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ORCIDAndrew J. Connolly
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2020 – today
- 2022
[i10]Cora Dvorkin, Siddharth Mishra-Sharma, Brian Nord
, V. Ashley Villar, Camille Avestruz, Keith Bechtol, Aleksandra Ciprijanovic, Andrew J. Connolly, Lehman H. Garrison, Gautham Narayan, Francisco Villaescusa-Navarro:
Machine Learning and Cosmology. CoRR abs/2203.08056 (2022)- 2020
- [c14]Parmita Mehta, Stephen Portillo, Magdalena Balazinska, Andrew J. Connolly:
Toward Sampling for Deep Learning Model Diagnosis. ICDE 2020: 1910-1913 - [i9]J. Bryce Kalmbach, Jacob VanderPlas, Andrew J. Connolly:
Applying Information Theory to Design Optimal Filters for Photometric Redshifts. CoRR abs/2001.01372 (2020) - [i8]Parmita Mehta, Stephen Portillo, Magdalena Balazinska, Andrew J. Connolly:
Sampling for Deep Learning Model Diagnosis (Technical Report). CoRR abs/2002.09754 (2020)
2010 – 2019
- 2019
- [i7]Petar Zecevic, Colin T. Slater, Mario Juric, Andrew J. Connolly, Sven Loncaric, Eric C. Bellm, V. Zach Golkhou, Krzysztof Suberlak:
AXS: A framework for fast astronomical data processing based on Apache Spark. CoRR abs/1905.09034 (2019) - [i6]Brian Nord, Andrew J. Connolly, Jamie Kinney, Jeremy Kubica, Gautaum Narayan, Joshua E. G. Peek, Chad Schafer, Erik J. Tollerud, Camille Avestruz, Gutti Jogesh Babu, Simon Birrer, Douglas Burke, João Caldeira, Douglas A. Caldwell, Joleen K. Carlberg, Yen-Chi Chen, Chuanfei Dong, Eric D. Feigelson, V. Zach Golkhou, Vinay Kashyap, T. S. Li, Thomas Loredo, Luisa Lucie-Smith, Kaisey S. Mandel, J. R. Martínez-Galarza, Adam A. Miller, Priyamvada Natarajan, Michelle Ntampaka, Andy Ptak, David Rapetti, Lior Shamir, Aneta Siemiginowska, Brigitta M. Sipocz, Arfon M. Smith, Nhan Tran, Ricardo Vilalta, Lucianne M. Walkowicz, John ZuHone:
Algorithms and Statistical Models for Scientific Discovery in the Petabyte Era. CoRR abs/1911.02479 (2019) - 2017
- [j2]Parmita Mehta, Sven Dorkenwald, Dongfang Zhao, Tomer Kaftan, Alvin Cheung, Magdalena Balazinska, Ariel Rokem, Andrew J. Connolly, Jacob VanderPlas, Yusra AlSayyad:
Comparative Evaluation of Big-Data Systems on Scientific Image Analytics Workloads. Proc. VLDB Endow. 10(11): 1226-1237 (2017) - [i5]Pablo Huijse, Pablo A. Estévez, Francisco Förster, Scott F. Daniel, Andrew J. Connolly, Pavlos Protopapas, Rodrigo Carrasco, José C. Príncipe:
Robust period estimation using mutual information for multi-band light curves in the synoptic survey era. CoRR abs/1709.03541 (2017) - 2016
- [c13]Zeljko Ivezic, Andrew J. Connolly, Mario Juric:
Everything we'd like to do with LSST data, but we don't know (yet) how. Astroinformatics 2016: 93-102 - [i4]Parmita Mehta, Sven Dorkenwald, Dongfang Zhao, Tomer Kaftan, Alvin Cheung, Magdalena Balazinska, Ariel Rokem, Andrew J. Connolly, Jacob VanderPlas, Yusra AlSayyad:
Comparative Evaluation of Big-Data Systems on Scientific Image Analytics Workloads. CoRR abs/1612.02485 (2016) - 2015
- [c12]Emad Soroush, Magdalena Balazinska, K. Simon Krughoff, Andrew J. Connolly:
Efficient iterative processing in the SciDB parallel array engine. SSDBM 2015: 39:1-39:6 - [c11]Ryan Maas, Jeremy Hyrkas, Olivia Grace Telford, Magdalena Balazinska, Andrew J. Connolly, Bill Howe:
Gaussian Mixture Models Use-Case: In-Memory Analysis with Myria. IMDM@VLDB 2015: 3:1-3:8 - [i3]Emad Soroush, Magdalena Balazinska, K. Simon Krughoff, Andrew J. Connolly:
Efficient Iterative Processing in the SciDB Parallel Array Engine. CoRR abs/1506.00307 (2015) - 2013
- [j1]Matthew I. Moyers, Emad Soroush, Spencer Wallace, K. Simon Krughoff, Jake VanderPlas, Magdalena Balazinska, Andrew J. Connolly:
A Demonstration of Iterative Parallel Array Processing in Support of Telescope Image Analysis. Proc. VLDB Endow. 6(12): 1322-1325 (2013) - 2012
- [c10]Jacob VanderPlas, Andrew J. Connolly, Zeljko Ivezic, Alexander G. Gray:
Introduction to astroML: Machine learning for astrophysics. CIDU 2012: 47-54 - [c9]William B. March, Andrew J. Connolly, Alexander G. Gray:
Fast algorithms for comprehensive n-point correlation estimates. KDD 2012: 1478-1486 - [c8]William B. March, Kenneth Czechowski, Marat Dukhan, Thomas Benson, Dongryeol Lee, Andrew J. Connolly, Richard W. Vuduc, Edmond Chow, Alexander G. Gray:
Optimizing the computation of n-point correlations on large-scale astronomical data. SC 2012: 74 - 2011
- [c7]Yusra AlSayyad, K. Simon Krughoff, Bill Howe, Andrew J. Connolly, Magdalena Balazinska, Lynne Jones:
Towards Efficient and Precise Queries over Ten Million Asteroid Trajectory Models. SSDBM 2011: 568-570 - [c6]Liang Xiong, Barnabás Póczos, Jeff G. Schneider, Andrew J. Connolly, Jake VanderPlas:
Hierarchical Probabilistic Models for Group Anomaly Detection. AISTATS 2011: 789-797 - 2010
- [i2]Keith Wiley, Andrew J. Connolly, Jeffrey P. Gardner, K. Simon Krughoff, Magdalena Balazinska, Bill Howe, YongChul Kwon, Yingyi Bu:
Astronomy in the Cloud: Using MapReduce for Image Coaddition. CoRR abs/1010.1015 (2010)
2000 – 2009
- 2009
- [c5]Dan Suciu, Andrew J. Connolly, Bill Howe:
Embracing Uncertainty in Large-Scale Computational Astrophysics. MUD 2009: 63-77 - 2007
- [c4]Jeffrey P. Gardner, Andrew J. Connolly, Cameron McBride:
Enabling rapid development of parallel tree search applications. CLADE@HPDC 2007: 1-10 - 2005
- [c3]Jeremy Kubica, Andrew W. Moore, Andrew J. Connolly, Robert Jedicke:
A multiple tree algorithm for the efficient association of asteroid observations. KDD 2005: 138-146 - [c2]Jeremy Kubica, Joseph Masiero, Andrew W. Moore, Robert Jedicke, Andrew J. Connolly:
Variable KD-Tree Algorithms for Spatial Pattern Search and Discovery. NIPS 2005: 691-698 - 2004
- [c1]Brigham S. Anderson, Andrew W. Moore, Andrew J. Connolly, Robert Nichol:
Fast nonlinear regression via eigenimages applied to galactic morphology. KDD 2004: 40-48 - 2002
- [i1]Alexander S. Szalay, Tamas Budavari, Andrew J. Connolly, Jim Gray, Takahiko Matsubara, Adrian Pope, Istvan Szapudi:
Spatial Clustering of Galaxies in Large Datasets. CoRR cs.DB/0208015 (2002)
Coauthor Index
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