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2020 – today
- 2023
[j1]Yiwen Zhu
, Rathijit Sen, Robert Horton, John Mark Agosta:
Runtime Variation in Big Data Analytics. Proc. ACM Manag. Data 1(1): 67:1-67:20 (2023)- [i8]Yiwen Zhu, Rathijit Sen, Robert Horton, John Mark Agosta:
Runtime Variation in Big Data Analytics. CoRR abs/2304.03424 (2023) - [i7]John Mark Agosta, Mario Inchiosa:
Hierarchical Bayesian Regression for Multi-Location Sales Transaction Forecasting. CoRR abs/2306.17795 (2023) - [i6]John Mark Agosta, Robert Horton:
Redeeming Data Science by Decision Modelling. CoRR abs/2307.00088 (2023)
2010 – 2019
- 2016
- [c15]John Mark Agosta, Debraj GuhaThakurta, Robert Horton, Mario Inchiosa, Srini Kumar, Mengyue Zhao:
Scalable Data Analytics Using R: Single Machines to Hadoop Spark Clusters. KDD 2016: 2115 - [e2]John Mark Agosta, Rommel Novaes Carvalho:
Proceedings of the Twelfth UAI Bayesian Modeling Applications Workshop (BMAW 2015) co-located with the 31st Conference on Uncertainty in Artificial Intelligence (UAI 2015), Amsterdam, The Netherlands, July 16, 2015. CEUR Workshop Proceedings 1565, CEUR-WS.org 2016 [contents] - 2013
- [c14]John Mark Agosta, Jaideep Chandrashekar, Mark Crovella, Nina Taft, Daniel Ting:
Mixture models of endhost network traffic. INFOCOM 2013: 225-229 - [c13]Omar Zia Khan, Pascal Poupart, John Mark Agosta:
Iterative Model Refinement of Recommender MDPs Based on Expert Feedback. ECML/PKDD (1) 2013: 162-177 - [c12]John Mark Agosta, Preeti J. Pillai:
A Lightweight Inference Method for Image Classification. UAI Application Workshops 2013: 50-57 - [e1]Ann E. Nicholson, John Mark Agosta, M. Julia Flores:
Proceedings of the Ninth UAI Bayesian Modeling Applications Workshop, Catalina Island, United States, August 18, 2012. CEUR Workshop Proceedings 962, CEUR-WS.org 2013 [contents] - [i5]John Mark Agosta:
Constraining Influence Diagram Structure by Generative Planning: An Application to the Optimization of Oil Spill Response. CoRR abs/1302.3550 (2013) - [i4]John Mark Agosta:
"Conditional Inter-Causally Independent" Node Distributions, a Property of "Noisy-Or" Models. CoRR abs/1303.5704 (2013) - [i3]Tod S. Levitt, John Mark Agosta, Thomas O. Binford:
Model-based Influence Diagrams for Machine Vision. CoRR abs/1304.1517 (2013) - [i2]John Mark Agosta:
The structure of Bayes nets for vision recognition. CoRR abs/1304.2339 (2013) - 2012
- [i1]John Mark Agosta, Jaideep Chandrashekar, Mark Crovella, Nina Taft, Daniel Ting:
Mixture Models of Endhost Network Traffic. CoRR abs/1212.2744 (2012) - 2011
- [c11]Omar Zia Khan, Pascal Poupart, John Mark Agosta:
Automated Refinement of Bayes Networks' Parameters based on Test Ordering Constraints. NIPS 2011: 2591-2599 - 2010
- [c10]Rob Ennals, Dan Byler, John Mark Agosta, Barbara Rosario:
What is disputed on the web? WICOW 2010: 67-74 - [c9]Rob Ennals, Beth Trushkowsky, John Mark Agosta:
Highlighting disputed claims on the web. WWW 2010: 341-350
2000 – 2009
- 2009
- [c8]John Mark Agosta, Russell G. Almond, Dennis M. Buede, Marek J. Druzdzel, Judy Goldsmith, Silja Renooij:
Workshop summary: Seventh annual workshop on Bayes applications. ICML 2009: 3 - 2008
- [c7]Senthilkumar G. Cheetancheri, John Mark Agosta, Karl N. Levitt, Shyhtsun Felix Wu, Jeff Rowe:
Optimal Cost, Collaborative, and Distributed Response to Zero-Day Worms - A Control Theoretic Approach. RAID 2008: 231-250 - 2006
- [c6]Denver Dash, Branislav Kveton, John Mark Agosta, Eve M. Schooler, Jaideep Chandrashekar, Abraham Bachrach, Alex Newman:
When Gossip is Good: Distributed Probabilistic Inference for Detection of Slow Network Intrusions. AAAI 2006: 1115-1122 - [c5]Senthilkumar G. Cheetancheri, John Mark Agosta, Denver Dash, Karl N. Levitt, Jeff Rowe, Eve M. Schooler:
A distributed host-based worm detection system. LSAD@SIGCOMM 2006: 107-113
1990 – 1999
1980 – 1989
- 1989
- [c2]Tod S. Levitt, John Mark Agosta, Thomas O. Binford:
Model-Based Influence Diagrams for Machine Vision. UAI 1989: 371-388 - 1988
- [c1]John Mark Agosta:
The structure of bayes networks for visual recognition. UAI 1988: 397-406
Coauthor Index
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