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Methodology
← Learning Types
Machine Learning
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Learning Types
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Adversarial Learning
4854 directly classified papers
Papers per year
2006: 3
2007: 1
2009: 4
2010: 6
2011: 3
2012: 5
2013: 10
2014: 6
2015: 8
2016: 18
2017: 87
2018: 261
2019: 551
2020: 588
2021: 703
2022: 633
2023: 672
2024: 579
2025: 561
2026: 155
Papers
Physically Realizable Adversarial Examples for LiDAR Object Detection
CVPR 2020
Robustness to Programmable String Transformations via Augmented Abstract Training
ICML 2020
Transfer Learning without Knowing: Reprogramming Black-box Machine Learning Models with Scarce Data and Limited Resources
ICML 2020
Fundamental Tradeoffs between Invariance and Sensitivity to Adversarial Perturbations
ICML 2020
Understanding and Mitigating the Tradeoff between Robustness and Accuracy
ICML 2020
Fairness without Demographics through Adversarially Reweighted Learning
NIPS 2020
Cross-lingual Spoken Language Understanding with Regularized Representation Alignment
EMNLP 2020
Increasing the Intelligibility and Naturalness of Alaryngeal Speech Using Voice Conversion and Synthetic Fundamental Frequency
INTERSPEECH 2020
Scalable Differential Privacy with Certified Robustness in Adversarial Learning
ICML 2020
Adversarial Robustness Against the Union of Multiple Perturbation Models
ICML 2020
Implicit Euler Skip Connections: Enhancing Adversarial Robustness via Numerical Stability
ICML 2020
DeepMatch: Balancing Deep Covariate Representations for Causal Inference Using Adversarial Training
ICML 2020
Towards Understanding the Dynamics of the First-Order Adversaries
ICML 2020
Minimally distorted Adversarial Examples with a Fast Adaptive Boundary Attack
ICML 2020
Concise Explanations of Neural Networks using Adversarial Training
ICML 2020
Enhance Robustness of Sequence Labelling with Masked Adversarial Training
EMNLP 2020
x-Vectors Meet Adversarial Attacks: Benchmarking Adversarial Robustness in Speaker Verification
INTERSPEECH 2020
A principled approach for generating adversarial images under non-smooth dissimilarity metrics
AISTATS 2020
The Attacker’s Perspective on Automatic Speaker Verification: An Overview
INTERSPEECH 2020
Non-Parallel Emotion Conversion Using a Deep-Generative Hybrid Network and an Adversarial Pair Discriminator
INTERSPEECH 2020
Learning Improvised Chatbots from Adversarial Modifications of Natural Language Feedback
EMNLP 2020
Understanding and Improving Fast Adversarial Training
NIPS 2020
Adversarial Mutual Information Learning for Network Embedding
IJCAI 2020
Searching for a Search Method: Benchmarking Search Algorithms for Generating NLP Adversarial Examples
EMNLP 2020
Precise Tradeoffs in Adversarial Training for Linear Regression
COLT 2020
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