networks Learn. Syst., 2022

FedBERT: When Federated Learning Meets Pre-training.
ACM Trans. Intell. Syst. Technol., 2022

A Survey on Text Classification: From Traditional to Deep Learning.
ACM Trans. Intell. Syst. Technol., 2022

Federated Multi-view Learning for Private Medical Data Integration and Analysis.
ACM Trans. Intell. Syst. Technol., 2022

Privacy-Preserving Federated Depression Detection From Multisource Mobile Health Data.
IEEE Trans. Ind. Informatics, 2022

Fully Privacy-Preserving Federated Representation Learning via Secure Embedding Aggregation.
IACR Cryptol. ePrint Arch., 2022

Toward Better Target Representation for Source-Free and Black-Box Domain Adaptation.
CoRR, 2022

Benchmarking Node Outlier Detection on Graphs.
CoRR, 2022

Efficient Federated Learning on Knowledge Graphs via Privacy-preserving Relation Embedding Aggregation.
CoRR, 2022

DoubleStar: Long-Range Attack Towards Depth Estimation based Obstacle Avoidance in Autonomous Systems.
Proceedings of the 31st USENIX Security Symposium, 2022

You see what I want you to see: poisoning vulnerabilities in neural code search.
Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2022

BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed Graphs.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Distributional Reward Estimation for Effective Multi-agent Deep Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Backdoor Attacks on Crowd Counting.
Proceedings of the MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10, 2022

Structure-Preserving Graph Kernel for Brain Network Classification.
Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022

Data-Free Adversarial Knowledge Distillation for Graph Neural Networks.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Membership Inference via Backdooring.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

How to Inject Backdoors with Better Consistency: Logit Anchoring on Clean Data.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Rethinking the Video Sampling and Reasoning Strategies for Temporal Sentence Grounding.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Efficient Federated Learning on Knowledge Graphs via Privacy-preserving Relation Embedding Aggregation.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Joint Embedding of Structural and Functional Brain Networks with Graph Neural Networks for Mental Illness Diagnosis.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

The 1st International Workshop on Federated Learning with Graph Data (FedGraph).
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Multi-View Brain Network Analysis with Cross-View Missing Network Generation.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022

Query and Extract: Refining Event Extraction as Type-oriented Binary Decoding.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

SplitFed: When Federated Learning Meets Split Learning.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Kollector: Detecting Fraudulent Activities on Mobile Devices Using Deep Learning.
IEEE Trans. Mob. Comput., 2021

Localization of multiple diffusion sources based on overlapping community detection.
Knowl. Based Syst., 2021

FedHM: Efficient Federated Learning for Heterogeneous Models via Low-rank Factorization.
CoRR, 2021

Multiplex Graph Networks for Multimodal Brain Network Analysis.
CoRR, 2021

Global Knowledge Distillation in Federated Learning.
CoRR, 2021

Killing Two Birds with One Stone: Stealing Model and Inferring Attribute from BERT-based APIs.
CoRR, 2021

Federated Multi-View Learning for Private Medical Data Integration and Analysis.
CoRR, 2021

Federated Depression Detection from Multi-SourceMobile Health Data.
CoRR, 2021

Automatically predicting cyber attack preference with attributed heterogeneous attention networks and transductive learning.
Comput. Secur., 2021

User Preference-aware Fake News Detection.
Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

Subgraph Federated Learning with Missing Neighbor Generation.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Model Extraction and Adversarial Transferability, Your BERT is Vulnerable!
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Secure Deep Graph Generation with Link Differential Privacy.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

LDP-FL: Practical Private Aggregation in Federated Learning with Local Differential Privacy.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Federated Model Distillation with Noise-Free Differential Privacy.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Graph Entropy Guided Node Embedding Dimension Selection for Graph Neural Networks.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Source Inference Attacks in Federated Learning.
Proceedings of the IEEE International Conference on Data Mining, 2021

DSKReG: Differentiable Sampling on Knowledge Graph for Recommendation with Relational GNN.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Graph-based Semi-Supervised Learning by Strengthening Local Label Consistency.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

This Sneaky Piggy Went to the Android Ad Market: Misusing Mobile Sensors for Stealthy Data Exfiltration.
Proceedings of the CCS '21: 2021 ACM SIGSAC Conference on Computer and Communications Security, Virtual Event, Republic of Korea, November 15, 2021

2020
Privacy and Robustness in Federated Learning: Attacks and Defenses.
CoRR, 2020

Mixup-Transfomer: Dynamic Data Augmentation for NLP Tasks.
CoRR, 2020

A Survey on Text Classification: From Shallow to Deep Learning.
CoRR, 2020

LDP-FL: Practical Private Aggregation in Federated Learning with Local Differential Privacy.
CoRR, 2020

Secure Network Release with Link Privacy.
CoRR, 2020

Adv-BERT: BERT is not robust on misspellings! Generating nature adversarial samples on BERT.
CoRR, 2020

Differentially Private Deep Learning with Smooth Sensitivity.
CoRR, 2020

Influence Maximization with Spontaneous User Adoption.
Proceedings of the WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, 2020

Target Privacy Preserving for Social Networks.
Proceedings of the 36th IEEE International Conference on Data Engineering, 2020

Mixup-Transformer: Dynamic Data Augmentation for NLP Tasks.
Proceedings of the 28th International Conference on Computational Linguistics, 2020

2019
Self-Activation Influence Maximization.
CoRR, 2019

Meta-path Reduction with Transition Probability Preserving in Heterogeneous Information Network.
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

Private Model Compression via Knowledge Distillation.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Significant Permission Identification for Machine-Learning-Based Android Malware Detection.
IEEE Trans. Ind. Informatics, 2018

Adversarial Attack and Defense on Graph Data: A Survey.
CoRR, 2018

Unsupervised Meta-path Reduction on Heterogeneous Information Networks.
CoRR, 2018

Multi-Round Influence Maximization (Extended Version).
CoRR, 2018

Multi-Round Influence Maximization.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Deep Learning towards Mobile Applications.
Proceedings of the 38th IEEE International Conference on Distributed Computing Systems, 2018

Joint Embedding of Meta-Path and Meta-Graph for Heterogeneous Information Networks.
Proceedings of the 2018 IEEE International Conference on Big Knowledge, 2018

2017
Sequential Keystroke Behavioral Biometrics for Mobile User Identification via Multi-view Deep Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Coupled Sparse Matrix Factorization for Response Time Prediction in Logistics Services.
Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017

Contaminant removal for Android malware detection systems.
Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

2016
DroidClassifier: Efficient Adaptive Mining of Application-Layer Header for Classifying Android Malware.
Proceedings of the Security and Privacy in Communication Networks, 2016

SigPID: significant permission identification for android malware detection.
Proceedings of the 11th International Conference on Malicious and Unwanted Software, 2016


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