| Towards Evaluating the Robustness of Neural Networks Learned by Transduction | 0 | 0.34 | 2022 |
| Person Re-Identification Combined with Style Transfer and Pose Generation | 0 | 0.34 | 2022 |
| Detecting Errors and Estimating Accuracy on Unlabeled Data with Self-training Ensembles. | 0 | 0.34 | 2021 |
| ATOM: Robustifying Out-of-Distribution Detection Using Outlier Mining | 1 | 0.41 | 2021 |
| Tackling Android Fragmentation - Mobile Apps' Dilemma and the Platform's Strategies. | 0 | 0.34 | 2020 |
| Concise Explanations of Neural Networks using Adversarial Training | 0 | 0.34 | 2020 |
| Enhancing ML Robustness Using Physical-World Constraints. | 0 | 0.34 | 2019 |
| Robust Attribution Regularization. | 0 | 0.34 | 2019 |
| UTP Semantics of a Calculus for Mobile Ad Hoc Networks. | 0 | 0.34 | 2019 |
| Function-Structure Collaborative Mapping Induced by Universal Triple I Systems. | 0 | 0.34 | 2019 |
| Generative Adversarial Networks with Enhanced Symmetric Residual Units for Single Image Super-Resolution. | 0 | 0.34 | 2019 |
| Towards Understanding Limitations of Pixel Discretization Against Adversarial Attacks | 1 | 0.36 | 2019 |
| That's Mine! Employee Side Projects, Intellectual Property Ownership, and Innovation. | 0 | 0.34 | 2019 |
| Improving Adversarial Robustness by Data-Specific Discretization. | 2 | 0.35 | 2018 |
| Reinforcing Adversarial Robustness using Model Confidence Induced by Adversarial Training. | 0 | 0.34 | 2018 |
| Adversarial Learning and Explainability in Structured Datasets. | 1 | 0.35 | 2018 |
| When Lempel-Ziv-Welch Meets Machine Learning: A Case Study of Accelerating Machine Learning using Coding. | 0 | 0.34 | 2017 |
| Bolt-on Differential Privacy for Scalable Stochastic Gradient Descent-based Analytics. | 16 | 0.70 | 2017 |
| Objective Metrics and Gradient Descent Algorithms for Adversarial Examples in Machine Learning. | 6 | 0.42 | 2017 |
| Manifold Assumption and Defenses Against Adversarial Perturbations. | 0 | 0.34 | 2017 |
| A Methodology for Formalizing Model-Inversion Attacks | 8 | 0.49 | 2016 |
| Differentially Private Stochastic Gradient Descent for in-RDBMS Analytics. | 5 | 0.58 | 2016 |
| Distillation as a Defense to Adversarial Perturbations Against Deep Neural Networks | 309 | 13.23 | 2015 |
| Revisiting Differentially Private Regression: Lessons From Learning Theory and their Consequences. | 0 | 0.34 | 2015 |
| Uncertainty aware query execution time prediction | 5 | 0.41 | 2014 |
| Uncertainty Aware Query Execution Time Prediction. | 0 | 0.34 | 2014 |
| A Completeness Theory for Polynomial (Turing) Kernelization | 10 | 0.56 | 2013 |
| Weak compositions and their applications to polynomial lower bounds for kernelization | 0 | 0.34 | 2012 |
| COREMU: a scalable and portable parallel full-system emulator | 29 | 0.96 | 2011 |
| Hierarchies of Inefficient Kernelizability | 4 | 0.41 | 2011 |
| Extended islands of tractability for parsimony haplotyping | 3 | 0.42 | 2010 |
| Experimental Study of FPT Algorithms for the Directed Feedback Vertex Set Problem | 1 | 0.36 | 2009 |
| Control flow obfuscation with information flow tracking | 16 | 0.77 | 2009 |
| GloSDC: A Framework for a Global Spatial Data Catalog | 2 | 0.36 | 2008 |
