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Katie McConky
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2020 – today
- 2024
- [c9]Calvin Nau, Prashant Sankaran, Moises Sudit, Payam Khazaelpour, Katie McConky, Alvaro Velasquez, Liise Kayler:
An Exploration of Optimizing Kidney Exchanges with Graph Machine Learning. CogSIMA 2024: 114-119 - 2023
- [j2]Prashant Sankaran
, Katie McConky
, Moises Sudit
, Héctor J. Ortiz-Peña:
GAMMA: Graph Attention Model for Multiple Agents to Solve Team Orienteering Problem With Multiple Depots. IEEE Trans. Neural Networks Learn. Syst. 34(11): 9412-9423 (2023) - 2021
- [c8]Gordon Werner, Shanchieh Jay Yang, Katie McConky:
Near real-time intrusion alert aggregation using concept-based learning. CF 2021: 152-160
2010 – 2019
- 2019
- [c7]Ahmet Okutan, Shanchieh Jay Yang, Katie McConky, Gordon Werner:
CAPTURE: Cyberattack Forecasting Using Non-Stationary Features with Time Lags. CNS 2019: 205-213 - 2018
- [j1]Ahmet Okutan
, Gordon Werner, Shanchieh Jay Yang, Katie McConky:
Forecasting cyberattacks with incomplete, imbalanced, and insignificant data. Cybersecur. 1(1): 15 (2018) - [c6]Gordon Werner, Shanchieh Yang, Katie McConky:
Leveraging Intra-Day Temporal Variations to Predict Daily Cyberattack Activity. ISI 2018: 58-63 - [i1]Ahmet Okutan, Shanchieh Jay Yang, Katie McConky:
Forecasting Cyber Attacks with Imbalanced Data Sets and Different Time Granularities. CoRR abs/1803.09560 (2018) - 2017
- [c5]Ahmet Okutan, Gordon Werner, Katie McConky, Shanchieh Jay Yang:
POSTER: Cyber Attack Prediction of Threats from Unconventional Resources (CAPTURE). CCS 2017: 2563-2565 - [c4]Ahmet Okutan, Shanchieh Jay Yang, Katie McConky:
Predicting cyber attacks with bayesian networks using unconventional signals. CISRC 2017: 13:1-13:4 - [c3]Gordon Werner, Shanchieh Jay Yang, Katie McConky:
Time series forecasting of cyber attack intensity. CISRC 2017: 18:1-18:3 - 2012
- [c2]Katie McConky, Rakesh Nagi
, Moises Sudit, William Hughes:
Improving event co-reference by context extraction and dynamic feature weighting. CogSIMA 2012: 38-43 - 2011
- [c1]Katie McConky, Rakesh Nagi, Moises Sudit, William J. Rose, Gary J. Katz:
Significant information encapsulation and valence exploitation (SIEVE) for discovery. FUSION 2011: 1-8
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