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Jared Sylvester
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2020 – today
- 2020
- [j4]Jared Sylvester, Edward Raff:
Trimming the Thorns of AI Fairness Research. IEEE Data Eng. Bull. 43(4): 74-84 (2020) - no results
2010 – 2019
- 2019
- [c12]Edward Raff
, Jared Sylvester, Steven Forsyth, Mark McLean:
Barrage of Random Transforms for Adversarially Robust Defense. CVPR 2019: 6528-6537 - 2018
- [j3]Edward Raff
, Richard Zak
, Russell Cox, Jared Sylvester, Paul Yacci, Rebecca Ward, Anna Tracy, Mark McLean, Charles Nicholas:
An investigation of byte n-gram features for malware classification. J. Comput. Virol. Hacking Tech. 14(1): 1-20 (2018) - [c11]Edward Raff, Jon Barker, Jared Sylvester, Robert Brandon, Bryan Catanzaro, Charles K. Nicholas:
Malware Detection by Eating a Whole EXE. AAAI Workshops 2018: 268-276 - [c10]Edward Raff, Jared Sylvester, Steven Mills:
Fair Forests: Regularized Tree Induction to Minimize Model Bias. AIES 2018: 243-250 - [c9]Edward Raff
, Booz Allen Hamilton, Jared Sylvester:
Linear Models with Many Cores and CPUs: A Stochastic Atomic Update Scheme. IEEE BigData 2018: 65-73 - [c8]Edward Raff
, Jared Sylvester, Charles Nicholas:
Engineering a Simplified 0-Bit Consistent Weighted Sampling. CIKM 2018: 1203-1212 - [c7]Edward Raff
, Jared Sylvester:
Gradient Reversal against Discrimination: A Fair Neural Network Learning Approach. DSAA 2018: 189-198 - [i8]Edward Raff, Jared Sylvester, Charles Nicholas:
Engineering a Simplified 0-Bit Consistent Weighted Sampling. CoRR abs/1804.00069 (2018) - [i7]Jared Sylvester, Edward Raff:
What About Applied Fairness? CoRR abs/1806.05250 (2018) - [i6]William Fleshman, Edward Raff, Jared Sylvester, Steven Forsyth, Mark McLean:
Non-Negative Networks Against Adversarial Attacks. CoRR abs/1806.06108 (2018) - [i5]Edward Raff, Jared Sylvester:
Gradient Reversal Against Discrimination. CoRR abs/1807.00392 (2018) - 2017
- [c6]Edward Raff
, Jared Sylvester, Charles Nicholas:
Learning the PE Header, Malware Detection with Minimal Domain Knowledge. AISec@CCS 2017: 121-132 - [i4]Edward Raff, Jared Sylvester, Charles K. Nicholas:
Learning the PE Header, Malware Detection with Minimal Domain Knowledge. CoRR abs/1709.01471 (2017) - [i3]Edward Raff, Jon Barker, Jared Sylvester, Robert Brandon, Bryan Catanzaro, Charles K. Nicholas:
Malware Detection by Eating a Whole EXE. CoRR abs/1710.09435 (2017) - [i2]Edward Raff, Jared Sylvester, Steven Mills:
Fair Forests: Regularized Tree Induction to Minimize Model Bias. CoRR abs/1712.08197 (2017) - 2016
- [j2]Jared Sylvester, James A. Reggia:
Engineering neural systems for high-level problem solving. Neural Networks 79: 37-52 (2016) - 2013
- [c5]David Darmon, Jared Sylvester, Michelle Girvan, William Rand
:
Predictability of User Behavior in Social Media: Bottom-Up v. Top-Down Modeling. SocialCom 2013: 102-107 - [i1]David Darmon, Jared Sylvester, Michelle Girvan, William Rand:
Predictability of User Behavior in Social Media: Bottom-Up v. Top-Down Modeling. CoRR abs/1306.6111 (2013) - 2011
- [c4]Jared Sylvester, James A. Reggia, Scott A. Weems:
Cognitive control as a gated cortical net. BICA 2011: 371-376 - no results
2000 – 2009
- 2009
- [j1]Jared Sylvester, James A. Reggia:
Plasticity-Induced Symmetry Relationships Between Adjacent Self-Organizing Topographic Maps. Neural Comput. 21(12): 3429-3443 (2009) - [c3]James A. Reggia, Jared Sylvester, Scott A. Weems, Michael F. Bunting:
A Simple Oscillatory Short-Term Memory. AAAI Fall Symposium: Biologically Inspired Cognitive Architectures 2009 - 2007
- [c2]Nitesh V. Chawla
, Jared Sylvester:
Exploiting Diversity in Ensembles: Improving the Performance on Unbalanced Datasets. MCS 2007: 397-406 - 2006
- [c1]Jared Sylvester, Nitesh V. Chawla
:
Evolutionary Ensemble Creation and Thinning. IJCNN 2006: 5148-5155 - no results
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