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Jaroslaw Zola
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2020 – today
- 2024
- [j14]Subhadeep Karan, Zainul Abideen Sayed
, Jaroslaw Zola
End-to-End Bayesian Networks Exact Learning in Shared Memory. IEEE Trans. Parallel Distributed Syst. 35(4): 634-645 (2024) - [c32]Namit Juneja, Varun Chandola, Jaroslaw Zola, Olga Wodo, Parth Desai:
Resource Efficient Bayesian Optimization. CLOUD 2024: 12-19 - [c31]Asif Imran, Tevfik Kosar, Jaroslaw Zola, Muhammed Fatih Bulut:
Towards Sustainable Cloud Software Systems through Energy-Aware Code Smell Refactoring. CLOUD 2024: 223-234 - 2023
- [j13]Andrew J. Mikalsen, Jaroslaw Zola
Coriolis: enabling metagenomic classification on lightweight mobile devices. Bioinform. 39(Supplement-1): 66-75 (2023) - [j12]Vicky Zheng
Identifying Taxonomic Units in Metagenomic DNA Streams on Mobile Devices. IEEE ACM Trans. Comput. Biol. Bioinform. 20(2): 1092-1103 (2023) - [c30]Pawel Bratek
Parallel Auto-Scheduling of Counting Queries in Machine Learning Applications on HPC Systems. Euro-Par Workshops 2023: 327-333 - [c29]Zainul Abideen Sayed, Jaroslaw Zola
SCoOL - Scalable Common Optimization Library. HiPC 2023: 277-287 - [i9]Asif Imran, Tevfik Kosar, Jaroslaw Zola, Muhammed Fatih Bulut:
Predicting the Impact of Batch Refactoring Code Smells on Application Resource Consumption. CoRR abs/2306.15763 (2023) - 2022
- [j11]Devyani Jivani
GraSPI: Extensible software for the graph-based quantification of morphology in organic electronics. SoftwareX 17: 100969 (2022) - [c28]Jason Niu, Jaroslaw Zola
Counting Induced 6-Cycles in Bipartite Graphs. ICPP 2022: 36:1-36:10 - [c27]Bekir Oguzhan Turkkan
GreenABR: energy-aware adaptive bitrate streaming with deep reinforcement learning. MMSys 2022: 150-163 - 2021
- [j10]Sarah Mullin, Jaroslaw Zola
Longitudinal K-means approaches to clustering and analyzing EHR opioid use trajectories for clinical subtypes. J. Biomed. Informatics 122: 103889 (2021) - [c26]Pawel Bratek
Parallelization and Auto-scheduling of Data Access Queries in ML Workloads. Euro-Par Workshops 2021: 525-529 - [c25]Namit Juneja, Jaroslaw Zola, Varun Chandola, Olga Wodo
Graph-based Strategy for Establishing Morphology Similarity. SSDBM 2021: 169-180 - 2020
- [j9]Frank Schoeneman, Varun Chandola
Learning Manifolds from Dynamic Process Data. Algorithms 13(2): 30 (2020) - [c24]Mohammad Mahdi Javanmard, Zafar Ahmad
Efficient Execution of Dynamic Programming Algorithms on Apache Spark. CLUSTER 2020: 337-348
2010 – 2019
- 2019
- [c23]Frank Schoeneman, Jaroslaw Zola
Solving All-Pairs Shortest-Paths Problem in Large Graphs Using Apache Spark. ICPP 2019: 9:1-9:10 - [i8]Frank Schoeneman, Jaroslaw Zola:
Performance of All-Pairs Shortest-Paths Solvers with Apache Spark. CoRR abs/1902.04446 (2019) - 2018
- [c22]Frank Schoeneman, Jaroslaw Zola:
Scalable Manifold Learning for Big Data with Apache Spark. IEEE BigData 2018: 272-281 - [c21]Frank Schoeneman, Varun Chandola, Nils Napp, Olga Wodo
Entropy-Isomap: Manifold Learning for High-dimensional Dynamic Processes. IEEE BigData 2018: 1655-1660 - [c20]Subhadeep Karan, Matthew Eichhorn, Blake Hurlburt, Grant Iraci, Jaroslaw Zola:
Fast Counting in Machine Learning Applications. UAI 2018: 540-549 - [c19]Steven Y. Ko, Lauren Sassoubre, Jaroslaw Zola
Applications and Challenges of Real-time Mobile DNA Analysis. HotMobile 2018: 1-6 - [i7]Frank Schoeneman, Varun Chandola, Nils Napp, Olga Wodo, Jaroslaw Zola:
Entropy-Isomap: Manifold Learning for High-dimensional Dynamic Processes. CoRR abs/1802.06823 (2018) - [i6]Subhadeep Karan, Matthew Eichhorn, Blake Hurlburt, Grant Iraci, Jaroslaw Zola:
Fast Counting in Machine Learning Applications. CoRR abs/1804.04640 (2018) - [i5]Marina Blanton, Ah Reum Kang
Privacy Preserving Analytics on Distributed Medical Data. CoRR abs/1806.06477 (2018) - [i4]Frank Schoeneman, Jaroslaw Zola:
Scalable Manifold Learning for Big Data with Apache Spark. CoRR abs/1808.10776 (2018) - 2017
- [c18]Subhadeep Karan, Jaroslaw Zola:
Scalable Exact Parent Sets Identification in Bayesian Networks Learning with Apache Spark. HiPC 2017: 33-41 - [c17]Frank Schoeneman, Suchismit Mahapatra
Error Metrics for Learning Reliable Manifolds from Streaming Data. SDM 2017: 750-758 - [i3]Subhadeep Karan, Jaroslaw Zola:
Scalable Exact Parent Sets Identification in Bayesian Networks Learning with Apache Spark. CoRR abs/1705.06390 (2017) - [i2]Steven Y. Ko, Lauren Sassoubre, Jaroslaw Zola:
Applications and Challenges of Real-time Mobile DNA Analysis. CoRR abs/1711.07370 (2017) - 2016
- [c16]Subhadeep Karan, Jaroslaw Zola
Exact structure learning of Bayesian networks by optimal path extension. IEEE BigData 2016: 48-55 - [c15]Srinivas Aluru, David A. Bader
HiCOMB Introduction and Committees. IPDPS Workshops 2016: 407 - [i1]Subhadeep Karan, Jaroslaw Zola:
Exact Structure Learning of Bayesian Networks by Optimal Path Extension. CoRR abs/1608.02682 (2016) - 2015
- [j8]Sai Kiranmayee Samudrala, Jaroslaw Zola, Srinivas Aluru, Baskar Ganapathysubramanian:
Parallel Framework for Dimensionality Reduction of Large-Scale Datasets. Sci. Program. 2015: 180214:1-180214:12 (2015) - 2014
- [j7]Javier Diaz Montes, Yu Xie, Ivan Rodero
Federated Computing for the Masses-Aggregating Resources to Tackle Large-Scale Engineering Problems. Comput. Sci. Eng. 16(4): 62-72 (2014) - [c14]Jaroslaw Zola
Constructing Similarity Graphs from Large-Scale Biological Sequence Collections. IPDPS Workshops 2014: 500-507 - [p3]Jaroslaw Zola:
Parallel Computing for Gene Networks Reverse Engineering. Approaches in Integrative Bioinformatics 2014: 337-354 - 2013
- [j6]Xiao Yang, Jaroslaw Zola, Srinivas Aluru:
Large-Scale metagenomic sequence Clustering on Map-Reduce Clusters. J. Bioinform. Comput. Biol. 11(1) (2013) - [j5]Olga Nikolova, Jaroslaw Zola, Srinivas Aluru:
Parallel globally optimal structure learning of Bayesian networks. J. Parallel Distributed Comput. 73(8): 1039-1048 (2013) - [c13]Ananth Kalyanaraman, Jaroslaw Zola:
BigLS - The 1st International Workshop on Big Data in Life Sciences. ICCABS 2013: 1 - [c12]Jaroslaw Zola, David A. Bader
HiCOMB Introduction. IPDPS Workshops 2013: 499-500 - 2011
- [j4]Abhinav Sarje, Jaroslaw Zola, Srinivas Aluru:
Accelerating Pairwise Computations on Cell Processors. IEEE Trans. Parallel Distributed Syst. 22(1): 69-77 (2011) - [c11]Xiao Yang, Jaroslaw Zola, Srinivas Aluru:
Parallel Metagenomic Sequence Clustering Via Sketching and Maximal Quasi-clique Enumeration on Map-Reduce Clouds. IPDPS 2011: 1223-1233 - [r1]Jaroslaw Zola, Srinivas Aluru:
Systems Biology, Network Inference in. Encyclopedia of Parallel Computing 2011: 1997-2002 - 2010
- [j3]Jaroslaw Zola, Maneesha Aluru, Abhinav Sarje, Srinivas Aluru:
Parallel Information-Theory-Based Construction of Genome-Wide Gene Regulatory Networks. IEEE Trans. Parallel Distributed Syst. 21(12): 1721-1733 (2010) - [p2]Abhinav Sarje, Jaroslaw Zola, Srinivas Aluru:
Pairwise Computations on the Cell Processor. Scientific Computing with Multicore and Accelerators 2010: 297-327
2000 – 2009
- 2009
- [c10]Olga Nikolova, Jaroslaw Zola, Srinivas Aluru:
A parallel algorithm for exact Bayesian network inference. HiPC 2009: 342-349 - [c9]Jaroslaw Zola, Abhinav Sarje, Srinivas Aluru:
Constructing Gene Regulatory Networks on Clusters of Cell Processors. ICPP 2009: 108-115 - 2008
- [j2]Michael Ott, Jaroslaw Zola, Srinivas Aluru, Andrew D. Johnson, Daniel Janies, Alexandros Stamatakis:
Large-scale phylogenetic analysis on current HPC architectures. Sci. Program. 16(2-3): 255-270 (2008) - [c8]Jaroslaw Zola, Maneesha Aluru, Srinivas Aluru:
Parallel Information Theory Based Construction of Gene Regulatory Networks. HiPC 2008: 336-349 - 2007
- [c7]Jaroslaw Zola, Xiao Yang, Adrian Rospondek, Srinivas Aluru:
PARALLEL-TCOFFEE: A parallel multiple sequence aligner. PDCS 2007: 248-253 - [c6]Michael Ott, Jaroslaw Zola, Alexandros Stamatakis
Large-scale maximum likelihood-based phylogenetic analysis on the IBM BlueGene/L. SC 2007: 4 - [p1]Denis Trystram, Jaroslaw Zola:
Multiple Sequence Alignment and Phylogenetic Inference. Grid Computing for Bioinformatics and Computational Biology 2007: 123-155 - 2006
- [j1]Gilles Parmentier, Denis Trystram, Jaroslaw Zola:
Large scale multiple sequence alignment with simultaneous phylogeny inference. J. Parallel Distributed Comput. 66(12): 1534-1545 (2006) - [c5]Jaroslaw Zola, Denis Trystram, Andrei Tchernykh
Parallel multiple sequence alignment with local phylogeny search by simulated annealing. IPDPS 2006 - 2005
- [c4]Denis Trystram, Jaroslaw Zola:
Parallel Multiple Sequence Alignment with Decentralized Cache Support. Euro-Par 2005: 1217-1226 - 2004
- [c3]Jaroslaw Zola:
CaLi, Efficient Library for Cache Implementation. ENC 2004: 415-420 - [c2]Gilles Parmentier, Denis Trystram, Jaroslaw Zola:
Cache-Based Parallelization of Multiple Sequence Alignment Problem. Euro-Par 2004: 1005-1012 - 2001
- [c1]Jaroslaw Zola, Roman Wyrzykowski
EPL-Julia the High-Performance Library for Evolutionary Computations. PPAM 2001: 652-662
Coauthor Index
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last updated on 2024-10-07 21:22 CEST by the dblp team
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