Pin-Yu Chen

Orcid: 0000-0003-1039-8369

According to our database1, Pin-Yu Chen authored at least 394 papers between 2010 and 2024.

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Bibliography

2024
Correction to: Stochastic inexact augmented Lagrangian method for nonconvex expectation constrained optimization.
Comput. Optim. Appl., November, 2024

Stochastic inexact augmented Lagrangian method for nonconvex expectation constrained optimization.
Comput. Optim. Appl., January, 2024

Neural Clamping: Joint Input Perturbation and Temperature Scaling for Neural Network Calibration.
Trans. Mach. Learn. Res., 2024

To Transfer or Not to Transfer: Suppressing Concepts from Source Representations.
Trans. Mach. Learn. Res., 2024

CURE: A deep learning framework pre-trained on large-scale patient data for treatment effect estimation.
Patterns, 2024

LabSafety Bench: Benchmarking LLMs on Safety Issues in Scientific Labs.
CoRR, 2024

Position Specific Scoring Is All You Need? Revisiting Protein Sequence Classification Tasks.
CoRR, 2024

SEAL: Safety-enhanced Aligned LLM Fine-tuning via Bilevel Data Selection.
CoRR, 2024

SONAR: A Synthetic AI-Audio Detection Framework and Benchmark.
CoRR, 2024

Large Language Models can be Strong Self-Detoxifiers.
CoRR, 2024

Justice or Prejudice? Quantifying Biases in LLM-as-a-Judge.
CoRR, 2024

Training Nonlinear Transformers for Chain-of-Thought Inference: A Theoretical Generalization Analysis.
CoRR, 2024

Attack Atlas: A Practitioner's Perspective on Challenges and Pitfalls in Red Teaming GenAI.
CoRR, 2024

Evaluating Image Hallucination in Text-to-Image Generation with Question-Answering.
CoRR, 2024

When Does Visual Prompting Outperform Linear Probing for Vision-Language Models? A Likelihood Perspective.
CoRR, 2024

Linking Robustness and Generalization: A k* Distribution Analysis of Concept Clustering in Latent Space for Vision Models.
CoRR, 2024

Data-Driven Lipschitz Continuity: A Cost-Effective Approach to Improve Adversarial Robustness.
CoRR, 2024

The Devil is in the Neurons: Interpreting and Mitigating Social Biases in Pre-trained Language Models.
CoRR, 2024

PSBD: Prediction Shift Uncertainty Unlocks Backdoor Detection.
CoRR, 2024

AutoJailbreak: Exploring Jailbreak Attacks and Defenses through a Dependency Lens.
CoRR, 2024

RIGID: A Training-free and Model-Agnostic Framework for Robust AI-Generated Image Detection.
CoRR, 2024

Defensive Prompt Patch: A Robust and Interpretable Defense of LLMs against Jailbreak Attacks.
CoRR, 2024

AI Risk Management Should Incorporate Both Safety and Security.
CoRR, 2024

Navigating the Safety Landscape: Measuring Risks in Finetuning Large Language Models.
CoRR, 2024

Safe LoRA: the Silver Lining of Reducing Safety Risks when Fine-tuning Large Language Models.
CoRR, 2024

Self-Taught Recognizer: Toward Unsupervised Adaptation for Speech Foundation Models.
CoRR, 2024

Improving Transformers using Faithful Positional Encoding.
CoRR, 2024

Graph is all you need? Lightweight data-agnostic neural architecture search without training.
CoRR, 2024

Steal Now and Attack Later: Evaluating Robustness of Object Detection against Black-box Adversarial Attacks.
CoRR, 2024

NaNa and MiGu: Semantic Data Augmentation Techniques to Enhance Protein Classification in Graph Neural Networks.
CoRR, 2024

Larimar: Large Language Models with Episodic Memory Control.
CoRR, 2024

How does promoting the minority fraction affect generalization? A theoretical study of the one-hidden-layer neural network on group imbalance.
CoRR, 2024

Detectors for Safe and Reliable LLMs: Implementations, Uses, and Limitations.
CoRR, 2024

Gradient Cuff: Detecting Jailbreak Attacks on Large Language Models by Exploring Refusal Loss Landscapes.
CoRR, 2024

DiffuseKronA: A Parameter Efficient Fine-tuning Method for Personalized Diffusion Models.
CoRR, 2024

Training Nonlinear Transformers for Efficient In-Context Learning: A Theoretical Learning and Generalization Analysis.
CoRR, 2024

A Quantum-Classical Collaborative Training Architecture Based on Quantum State Fidelity.
CoRR, 2024

From PEFT to DEFT: Parameter Efficient Finetuning for Reducing Activation Density in Transformers.
CoRR, 2024

TrustLLM: Trustworthiness in Large Language Models.
CoRR, 2024

Masking Improves Contrastive Self-Supervised Learning for ConvNets, and Saliency Tells You Where.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

Improving Privacy-Preserving Vertical Federated Learning by Efficient Communication with ADMM.
Proceedings of the IEEE Conference on Secure and Trustworthy Machine Learning, 2024

Model Reprogramming Outperforms Fine-tuning on Out-of-distribution Data in Text-Image Encoders.
Proceedings of the IEEE Conference on Secure and Trustworthy Machine Learning, 2024

On Dark Knowledge for Distilling Generators.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2024

Language Agnostic Code Embeddings.
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

SepsisLab: Early Sepsis Prediction with Uncertainty Quantification and Active Sensing.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Computational Complexity of Verifying the Group No-show Paradox.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Learning on Transformers is Provable Low-Rank and Sparse: A One-layer Analysis.
Proceedings of the 13th IEEE Sensor Array and Multichannel Signal Processing Workshop, 2024

Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Learning Optimal Projection for Forecast Reconciliation of Hierarchical Time Series.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

What Improves the Generalization of Graph Transformers? A Theoretical Dive into the Self-attention and Positional Encoding.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

How Do Nonlinear Transformers Learn and Generalize in In-Context Learning?
Proceedings of the Forty-first International Conference on Machine Learning, 2024

What Would Gauss Say About Representations? Probing Pretrained Image Models using Synthetic Gaussian Benchmarks.
Proceedings of the Forty-first International Conference on Machine Learning, 2024


Be Your Own Neighborhood: Detecting Adversarial Examples by the Neighborhood Relations Built on Self-Supervised Learning.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Larimar: Large Language Models with Episodic Memory Control.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

A Provably Effective Method for Pruning Experts in Fine-tuned Sparse Mixture-of-Experts.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Prompting4Debugging: Red-Teaming Text-to-Image Diffusion Models by Finding Problematic Prompts.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

SF-DQN: Provable Knowledge Transfer using Successor Feature for Deep Reinforcement Learning.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

AutoVP: An Automated Visual Prompting Framework and Benchmark.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Ring-A-Bell! How Reliable are Concept Removal Methods For Diffusion Models?
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!
Proceedings of the Twelfth International Conference on Learning Representations, 2024

The Devil is in the Neurons: Interpreting and Mitigating Social Biases in Language Models.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Large Language Models are Efficient Learners of Noise-Robust Speech Recognition.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Rethinking Backdoor Attacks on Dataset Distillation: A Kernel Method Perspective.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

It's Never Too Late: Fusing Acoustic Information into Large Language Models for Automatic Speech Recognition.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Time-LLM: Time Series Forecasting by Reprogramming Large Language Models.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Variance Reduction Can Improve Trade-Off in Multi-Objective Learning.
Proceedings of the IEEE International Conference on Acoustics, 2024

DDI-CoCo: A Dataset for Understanding the Effect of Color Contrast in Machine-Assisted Skin Disease Detection.
Proceedings of the IEEE International Conference on Acoustics, 2024

Uncovering the Hidden Cost of Model Compression.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Overload: Latency Attacks on Object Detection for Edge Devices.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

MulBERRY: Enabling Bit-Error Robustness for Energy-Efficient Multi-Agent Autonomous Systems.
Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2024

Duwak: Dual Watermarks in Large Language Models.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

A Deep Dive into the Trade-Offs of Parameter-Efficient Preference Alignment Techniques.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

Model Reprogramming: Resource-Efficient Cross-Domain Machine Learning.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Elijah: Eliminating Backdoors Injected in Diffusion Models via Distribution Shift.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
AI Maintenance: A Robustness Perspective.
Computer, February, 2023

Exploiting Low-Rank Tensor-Train Deep Neural Networks Based on Riemannian Gradient Descent With Illustrations of Speech Processing.
IEEE ACM Trans. Audio Speech Lang. Process., 2023

Diagnostic spatio-temporal transformer with faithful encoding.
Knowl. Based Syst., 2023

Robust Event Classification Using Imperfect Real-World PMU Data.
IEEE Internet Things J., 2023

Conditional Modeling Based Automatic Video Summarization.
CoRR, 2023

Ring-A-Bell! How Reliable are Concept Removal Methods for Diffusion Models?
CoRR, 2023

AutoVP: An Automated Visual Prompting Framework and Benchmark.
CoRR, 2023

Exploring the Benefits of Differentially Private Pre-training and Parameter-Efficient Fine-tuning for Table Transformers.
CoRR, 2023

Reprogramming under constraints: Revisiting efficient and reliable transferability of lottery tickets.
CoRR, 2023

NeuralFuse: Learning to Improve the Accuracy of Access-Limited Neural Network Inference in Low-Voltage Regimes.
CoRR, 2023

Virus2Vec: Viral Sequence Classification Using Machine Learning.
CoRR, 2023

GREAT Score: Global Robustness Evaluation of Adversarial Perturbation using Generative Models.
CoRR, 2023

Certified Interpretability Robustness for Class Activation Mapping.
CoRR, 2023

Reprogramming Pretrained Language Models for Protein Sequence Representation Learning.
CoRR, 2023

Treatment Learning Causal Transformer for Noisy Image Classification.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Pessimistic Model Selection for Offline Deep Reinforcement Learning.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

Less is More: Dimension Reduction Finds On-Manifold Adversarial Examples in Hard-Label Attacks.
Proceedings of the 2023 IEEE Conference on Secure and Trustworthy Machine Learning, 2023

Reprogrammable-FL: Improving Utility-Privacy Tradeoff in Federated Learning via Model Reprogramming.
Proceedings of the 2023 IEEE Conference on Secure and Trustworthy Machine Learning, 2023

On the Convergence and Sample Complexity Analysis of Deep Q-Networks with ε-Greedy Exploration.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Uncovering and Quantifying Social Biases in Code Generation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

RADAR: Robust AI-Text Detection via Adversarial Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

VillanDiffusion: A Unified Backdoor Attack Framework for Diffusion Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

HyPoradise: An Open Baseline for Generative Speech Recognition with Large Language Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Inference and Denoise: Causal Inference-Based Neural Speech Enhancement.
Proceedings of the 33rd IEEE International Workshop on Machine Learning for Signal Processing, 2023

Spectral Adversarial MixUp for Few-Shot Unsupervised Domain Adaptation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Unveiling the Robustness of Machine Learning Models in Classifying COVID-19 Spike Sequences.
Proceedings of the Bioinformatics Research and Applications - 19th International Symposium, 2023

MENTOR: Multilingual Text Detection Toward Learning by Analogy.
IROS, 2023

Neural Model Reprogramming with Similarity Based Mapping for Low-Resource Spoken Command Recognition.
Proceedings of the 24th Annual Conference of the International Speech Communication Association, 2023

Learning to Design Fair and Private Voting Rules (Extended Abstract).
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Compressed Decentralized Proximal Stochastic Gradient Method for Nonconvex Composite Problems with Heterogeneous Data.
Proceedings of the International Conference on Machine Learning, 2023

Which Features are Learnt by Contrastive Learning? On the Role of Simplicity Bias in Class Collapse and Feature Suppression.
Proceedings of the International Conference on Machine Learning, 2023

Reprogramming Pretrained Language Models for Antibody Sequence Infilling.
Proceedings of the International Conference on Machine Learning, 2023

MultiRobustBench: Benchmarking Robustness Against Multiple Attacks.
Proceedings of the International Conference on Machine Learning, 2023

Patch-level Routing in Mixture-of-Experts is Provably Sample-efficient for Convolutional Neural Networks.
Proceedings of the International Conference on Machine Learning, 2023

Identification of the Adversary from a Single Adversarial Example.
Proceedings of the International Conference on Machine Learning, 2023

A Theoretical Understanding of Shallow Vision Transformers: Learning, Generalization, and Sample Complexity.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Joint Edge-Model Sparse Learning is Provably Efficient for Graph Neural Networks.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Robust Mixture-of-Expert Training for Convolutional Neural Networks.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Exploring the Benefits of Visual Prompting in Differential Privacy.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Better May Not Be Fairer: A Study on Subgroup Discrepancy in Image Classification.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Low-Resource Music Genre Classification with Cross-Modal Neural Model Reprogramming.
Proceedings of the IEEE International Conference on Acoustics, 2023

Certified Robustness of Quantum Classifiers Against Adversarial Examples Through Quantum Noise.
Proceedings of the IEEE International Conference on Acoustics, 2023

Visual Prompting for Adversarial Robustness.
Proceedings of the IEEE International Conference on Acoustics, 2023

Lost In Translation: Generating Adversarial Examples Robust to Round-Trip Translation.
Proceedings of the IEEE International Conference on Acoustics, 2023

Locally Differentially Private Document Generation Using Zero Shot Prompting.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

BERRY: Bit Error Robustness for Energy-Efficient Reinforcement Learning-Based Autonomous Systems.
Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023

Causalainer: Causal Explainer for Automatic Video Summarization.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Towards Compositional Adversarial Robustness: Generalizing Adversarial Training to Composite Semantic Perturbations.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

How to Backdoor Diffusion Models?
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Understanding and Improving Visual Prompting: A Label-Mapping Perspective.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Counterfactually Guided Policy Transfer in Clinical Settings.
Proceedings of the Conference on Health, Inference, and Learning, 2023

Unraveling the Connections between Privacy and Certified Robustness in Federated Learning Against Poisoning Attacks.
Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security, 2023

Convex Bounds on the Softmax Function with Applications to Robustness Verification.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

When Neural Networks Fail to Generalize? A Model Sensitivity Perspective.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

NCTV: Neural Clamping Toolkit and Visualization for Neural Network Calibration.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Holistic Adversarial Robustness of Deep Learning Models.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Active Sampling of Multiple Sources for Sequential Estimation.
IEEE Trans. Signal Process., 2022

On the Adversarial Robustness of Vision Transformers.
Trans. Mach. Learn. Res., 2022

Optimizing molecules using efficient queries from property evaluations.
Nat. Mach. Intell., 2022

Learning to Design Fair and Private Voting Rules.
J. Artif. Intell. Res., 2022

On Human Visual Contrast Sensitivity and Machine Vision Robustness: A Comparative Study.
CoRR, 2022

Better May Not Be Fairer: Can Data Augmentation Mitigate Subgroup Degradation?
CoRR, 2022

Low-Resource Music Genre Classification with Advanced Neural Model Reprogramming.
CoRR, 2022

An Empirical Evaluation of Zeroth-Order Optimization Methods on AI-driven Molecule Optimization.
CoRR, 2022

Reprogramming Large Pretrained Language Models for Antibody Sequence Infilling.
CoRR, 2022

Rethinking Normalization Methods in Federated Learning.
CoRR, 2022

SynBench: Task-Agnostic Benchmarking of Pretrained Representations using Synthetic Data.
CoRR, 2022

Uncovering the Connection Between Differential Privacy and Certified Robustness of Federated Learning against Poisoning Attacks.
CoRR, 2022

Be Your Own Neighborhood: Detecting Adversarial Example by the Neighborhood Relations Built on Self-Supervised Learning.
CoRR, 2022

Improving Privacy-Preserving Vertical Federated Learning by Efficient Communication with ADMM.
CoRR, 2022

Benchmarking Machine Learning Robustness in Covid-19 Genome Sequence Classification.
CoRR, 2022

On Certifying and Improving Generalization to Unseen Domains.
CoRR, 2022

Theoretical Error Performance Analysis for Variational Quantum Circuit Based Functional Regression.
CoRR, 2022

Learning Geometrically Disentangled Representations of Protein Folding Simulations.
CoRR, 2022

Evaluating the Adversarial Robustness for Fourier Neural Operators.
CoRR, 2022

Treatment Learning Transformer for Noisy Image Classification.
CoRR, 2022

Auto-Transfer: Learning to Route Transferrable Representations.
CoRR, 2022

How does unlabeled data improve generalization in self-training? A one-hidden-layer theoretical analysis.
CoRR, 2022

Neural Capacitance: A New Perspective of Neural Network Selection via Edge Dynamics.
CoRR, 2022

Distributed adversarial training to robustify deep neural networks at scale.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

Make an Omelette with Breaking Eggs: Zero-Shot Learning for Novel Attribute Synthesis.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Stock Prediction.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

The Fourth Workshop on Adversarial Learning Methods for Machine Learning and Data Mining (AdvML 2022).
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Iterative Qubits Management for Quantum Index Searching in a Hybrid System.
Proceedings of the IEEE International Performance, 2022

CARBEN: Composite Adversarial Robustness Benchmark.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Towards Creativity Characterization of Generative Models via Group-Based Subset Scanning.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

CAT: Customized Adversarial Training for Improved Robustness.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Generalization Guarantee of Training Graph Convolutional Networks with Graph Topology Sampling.
Proceedings of the International Conference on Machine Learning, 2022

Revisiting Contrastive Learning through the Lens of Neighborhood Component Analysis: an Integrated Framework.
Proceedings of the International Conference on Machine Learning, 2022

Linearity Grafting: Relaxed Neuron Pruning Helps Certifiable Robustness.
Proceedings of the International Conference on Machine Learning, 2022

Sharp-MAML: Sharpness-Aware Model-Agnostic Meta Learning.
Proceedings of the International Conference on Machine Learning, 2022

Causal Video Summarizer for Video Exploration.
Proceedings of the IEEE International Conference on Multimedia and Expo, 2022

Auto-Transfer: Learning to Route Transferable Representations.
Proceedings of the Tenth International Conference on Learning Representations, 2022

MAML is a Noisy Contrastive Learner in Classification.
Proceedings of the Tenth International Conference on Learning Representations, 2022

How unlabeled data improve generalization in self-training? A one-hidden-layer theoretical analysis.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Analyzing and Improving Resilience and Robustness of Autonomous Systems.
Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design, 2022

When BERT Meets Quantum Temporal Convolution Learning for Text Classification in Heterogeneous Computing.
Proceedings of the IEEE International Conference on Acoustics, 2022

When Does Backdoor Attack Succeed in Image Reconstruction? A Study of Heuristics vs. Bi-Level Solution.
Proceedings of the IEEE International Conference on Acoustics, 2022

Real-World Adversarial Examples Via Makeup.
Proceedings of the IEEE International Conference on Acoustics, 2022

Knowledge Graph Guided Simultaneous Forecasting and Network Learning for Multivariate Financial Time Series.
Proceedings of the 3rd ACM International Conference on AI in Finance, 2022

A Spectral View of Randomized Smoothing Under Common Corruptions: Benchmarking and Improving Certified Robustness.
Proceedings of the Computer Vision - ECCV 2022, 2022

Robust Text CAPTCHAs Using Adversarial Examples.
Proceedings of the IEEE International Conference on Big Data, 2022

Training a Resilient Q-network against Observational Interference.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

Vision Transformers Are Robust Learners.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

Zeroth-Order Optimization for Composite Problems with Functional Constraints.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

Adversarial Examples Can Be Effective Data Augmentation for Unsupervised Machine Learning.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

SenSE: A Toolkit for Semantic Change Exploration via Word Embedding Alignment.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022


Data Leakage in Federated Learning.
Proceedings of the Federated Learning, 2022

2021
Improved Linear Convergence of Training CNNs With Generalizability Guarantees: A One-Hidden-Layer Case.
IEEE Trans. Neural Networks Learn. Syst., 2021

Editorial: Safe and Trustworthy Machine Learning.
Frontiers Big Data, 2021

Network Graph Based Neural Architecture Search.
CoRR, 2021

Certified Adversarial Defenses Meet Out-of-Distribution Corruptions: Benchmarking Robustness and Simple Baselines.
CoRR, 2021

Meta Adversarial Perturbations.
CoRR, 2021

Mean-based Best Arm Identification in Stochastic Bandits under Reward Contamination.
CoRR, 2021

CAFE: Catastrophic Data Leakage in Vertical Federated Learning.
CoRR, 2021

How and When Adversarial Robustness Transfers in Knowledge Distillation?
CoRR, 2021

Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Pruned Neural Networks.
CoRR, 2021

A Study of Low-Resource Speech Commands Recognition based on Adversarial Reprogramming.
CoRR, 2021

QTN-VQC: An End-to-End Learning framework for Quantum Neural Networks.
CoRR, 2021

Real-World Adversarial Examples involving Makeup Application.
CoRR, 2021

MAML is a Noisy Contrastive Learner.
CoRR, 2021

Simple Transparent Adversarial Examples.
CoRR, 2021

High-Robustness, Low-Transferability Fingerprinting of Neural Networks.
CoRR, 2021

Gi and Pal Scores: Deep Neural Network Generalization Statistics.
CoRR, 2021

Towards creativity characterization of generative models via group-based subset scanning.
CoRR, 2021

On the Adversarial Robustness of Visual Transformers.
CoRR, 2021

Hard-label Manifolds: Unexpected Advantages of Query Efficiency for Finding On-manifold Adversarial Examples.
CoRR, 2021

Formalizing Generalization and Robustness of Neural Networks to Weight Perturbations.
CoRR, 2021

Adversarial Examples for Unsupervised Machine Learning Models.
CoRR, 2021

Causal Inference Q-Network: Toward Resilient Reinforcement Learning.
CoRR, 2021

Meta Federated Learning.
CoRR, 2021

Fast Training of Provably Robust Neural Networks by SingleProp.
CoRR, 2021

Adversarial Sample Enhanced Domain Adaptation: A Case Study on Predictive Modeling with Electronic Health Records.
CoRR, 2021

Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Sparse Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Adversarial Attack Generation Empowered by Min-Max Optimization.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Formalizing Generalization and Adversarial Robustness of Neural Networks to Weight Perturbations.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Predicting Deep Neural Network Generalization with Perturbation Response Curves.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Best Arm Identification in Contaminated Stochastic Bandits.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Understanding the Limits of Unsupervised Domain Adaptation via Data Poisoning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Catastrophic Data Leakage in Vertical Federated Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

The SenSE Toolkit: A System for Visualization and Explanation of Semantic Shift.
Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, 2021

When does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning?
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Don't Forget to Sign the Gradients!
Proceedings of the Fourth Conference on Machine Learning and Systems, 2021

Leveraging Latent Features for Local Explanations.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Third Workshop on Adversarial Learning Methods for Machine Learning and Data Mining (AdvML 2021).
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Active Binary Classification of Random Fields.
Proceedings of the IEEE International Symposium on Information Theory, 2021

Self-Attentive Recommendation for Multi-Source Review Package.
Proceedings of the International Joint Conference on Neural Networks, 2021

Characteristic Examples: High-Robustness, Low-Transferability Fingerprinting of Neural Networks.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Voice2Series: Reprogramming Acoustic Models for Time Series Classification.
Proceedings of the 38th International Conference on Machine Learning, 2021

CRFL: Certifiably Robust Federated Learning against Backdoor Attacks.
Proceedings of the 38th International Conference on Machine Learning, 2021

Fold2Seq: A Joint Sequence(1D)-Fold(3D) Embedding-based Generative Model for Protein Design.
Proceedings of the 38th International Conference on Machine Learning, 2021

On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning.
Proceedings of the 9th International Conference on Learning Representations, 2021

Decentralizing Feature Extraction with Quantum Convolutional Neural Network for Automatic Speech Recognition.
Proceedings of the IEEE International Conference on Acoustics, 2021

Non-Singular Adversarial Robustness of Neural Networks.
Proceedings of the IEEE International Conference on Acoustics, 2021

Domain Adaptation for Learning Generator From Paired Few-Shot Data.
Proceedings of the IEEE International Conference on Acoustics, 2021

Active Estimation From Multimodal Data.
Proceedings of the IEEE International Conference on Acoustics, 2021

AID: Attesting the Integrity of Deep Neural Networks.
Proceedings of the 58th ACM/IEEE Design Automation Conference, 2021

How Robust Are Randomized Smoothing Based Defenses to Data Poisoning?
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021


Hidden Cost of Randomized Smoothing.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Rate-improved inexact augmented Lagrangian method for constrained nonconvex optimization.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Fake it Till You Make it: Self-Supervised Semantic Shifts for Monolingual Word Embedding Tasks.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Self-Progressing Robust Training.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Fast Training of Provably Robust Neural Networks by SingleProp.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
A Primer on Zeroth-Order Optimization in Signal Processing and Machine Learning: Principals, Recent Advances, and Applications.
IEEE Signal Process. Mag., 2020

Fluid intelligence is associated with cortical volume and white matter tract integrity within multiple-demand system across adult lifespan.
NeuroImage, 2020

AI Explainability 360: An Extensible Toolkit for Understanding Data and Machine Learning Models.
J. Mach. Learn. Res., 2020

Zeroth-Order Hybrid Gradient Descent: Towards A Principled Black-Box Optimization Framework.
CoRR, 2020

Reprogramming Language Models for Molecular Representation Learning.
CoRR, 2020

A Dynamical Systems Approach for Convergence of the Bayesian EM Algorithm.
CoRR, 2020

A Primer on Zeroth-Order Optimization in Signal Processing and Machine Learning.
CoRR, 2020

Accelerating Antimicrobial Discovery with Controllable Deep Generative Models and Molecular Dynamics.
CoRR, 2020

Rethinking Randomized Smoothing for Adversarial Robustness.
CoRR, 2020

Defending against Backdoor Attack on Deep Neural Networks.
CoRR, 2020

Block Switching: A Stochastic Approach for Deep Learning Security.
CoRR, 2020

Reinforcement-Learning based Portfolio Management with Augmented Asset Movement Prediction States.
CoRR, 2020

Variational Quantum Circuits for Deep Reinforcement Learning.
IEEE Access, 2020

SChME at SemEval-2020 Task 1: A Model Ensemble for Detecting Lexical Semantic Change.
Proceedings of the Fourteenth Workshop on Semantic Evaluation, 2020

Optimizing Mode Connectivity via Neuron Alignment.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Higher-Order Certification For Randomized Smoothing.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

ScaleCom: Scalable Sparsified Gradient Compression for Communication-Efficient Distributed Training.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Toward a neuro-inspired creative decoder.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case.
Proceedings of the 37th International Conference on Machine Learning, 2020

Transfer Learning without Knowing: Reprogramming Black-box Machine Learning Models with Scarce Data and Limited Resources.
Proceedings of the 37th International Conference on Machine Learning, 2020

Is There a Trade-Off Between Fairness and Accuracy? A Perspective Using Mismatched Hypothesis Testing.
Proceedings of the 37th International Conference on Machine Learning, 2020

Proper Network Interpretability Helps Adversarial Robustness in Classification.
Proceedings of the 37th International Conference on Machine Learning, 2020

Bridging Mode Connectivity in Loss Landscapes and Adversarial Robustness.
Proceedings of the 8th International Conference on Learning Representations, 2020

DBA: Distributed Backdoor Attacks against Federated Learning.
Proceedings of the 8th International Conference on Learning Representations, 2020

Sign-OPT: A Query-Efficient Hard-label Adversarial Attack.
Proceedings of the 8th International Conference on Learning Representations, 2020

Enhanced Adversarial Strategically-Timed Attacks Against Deep Reinforcement Learning.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Characterizing Speech Adversarial Examples Using Self-Attention U-Net Enhancement.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Towards an Efficient and General Framework of Robust Training for Graph Neural Networks.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

AdvMS: A Multi-Source Multi-Cost Defense Against Adversarial Attacks.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020


Adversarial T-Shirt! Evading Person Detectors in a Physical World.
Proceedings of the Computer Vision - ECCV 2020, 2020

Practical Detection of Trojan Neural Networks: Data-Limited and Data-Free Cases.
Proceedings of the Computer Vision - ECCV 2020, 2020

Towards Verifying Robustness of Neural Networks Against A Family of Semantic Perturbations.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Guaranteed Convergence of Training Convolutional Neural Networks via Accelerated Gradient Descent.
Proceedings of the 54th Annual Conference on Information Sciences and Systems, 2020

Towards Query-Efficient Black-Box Adversary with Zeroth-Order Natural Gradient Descent.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Reinforcement-Learning Based Portfolio Management with Augmented Asset Movement Prediction States.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Towards Certificated Model Robustness Against Weight Perturbations.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Seq2Sick: Evaluating the Robustness of Sequence-to-Sequence Models with Adversarial Examples.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

TemPEST: Soft Template-Based Personalized EDM Subject Generation through Collaborative Summarization.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Identifying Influential Links for Event Propagation on Twitter: A Network of Networks Approach.
IEEE Trans. Signal Inf. Process. over Networks, 2019

Guest Editorial Special Issue on AI Enabled Cognitive Communication and Networking for IoT.
IEEE Internet Things J., 2019

A scalable attribute-aware network embedding system.
Neurocomputing, 2019

Neural-Brane: Neural Bayesian Personalized Ranking for Attributed Network Embedding.
Data Sci. Eng., 2019

Towards Verifying Robustness of Neural Networks Against Semantic Perturbations.
CoRR, 2019

Evading Real-Time Person Detectors by Adversarial T-shirt.
CoRR, 2019

An Information-Theoretic Perspective on the Relationship Between Fairness and Accuracy.
CoRR, 2019

One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques.
CoRR, 2019

Beyond Adversarial Training: Min-Max Optimization in Adversarial Attack and Defense.
CoRR, 2019

Model Agnostic Contrastive Explanations for Structured Data.
CoRR, 2019

Generating Contrastive Explanations with Monotonic Attribute Functions.
CoRR, 2019

Enterprise Cyber Resiliency Against Lateral Movement: A Graph Theoretic Approach.
CoRR, 2019

When Causal Intervention Meets Image Masking and Adversarial Perturbation for Deep Neural Networks.
CoRR, 2019

Toward A Neuro-inspired Creative Decoder.
CoRR, 2019

Improving Prediction Efficacy Through Abnormality Detection and Data Preprocessing.
IEEE Access, 2019

hpGAT: High-Order Proximity Informed Graph Attention Network.
IEEE Access, 2019

Corrections to "Learning Graph Topological Features via GAN".
IEEE Access, 2019

Learning Graph Topological Features via GAN.
IEEE Access, 2019

Reinforcement learning based interconnection routing for adaptive traffic optimization.
Proceedings of the 13th IEEE/ACM International Symposium on Networks-on-Chip, 2019

Discrete Adversarial Attacks and Submodular Optimization with Applications to Text Classification.
Proceedings of the Second Conference on Machine Learning and Systems, SysML 2019, 2019

Recent Progress in Zeroth Order Optimization and Its Applications to Adversarial Robustness in Data Mining and Machine Learning.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Protecting Neural Networks with Hierarchical Random Switching: Towards Better Robustness-Accuracy Trade-off for Stochastic Defenses.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

An Exploration on the Effect of Augmented Reality Learning System on Situational Interest in Historical Building Guide.
Proceedings of the 8th International Congress on Advanced Applied Informatics, 2019

PROVEN: Verifying Robustness of Neural Networks with a Probabilistic Approach.
Proceedings of the 36th International Conference on Machine Learning, 2019

Fast Incremental von Neumann Graph Entropy Computation: Theory, Algorithm, and Applications.
Proceedings of the 36th International Conference on Machine Learning, 2019

Characterizing Audio Adversarial Examples Using Temporal Dependency.
Proceedings of the 7th International Conference on Learning Representations, 2019

Structured Adversarial Attack: Towards General Implementation and Better Interpretability.
Proceedings of the 7th International Conference on Learning Representations, 2019

signSGD via Zeroth-Order Oracle.
Proceedings of the 7th International Conference on Learning Representations, 2019

Query-Efficient Hard-label Black-box Attack: An Optimization-based Approach.
Proceedings of the 7th International Conference on Learning Representations, 2019

When Causal Intervention Meets Adversarial Examples and Image Masking for Deep Neural Networks.
Proceedings of the 2019 IEEE International Conference on Image Processing, 2019

On the Design of Black-Box Adversarial Examples by Leveraging Gradient-Free Optimization and Operator Splitting Method.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Characterizing Adversarial Subspaces by Mutual Information.
Proceedings of the 2019 ACM Asia Conference on Computer and Communications Security, 2019

Neural-brane: an inductive approach for attributed network embedding.
Proceedings of the ASONAM '19: International Conference on Advances in Social Networks Analysis and Mining, 2019

AutoZOOM: Autoencoder-Based Zeroth Order Optimization Method for Attacking Black-Box Neural Networks.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Accelerated Distributed Dual Averaging Over Evolving Networks of Growing Connectivity.
IEEE Trans. Signal Process., 2018

Phase Transitions and a Model Order Selection Criterion for Spectral Graph Clustering.
IEEE Trans. Signal Process., 2018

Incremental eigenpair computation for graph Laplacian matrices: theory and applications.
Soc. Netw. Anal. Min., 2018

Analysis of Data Dissemination and Control in Social Internet of Vehicles.
IEEE Internet Things J., 2018

Analysis of Information Delivery Dynamics in Cognitive Sensor Networks Using Epidemic Models.
IEEE Internet Things J., 2018

PROVEN: Certifying Robustness of Neural Networks with a Probabilistic Approach.
CoRR, 2018

Discrete Attacks and Submodular Optimization with Applications to Text Classification.
CoRR, 2018

Controllability, Multiplexing, and Transfer Learning in Networks using Evolutionary Learning.
CoRR, 2018

Is Ordered Weighted ℓ<sub>1</sub> Regularized Regression Robust to Adversarial Perturbation? A Case Study on OSCAR.
CoRR, 2018

Structured Adversarial Attack: Towards General Implementation and Better Interpretability.
CoRR, 2018

On the Limitation of MagNet Defense against L<sub>1</sub>-based Adversarial Examples.
CoRR, 2018

Bypassing Feature Squeezing by Increasing Adversary Strength.
CoRR, 2018

Efficient Neural Network Robustness Certification with General Activation Functions.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Zeroth-Order Stochastic Variance Reduction for Nonconvex Optimization.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Scalable Spectral Clustering Using Random Binning Features.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach.
Proceedings of the 6th International Conference on Learning Representations, 2018

Attacking the Madry Defense Model with $L_1$-based Adversarial Examples.
Proceedings of the 6th International Conference on Learning Representations, 2018

On the Limitation of Local Intrinsic Dimensionality for Characterizing the Subspaces of Adversarial Examples.
Proceedings of the 6th International Conference on Learning Representations, 2018

On the Supermodularity of Active Graph-Based Semi-Supervised Learning with Stieltjes Matrix Regularization.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

Zeroth-Order Diffusion Adaptation Over Networks.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

First-Order Bifurcation Detection for Dynamic Complex Networks.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

On Extensions of Clever: A Neural Network Robustness Evaluation Algorithm.
Proceedings of the 2018 IEEE Global Conference on Signal and Information Processing, 2018

On the Utility of Conditional Generation Based Mutual Information for Characterizing Adversarial Subspaces.
Proceedings of the 2018 IEEE Global Conference on Signal and Information Processing, 2018

Is Ordered Weighted ℓ1 Regularized Regression Robust to Adversarial Perturbation? A Case Study on OSCAR.
Proceedings of the 2018 IEEE Global Conference on Signal and Information Processing, 2018

Zeroth-Order Stochastic Projected Gradient Descent for Nonconvex Optimization.
Proceedings of the 2018 IEEE Global Conference on Signal and Information Processing, 2018

Word Mover's Embedding: From Word2Vec to Document Embedding.
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

Is Robustness the Cost of Accuracy? - A Comprehensive Study on the Robustness of 18 Deep Image Classification Models.
Proceedings of the Computer Vision - ECCV 2018, 2018

On the Limitation of MagNet Defense Against L1-Based Adversarial Examples.
Proceedings of the 48th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops, 2018

Zeroth-Order Online Alternating Direction Method of Multipliers: Convergence Analysis and Applications.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Attacking Visual Language Grounding with Adversarial Examples: A Case Study on Neural Image Captioning.
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Multilayer Spectral Graph Clustering via Convex Layer Aggregation: Theory and Algorithms.
IEEE Trans. Signal Inf. Process. over Networks, 2017

Bias-Variance Tradeoff of Graph Laplacian Regularizer.
IEEE Signal Process. Lett., 2017

Show-and-Fool: Crafting Adversarial Examples for Neural Image Captioning.
CoRR, 2017

Attacking the Madry Defense Model with L<sub>1</sub>-based Adversarial Examples.
CoRR, 2017

Can GAN Learn Topological Features of a Graph?
CoRR, 2017

Traffic-Aware Patching for Cyber Security in Mobile IoT.
IEEE Commun. Mag., 2017

Principled Multilayer Network Embedding.
Proceedings of the 2017 IEEE International Conference on Data Mining Workshops, 2017

Revisiting Spectral Graph Clustering with Generative Community Models.
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

Distributed optimization for evolving networks of growing connectivity.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

AMOS: An automated model order selection algorithm for spectral graph clustering.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

ZOO: Zeroth Order Optimization Based Black-box Attacks to Deep Neural Networks without Training Substitute Models.
Proceedings of the 10th ACM Workshop on Artificial Intelligence and Security, 2017

FEAST: An Automated Feature Selection Framework for Compilation Tasks.
Proceedings of the 31st IEEE International Conference on Advanced Information Networking and Applications, 2017

2016
Buffer Occupancy and Delivery Reliability Tradeoffs for Epidemic Routing.
CoRR, 2016

Decapitation via digital epidemics: a bio-inspired transmissive attack.
IEEE Commun. Mag., 2016

Ecology-Based DoS Attack in Cognitive Radio Networks.
Proceedings of the 2016 IEEE Security and Privacy Workshops, 2016

Multi-centrality graph spectral decompositions and their application to cyber intrusion detection.
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

Multilayer spectral graph clustering via convex layer aggregation.
Proceedings of the 2016 IEEE Global Conference on Signal and Information Processing, 2016

2015
Deep Community Detection.
IEEE Trans. Signal Process., 2015

Phase Transitions in Spectral Community Detection.
IEEE Trans. Signal Process., 2015

Incremental Method for Spectral Clustering of Increasing Orders.
CoRR, 2015

Sequential Defense Against Random and Intentional Attacks in Complex Networks.
CoRR, 2015

When crowdsourcing meets mobile sensing: a social network perspective.
IEEE Commun. Mag., 2015

Action Recommendation for Cyber Resilience.
Proceedings of the 2015 Workshop on Automated Decision Making for Active Cyber Defense, 2015

Multivariate and Categorical Analysis of Gaming Statistics.
Proceedings of the 18th International Conference on Network-Based Information Systems, 2015

Phase transitions in spectral community detection of large noisy networks.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

Supervised Collective Classification for Crowdsourcing.
Proceedings of the 2015 IEEE Globecom Workshops, San Diego, CA, USA, December 6-10, 2015, 2015

DEMO: Action Recommendation for Cyber Resilience.
Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security, 2015

2014
Optimal Control of Epidemic Information Dissemination Over Networks.
IEEE Trans. Cybern., 2014

Information Fusion to Defend Intentional Attack in Internet of Things.
IEEE Internet Things J., 2014

Universal Phase Transition in Community Detectability under a Stochastic Block Model.
CoRR, 2014

Assessing and safeguarding network resilience to nodal attacks.
IEEE Commun. Mag., 2014

Modeling Dynamics of Malware with Incubation Period from the View of Individual.
Proceedings of the IEEE 79th Vehicular Technology Conference, 2014

Local Fiedler vector centrality for detection of deep and overlapping communities in networks.
Proceedings of the IEEE International Conference on Acoustics, 2014

2013
Node removal vulnerability of the largest component of a network.
Proceedings of the IEEE Global Conference on Signal and Information Processing, 2013

2012
Rate-Reliability-Delay Tradeoff of Multipath Transmission Using Network Coding.
IEEE Trans. Veh. Technol., 2012

Rate-Delay Enhanced Multipath Transmission Scheme via Network Coding in Multihop Networks.
IEEE Commun. Lett., 2012

Smart attacks in smart grid communication networks.
IEEE Commun. Mag., 2012

2011
Ecology of Cognitive Radio Ad Hoc Networks.
IEEE Commun. Lett., 2011

On Modeling Malware Propagation in Generalized Social Networks.
IEEE Commun. Lett., 2011

Topology control in multi-channel cognitive radio networks with non-uniform node arrangements.
Proceedings of the 16th IEEE Symposium on Computers and Communications, 2011

Network synchronization among femtocells.
Proceedings of the Workshops Proceedings of the Global Communications Conference, 2011

Optimal Control of Epidemic Information Dissemination in Mobile Ad Hoc Networks.
Proceedings of the Global Communications Conference, 2011

Intentional Attack and Fusion-Based Defense Strategy in Complex Networks.
Proceedings of the Global Communications Conference, 2011

Reciprocal spectrum sharing game and mechanism in cellular systems with Cognitive Radio users.
Proceedings of the Workshops Proceedings of the Global Communications Conference, 2011

2010
Information Epidemics in Complex Networks with Opportunistic Links and Dynamic Topology.
Proceedings of the Global Communications Conference, 2010


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