Adversarial Attacks on Deep-learning Models in Natural Language Processing

Adversarial Examples: Attacks and Defenses for Deep Learning

(2019) Xiaoyong Yuan et al.   IEEE Transactions on Neural Networks and Learning Systems

An attentive neural architecture for joint segmentation and parsing and its application to real estate ads

(2018) Giannis Bekoulis et al.   EXPERT SYSTEMS WITH APPLICATIONS

Recent Trends in Deep Learning Based Natural Language Processing [Review Article]

(2018) Tom Young et al.   IEEE Computational Intelligence Magazine

Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning

(2018) Battista Biggio et al.   PATTERN RECOGNITION

Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey

(2018) Naveed Akhtar et al.   IEEE Access

A Survey on Security Threats and Defensive Techniques of Machine Learning: A Data Driven View

(2018) Qiang Liu et al.   IEEE Access

Ian Goodfellow, Yoshua Bengio, and Aaron Courville: Deep learning

(2017) Jeff Heaton   Genetic Programming and Evolvable Machines

An End-to-End Trainable Neural Network for Image-Based Sequence Recognition and Its Application to Scene Text Recognition

(2017) Baoguang Shi et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations

(2017) Ranjay Krishna et al.   INTERNATIONAL JOURNAL OF COMPUTER VISION

Deep Sentence Embedding Using Long Short-Term Memory Networks: Analysis and Application to Information Retrieval

(2016) Hamid Palangi et al.   IEEE-ACM Transactions on Audio Speech and Language Processing

Development of a benchmark corpus to support the automatic extraction of drug-related adverse effects from medical case reports

(2012) Harsha Gurulingappa et al.   JOURNAL OF BIOMEDICAL INFORMATICS

The security of machine learning

(2010) Marco Barreno et al.   MACHINE LEARNING