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15000 Exploring team science, professional networks, and innovation success in the THRIVE COVID-19 fellowship program
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- Journal of Clinical and Translational Science / Volume 5 / Issue s1 / March 2021
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- 30 March 2021, pp. 109-110
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Pediatric research priorities in healthcare-associated infections and antimicrobial stewardship
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- Infection Control & Hospital Epidemiology / Volume 42 / Issue 5 / May 2021
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- 26 November 2020, pp. 519-522
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- May 2021
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Lift and drag forces acting on a particle moving with zero slip in a linear shear flow near a wall
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- Journal of Fluid Mechanics / Volume 904 / 10 December 2020
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- 08 October 2020, A6
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Analysis of unsteady flow effects on the Betz limit for flapping foil power generation
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- Journal of Fluid Mechanics / Volume 902 / 10 November 2020
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- 14 September 2020, A30
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9 - Adversarial Machine Learning Challenges
- from Part IV - Future Directions in Adversarial Machine Learning
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- Adversarial Machine Learning
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- 14 March 2019
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- 21 February 2019, pp 241-252
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5 - Availability Attack Case Study: SpamBayes
- from Part II - Causative Attacks on Machine Learning
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- Adversarial Machine Learning
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- 14 March 2019
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- 21 February 2019, pp 105-133
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6 - Integrity Attack Case Study: PCA Detector
- from Part II - Causative Attacks on Machine Learning
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- Adversarial Machine Learning
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- 14 March 2019
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- 21 February 2019, pp 134-164
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Part IV - Future Directions in Adversarial Machine Learning
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- Adversarial Machine Learning
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- 14 March 2019
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- 21 February 2019, pp 239-240
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4 - Attacking a Hypersphere Learner
- from Part II - Causative Attacks on Machine Learning
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- Adversarial Machine Learning
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- 14 March 2019
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- 21 February 2019, pp 69-104
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Part I - Overview of Adversarial Machine Learning
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- Adversarial Machine Learning
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- 14 March 2019
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- 21 February 2019, pp 1-2
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Adversarial Machine Learning
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- 14 March 2019
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- 21 February 2019
Acknowledgments
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- Adversarial Machine Learning
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- 14 March 2019
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- 21 February 2019, pp xiii-xiv
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3 - A Framework for Secure Learning
- from Part I - Overview of Adversarial Machine Learning
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- Adversarial Machine Learning
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- 14 March 2019
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- 21 February 2019, pp 29-66
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Appendix D: Full Proofs for Near-Optimal Evasion
- from Part V - Appendixes
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- Adversarial Machine Learning
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- 14 March 2019
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- 21 February 2019, pp 285-294
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Index
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- Adversarial Machine Learning
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- 14 March 2019
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- 21 February 2019, pp 322-325
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List of Symbols
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- Adversarial Machine Learning
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- 14 March 2019
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- 21 February 2019, pp xi-xii
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Part II - Causative Attacks on Machine Learning
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- Adversarial Machine Learning
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- 14 March 2019
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- 21 February 2019, pp 67-68
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2 - Background and Notation
- from Part I - Overview of Adversarial Machine Learning
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- Adversarial Machine Learning
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- 14 March 2019
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- 21 February 2019, pp 20-28
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Part III - Exploratory Attacks on Machine Learning
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- Adversarial Machine Learning
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- 14 March 2019
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- 21 February 2019, pp 165-166
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1 - Introduction
- from Part I - Overview of Adversarial Machine Learning
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- Adversarial Machine Learning
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- 14 March 2019
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- 21 February 2019, pp 3-19
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