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2017

1. B. Wang, S. Ethier, W. Tang, K. Ibrahim, K. Madduri, S. Williams, and L. Oliker, “Modern gyrokinetic particle-in-cell simulation of fusion plasmas on top supercomputers,” Int'l. Journal of High Performance Computing Applications (IJHPCA), 2017, to appear.
2. H. Kabir and K. Madduri, “Shared-memory graph truss decomposition,” in Proc. 24th IEEE Int'l. Conf. on High Performance Computing, Data, and Analytics (HiPC), Dec. 2017, to appear.
3. V. Rengasamy, T.-Y. Fu, W.-C. Lee, and K. Madduri, “Optimizing Word2Vec performance on multicore systems,” in Proc. Workshop on Irregular Applications: Architectures and Algorithms (IA³), Nov. 2017, to appear.
4. J. Kotra, S. Kim, K. Madduri, and M. T. Kandemir, “Congestion-aware memory management on NUMA platforms: A VMware ESXi case study,” in Proc. IEEE Int'l. Symp. on Workload Characterization (IISWC), Oct. 2017, to appear.
5. H. Kabir and K. Madduri, “Parallel k-truss decomposition on multicore systems,” in Proc. 21st IEEE High Performance Extreme Computing (HPEC) Conference, Sep. 2017.
6. L. Leonard, A. M. MacEachren, and K. Madduri, “Graph-based visual analysis for large-scale hydrological modeling,” SAGE Information Visualization (InfoVis), vol. 16, no. 3, pp. 205--216, 2017.
7. S. Parimalarangan, G. M. Slota, and K. Madduri, “Fast parallel graph triad census and triangle counting on shared-memory platforms,” in Proc. 2nd IEEE Workshop on Parallel and Distributed Processing for Computational Social Systems (ParSocial), Jun. 2017.
8. H. Kabir and K. Madduri, “Parallel k-core decomposition on multicore platforms,” in Proc. 2nd IEEE Workshop on Parallel and Distributed Processing for Computational Social Systems (ParSocial), Jun. 2017.
9. R. Narayanan and K. Madduri, “Parallel particle-in-cell performance optimization: A case study of electrospray simulation,” in Proc. 18th IEEE Int'l. Workshop on Parallel and Distributed Scientific and Engineering Computing (PDSEC), Jun. 2017.
10. H. Zhan and K. Madduri, “Analyzing community structure in networks,” in Proc. 1st Workshop on the Intersection of Graph Algorithms and Machine Learning (GraML), Jun. 2017.
11. G. M. Slota, S. Rajamanickam, K. Madduri, and K. Devine, “Partitioning trillion-edge graphs in minutes,” in Proc. 31st IEEE Int'l. Parallel and Distributed Processing Symposium (IPDPS). IEEE, May 2017.
12. V. Rengasamy, P. Medvedev, and K. Madduri, “Parallel and memory-efficient preprocessing for metagenome assembly,” in Proc. 16th IEEE Int'l. Workshop on High Performance Computational Biology (HiCOMB), May 2017.
13. G. M. Slota, S. Rajamanickam, and K. Madduri, “Order or Shuffle: Empirically evaluating vertex order impact on parallel graph computations,” in Proc. Workshop on Graph Algorithms Building Blocks (GABB), May 2017.
14. G. M. Slota, S. Rajamanickam, K. Madduri, and K. D. Devine, “Partitioning irregular graphs at the trillion-edge scale,” SIAM Conf. on Computational Science and Engineering (CSE), Feb 2017.
15. V. Rengasamy and K. Madduri, “High-performance graph traversal for De Bruijn graph-based metagenome assembly,” SIAM Conf. on Computational Science and Engineering (CSE), Feb 2017.

2016

1. W. Tang, B. Wang, S. Ethier, G. Kwasniewski, T. Hoefler, K. Ibrahim, K. Madduri, S. Williams, L. Oliker, C. Rosales-Fernandez, and T. Williams, “Extreme scale plasma turbulence simulations on top supercomputers worldwide,” in Proc. ACM/IEEE Conf. on Supercomputing (SC), Nov. 2016.
2. G. M. Slota, K. Madduri, and S. Rajamanickam, “Complex network partitioning using label propagation,” SIAM Journal on Scientific Computing (SISC), vol. 38, no. 5, pp. S620--S645, 2016.
3. G. Slota, S. Rajamanickam, and K. Madduri, “HPCGraph: Benchmarking massive graph analytics on supercomputers,” 7th SIAM Workshop on Combinatorial Scientific Computing (CSC), Oct. 2016.
4. L. Leonard, K. Madduri, and C. Duffy, “Tuning heterogeneous computing platforms for large-scale hydrology data management,” IEEE Trans. Parallel Distrib. Syst., vol. 27, no. 9, pp. 2753--65, 2016.
5. H. Zhan and K. Madduri, “A combinatorially-interpretable matrix factorization for network community structure evaluation,” SIAM Annual Meeting, Jul. 2016.
6. V. Rengasamy and K. Madduri, “SPRITE: A fast parallel SNP detection pipeline,” in Proc. 31st Int'l. Conf. ISC High Performance. Springer, Jun. 2016.
7. G. M. Slota, S. Rajamanickam, and K. Madduri, “A case study of complex graph analysis in distributed memory: Implementation and optimization,” in Proc. 30th IEEE Int'l. Parallel and Distributed Processing Symposium (IPDPS). IEEE, May 2016.
8. H. Zhan and K. Madduri, “GSK: Graph sparsification as a knapsack problem formulation,” in Proc. 3rd SDM Workshop on Mining Networks and Graphs (MNG), May 2016.

2015

1. L. Leonard, K. Madduri, and C. J. Duffy, “Graph-based analysis for large-scale hydrological modeling,” in Proc. IEEE VIS Exploring Graphs at Scale (EGAS) Workshop, Oct. 2015.
2. K. Madduri, V. Rengasamy, and P. Medvedev, “SPRITE: A fast parallel SNP detection pipeline,” poster presentation at the American Society of Human Genetics (ASHG) Annual Meeting, Oct. 2015.
3. G. M. Slota and K. Madduri, “Parallel color-coding,” Parallel Computing, vol. 47, pp. 51--69, 2015.
4. G. M. Slota, S. Rajamanickam, and K. Madduri, “High-performance graph analytics on manycore processors,” in Proc. 29th IEEE Int'l. Parallel and Distributed Processing Symposium (IPDPS). IEEE, May 2015, pp. 17--27.
5. G. M. Slota, S. Rajamanickam, and K. Madduri, “PuLP: Complex objective partitioning of small-world networks using label propagation,” SIAM Conf. on Computational Science and Engineering, Mar. 2015.

2014

1. G. M. Slota and K. Madduri, “Simple parallel biconnectivity algorithms for multicore platforms,” in Proc. 20th IEEE Int'l. Conf. on High Performance Computing (HiPC). IEEE, Dec. 2014, pp. 1--10.
2. G. M. Slota, K. Madduri, and S. Rajamanickam, “PuLP: Scalable multi-objective multi-constraint partitioning for small-world networks,” in Proc. 2nd IEEE Int'l. Conf. on Big Data (BigData). IEEE, Oct. 2014, pp. 481--490.
3. T. Panitanarak and K. Madduri, “Performance analysis of single-source shortest path algorithms on distributed-memory systems,” in Proc. 6th SIAM Workshop on Combinatorial Scientific Computing (CSC), Jul. 2014, pp. 60--63.
4. G. M. Slota, S. Rajamanickam, and K. Madduri, “BFS and Coloring-based parallel algorithms for strongly connected components and related problems,” in Proc. 28th IEEE Int'l. Parallel and Distributed Processing Symposium (IPDPS). IEEE, May 2014, pp. 550--559.
5. G. M. Slota and K. Madduri, “Complex network analysis using parallel approximate motif counting,” in Proc. 28th IEEE Int'l. Parallel and Distributed Processing Symposium (IPDPS). IEEE, May 2014, pp. 405--414.
6. J. Choi, A. Chandramowlishwaran, K. Madduri, and R. Vuduc, “A CPU-GPU hybrid implementation and model-driven scheduling of the Fast Multipole Method,” in Proc. 7th Workshop on General Purpose Processing using GPUs (GPGPU), Mar. 2014, pp. 64:1--64:8.
7. G. Slota, S. Rajamanickam, and K. Madduri, “Parallel strongly connected components in shared memory architectures,” SIAM Conf. on Parallel Processing for Scientific Computing, Feb. 2014.
8. G. Slota and K. Madduri, “Characterizing biological networks using subgraph counting and enumeration,” SIAM Conf. on Parallel Processing for Scientific Computing, Feb. 2014.

2013

1. B. Wang, S. Ethier, W. Tang, T. Williams, K. Ibrahim, K. Madduri, S. Williams, and L. Oliker, “Kinetic turbulence simulations at extreme scale on leadership-class systems,” in Proc. ACM/IEEE Conf. on Supercomputing (SC), Nov. 2013, pp. 82:1--82:12.
2. K. Z. Ibrahim, K. Madduri, S. Williams, B. Wang, S. Ethier, and L. Oliker, “Analysis and optimization of gyrokinetic toroidal simulations on homogenous and heterogenous platforms,” Int'l. Journal of High Performance Computing Applications (IJHPCA), vol. 27, no. 4, pp. 454--473, 2013.
3. G. Slota and K. Madduri, “Fast approximate subgraph counting and enumeration,” in Proc. 42nd Int'l. Conf. on Parallel Processing (ICPP), Oct. 2013, pp. 210--219.
4. K. Madduri, “Parallel analysis of graph-structured data in genomics and proteomics,” First Int'l. Workshop on Big Data in Life Sciences (BigLS), Jun. 2013.
5. A. Buluç and K. Madduri, “Graph partitioning for scalable distributed graph computations,” in Graph Partitioning and Graph Clustering, D. Bader, H. Meyerhenke, P. Sanders, and D. Wagner, Eds. AMS, 2013, ch. 6, pp. 81--100.
6. D. Hadka, P. Reed, and K. Madduri, “Scalability analysis of the asynchronous, master-slave multiobjective evolutionary algorithm,” in Proc. 16th Int'l. Workshop on Nature Inspired Distributed Computing (NIDISC), May 2013, pp. 425--434.

2012

1. M. Frasca, K. Madduri, and P. Raghavan, “NUMA-aware graph mining techniques for performance and energy efficiency,” in Proc. ACM/IEEE Conf. on Supercomputing (SC), Nov. 2012, pp. 95:1--95:11.
2. K. Madduri, J. Su, S. Williams, L. Oliker, S. Ethier, and K. Yelick, “Optimization of parallel particle-to-grid interpolation on leading multicore platforms,” IEEE Trans. Parallel Distrib. Syst., vol. 23, no. 10, pp. 1915--1922, 2012.
3. K. Madduri, “High-performance metagenomic data clustering and assembly,” SIAM Annual Meeting, Jul. 2012.
4. A. Chandramowlishwaran, J. Choi, K. Madduri, and R. W. Vuduc, “Brief announcement: Towards a Communication optimal Fast Multipole Method and its implications at Exascale,” in Proc. 24th ACM Symp. on Parallelism in Algorithms and Architectures (SPAA). ACM, Jun. 2012, pp. 182--184.
5. K. Madduri, “Scalable SPARQL querying with compressed bitmap indexes,” SIAM Conf. on Parallel Processing for Scientific Computing, Mar. 2012.
6. A. Buluç and K. Madduri, “Graph partitioning for scalable distributed graph computations,” in Proc. 10th DIMACS Implementation Challenge Workshop -- Graph Partitioning and Graph Clustering, Feb. 2012.
7. D. A. Bader and K. Madduri, “Computational challenges in emerging combinatorial scientific computing applications,” in Combinatorial Scientific Computing, U. Naumann and O. Schenk, Eds. Boca Raton, FL: Chapman and Hall/CRC, 2012, ch. 17, pp. 471--494.

2011

1. K. Madduri, “SNAP (Small-World Network Analysis and Partitioning) framework,” in Encyclopedia of Parallel Computing, D. A. Padua, Ed. Springer, 2011, pp. 1832--1837.
2. K. Madduri, K. Z. Ibrahim, S. Williams, E.-J. Im, S. Ethier, J. Shalf, and L. Oliker, “Gyrokinetic toroidal simulations on leading multi- and manycore HPC systems,” in Proc. Conf. on High Performance Computing, Networking, Storage and Analysis (SC). ACM, Nov. 2011, p. 23.
3. A. Buluç and K. Madduri, “Parallel breadth-first search on distributed memory systems,” in Proc. Conf. on High Performance Computing, Networking, Storage and Analysis (SC). ACM, Nov. 2011, p. 65.
4. K. Madduri, E.-J. Im, K. Z. Ibrahim, S. Williams, S. Ethier, and L. Oliker, “Gyrokinetic particle-in-cell optimization on emerging multi- and manycore platforms,” Parallel Computing, vol. 37, no. 9, pp. 501--520, 2011.
5. K. Madduri and K. Wu, “Massive-scale RDF processing using compressed bitmap indexes,” in Proc. 23rd Int'l. Conf. on Scientific and Statistical Database Management (SSDBM), ser. LNCS, J. B. Cushing, J. C. French, and S. Bowers, Eds., vol. 6809. Springer, Jul. 2011, pp. 470--479.
6. D. A. Bader, C. E. Heitsch, and K. Madduri, “Large-scale network analysis,” in Graph Algorithms in the Language of Linear Algebra, J. Kepner and J. Gilbert, Eds. Philadelphia, PA: SIAM, 2011, ch. 12, pp. 253--285.
7. R. Sudarsan, J. Borrill, C. Cantalupo, T. Kisner, K. Madduri, L. Oliker, Y. Zheng, and H. Simon, “Cosmic microwave background map-making at the petascale and beyond,” in Proc. 25th Int'l. Conf. on Supercomputing (ICS). ACM, May-June 2011, pp. 305--316.
8. K. Madduri, “Optimizing short-read genome assembly algorithms for emerging multicore platforms,” SIAM Conf. on Computational Science and Engineering, February-March 2011.

2010

1. D. A. Bader, V. Agarwal, K. Madduri, and F. Petrini, “Combinatorial algorithm design on the Cell/B.E. processor,” in Scientific Computing with Multicore and Accelerators, J. Kurzak, D. A. Bader, and J. Dongarra, Eds. Boca Raton, FL: CRC Press, 2010, ch. 10, pp. 195--216.
2. A. Chandramowlishwaran, K. Madduri, and R. Vuduc, “Diagnosis, tuning, and redesign for multicore performance: A case study of the Fast Multipole Method,” in Proc. Conf. on High Performance Computing, Networking, Storage and Analysis (SC). ACM/IEEE, Nov. 2010, pp. 1--12.
3. K. Subramani and K. Madduri, “Two-level heaps: a new priority queue structure with applications to the single source shortest path problem,” Computing, vol. 90, no. 3-4, pp. 113--130, 2010.
4. E. Strohmaier, S. Williams, A. Kaiser, K. Madduri, K. Ibrahim, D. Bailey, and J. W. Demmel, “A kernel testbed for parallel architecture, language, and performance research,” in Proc. 8th Int'l. Conf. of Numerical Analysis and Applied Mathematics (ICNAAM), ser. AIP Conference Proceedings, vol. 1281, Sep. 2010, pp. 1297--1300.
5. K. Wu, K. Madduri, and S. Canon, “Multi-level bitmap indexes for flash memory storage,” in Proc. 14th Int'l. Database Engineering & Applications Symposium (IDEAS). ACM, Aug. 2010, pp. 114--116.
6. K. Madduri, “Hybrid parallel programming for massive graph analysis,” SIAM Annual Meeting, Jul. 2010.
7. A. Kaiser, S. Williams, K. Madduri, K. Ibrahim, D. H. Bailey, J. Demmel, and E. Strohmaier, “A case for a testbed of kernels for software/hardware co-design research,” in Proc. 2nd USENIX Workshop on Hot Topics in Parallelism (HotPar). USENIX, Jun. 2010.
8. J. Orlin, K. Madduri, K. Subramani, and M. Williamson, “A faster algorithm for the single source shortest path problem with few distinct positive lengths,” Journal of Discrete Algorithms, vol. 8, no. 2, pp. 189--198, 2010.
9. K. Subramani, C. Tauras, and K. Madduri, “Space-time tradeoffs in negative cycle detection - an empirical analysis of the Stressing algorithm,” Applied Mathematics and Computation, vol. 215, no. 10, pp. 3563--3575, 2010.

2009

1. K. Madduri, S. Williams, S. Ethier, L. Oliker, J. Shalf, E. Strohmaier, and K. Yelick, “Memory-efficient optimization of gyrokinetic particle-to-grid interpolation for multicore processors,” in Proc. ACM/IEEE Conf. on High Performance Computing (SC). ACM/IEEE, Nov. 2009.
2. K. Madduri and K. Wu, “Efficient joins with compressed bitmap indices,” in Proc. 18th ACM Conf. on Information and Knowledge Management (CIKM). ACM, Nov. 2009, pp. 1017--1026.
3. K. Madduri, “Scaling up graph algorithms on emerging multicore systems,” SIAM Annual Meeting, Jul. 2009.
4. X. Gu, K. Madduri, K. Subramani, and H.-J. Lai, “Improved algorithms for detecting negative cost cycles in undirected graphs,” in Proc. 3rd Int'l. Frontiers of Algorithmics Workshop (FAW), ser. LNCS, X. Deng, J. Hopcroft, and J. Xue, Eds., vol. 5598. Springer, Jun. 2009, pp. 40--50.
5. K. Subramani and K. Madduri, “Two-level heaps: a new priority queue structure with applications to the single source shortest path problem,” in Proc. 3rd Int'l. Conf. on Combinatorial Optimization and Applications (COCOA), ser. LNCS, D.-Z. Du, X. Hu, and P. M. Pardalos, Eds., vol. 5573. Springer, Jun. 2009, pp. 186--196.
6. K. Madduri, D. Ediger, K. Jiang, D. A. Bader, and D. Chavarria-Miranda, “A faster parallel algorithm and efficient multithreaded implementations for evaluating betweenness centrality on massive datasets,” in Proc. 3rd Workshop on Multithreaded Architectures and Applications (MTAAP). IEEE Computer Society, May 2009.
7. K. Madduri and D. A. Bader, “Compact graph representations and parallel connectivity algorithms for massive dynamic network analysis,” in Proc. 23rd IEEE Int'l. Parallel and Distributed Processing Symposium (IPDPS). IEEE Computer Society, May 2009.
8. K. Madduri, D. A. Bader, J. W. Berry, and J. R. Crobak, “Parallel shortest path algorithms for solving large-scale instances,” in The Shortest Path Problem: Ninth DIMACS Implementation Challenge, C. Demetrescu, A. V. Goldberg, and D. Johnson, Eds. Providence, RI: AMS, 2009, vol. 74, pp. 249--290.

2008

1. D. A. Bader and K. Madduri, “A graph-theoretic analysis of the human protein-interaction network using multicore parallel algorithms,” Parallel Computing, vol. 34, no. 11, pp. 627--639, 2008.
2. K. Subramani and K. Madduri, “A Randomized Queueless Algorithm for Breadth-First Search,” Int'l. Journal of Computers and their Applications, vol. 15, no. 3, pp. 177--186, 2008.
3. D. A. Bader and K. Madduri, “SNAP: Small-world Network Analysis and Partitioning: an open-source parallel graph framework for the exploration of large-scale networks,” in Proc. 22nd IEEE Int'l. Parallel and Distributed Processing Symposium (IPDPS). IEEE, Apr. 2008.
4. K. Madduri, “High performance combinatorial techniques for processing dynamic interaction networks,” SIAM Conf. on Parallel Processing for Scientific Computing, Mar. 2008.

2007

1. K. Madduri, D. A. Bader, J. W. Berry, J. R. Crobak, and B. A. Hendrickson, “Multithreaded algorithms for processing massive graphs,” in Petascale Computing: Algorithms and Applications, D. Bader, Ed. Boca Raton, FL: Chapman and Hall/CRC, 2007, ch. 12, pp. 237--262.
2. D. A. Bader, K. Madduri, G. Cong, and J. Feo, “Design of multithreaded algorithms for combinatorial problems,” in Handbook of Parallel Computing: Models, Algorithms, and Applications, S. Rajasekaran and J. Reif, Eds. Boca Raton, FL: Chapman and Hall/CRC, 2007, ch. 31, pp. 1--29.
3. K. Subramani and K. Madduri, “Accomplishing Approximate FCFS fairness without queues,” in Proc. 14th Int'l. Conf. on High Performance Computing (HiPC), ser. LNCS, S. Aluru, M. Parashar, R. Badrinath, and V. K. Prasanna, Eds., vol. 4873. Springer, Dec. 2007, pp. 540--551.
4. D. A. Bader, S. Kintali, K. Madduri, and M. Mihail, “Approximating betweenness centrality,” in Proc. 5th Int'l. Workshop on Algorithms and Models for the Web-Graph (WAW), ser. LNCS, A. Bonato and F. R. K. Chung, Eds., vol. 4863. Springer, Dec. 2007, pp. 124--137.
5. D. A. Bader, V. Agarwal, K. Madduri, and S. Kang, “High performance combinatorial algorithm design on the Cell Broadband Engine processor,” Parallel Computing, vol. 33, no. 10-11, pp. 720--740, 2007.
6. D. A. Bader and K. Madduri, “High-performance combinatorial techniques for analyzing massive dynamic interaction networks,” DIMACS/DyDAn Workshop on Computational Methods for Dynamic Interaction Networks, Sep. 2007.
7. J. R. Crobak, J. Berry, K. Madduri, and D. A. Bader, “Advanced shortest paths algorithms on a massively-multithreaded architecture,” in Proc. 1st Workshop on Multithreaded Architectures and Applications (MTAAP). IEEE, Mar. 2007.
8. D. A. Bader, V. Kanade, and K. Madduri, “SWARM: A parallel programming framework for multicore processors,” in Proc. 1st Workshop on Multithreaded Architectures and Applications (MTAAP). IEEE, Mar. 2007.
9. D. A. Bader, V. Agarwal, and K. Madduri, “On the design and analysis of irregular algorithms on the Cell processor: A case study of list ranking,” in Proc. 21st IEEE Int'l. Parallel and Distributed Processing Symposium (IPDPS). IEEE, Mar. 2007.
10. D. A. Bader and K. Madduri, “A graph-theoretic analysis of the human protein-interaction network using multi-core parallel algorithms,” in Proc. 6th IEEE Int'l. Workshop on High-Performance Computational Biology (HiCOMB). IEEE, Mar. 2007.
11. K. Madduri, D. A. Bader, J. W. Berry, and J. R. Crobak, “An experimental study of a parallel shortest path algorithm for solving large-scale graph instances,” in Proc. 9th Workshop on Algorithm Engineering and Experiments (ALENEX). SIAM, Jan. 2007.

2006

1. K. Madduri, D. A. Bader, J. W. Berry, and J. R. Crobak, “Parallel shortest path algorithms for solving large-scale instances,” 9th DIMACS Implementation Challenge workshop (The Shortest Path Problem), Nov. 2006.
2. D. A. Bader and K. Madduri, “Parallel algorithms for evaluating centrality indices in real-world networks,” in Proc. 35th Int'l. Conf. on Parallel Processing (ICPP). IEEE Computer Society, Aug. 2006, pp. 539--550.
3. D. A. Bader and K. Madduri, “Designing multithreaded algorithms for breadth-first search and st-connectivity on the Cray MTA-2,” in Proc. 35th Int'l. Conf. on Parallel Processing (ICPP). IEEE Computer Society, Aug. 2006, pp. 523--530.
4. D. A. Bader and K. Madduri, “Efficient shared-memory algorithms and implementations for solving large-scale graph problems,” SIAM Annual Meeting, Jul. 2006.
5. D. A. Bader, K. Madduri, J. R. Gilbert, V. Shah, J. Kepner, T. Meuse, and A. Krishnamurthy, “Designing Scalable Synthetic Compact Applications for Benchmarking High Productivity Computing Systems,” CTWatch Quarterly, vol. 2, no. 4B, pp. 41--51, 2006.

2005

1. D. A. Bader and K. Madduri, “Design and implementation of the HPCS graph analysis benchmark on symmetric multiprocessors,” in Proc. 12th Int'l. Conf. on High Performance Computing (HiPC), ser. LNCS, D. A. Bader, M. Parashar, S. Varadarajan, and V. K. Prasanna, Eds., vol. 3769. Springer, Dec. 2005, pp. 465--476.

2004

1. D. A. Bader and K. Madduri, “A parallel state assignment algorithm for finite state machines,” in Proc. 11th Int'l. Conf. on High Performance Computing (HiPC), ser. LNCS, L. Bougé and V. K. Prasanna, Eds., vol. 3296. Springer, Dec. 2004, pp. 297--308.
2. K. Madduri, K. H. Aparna, and V. S. Chakravarthy, “PATRAM: A handwritten word processor for Indian languages,” in Proc. 9th Int'l. Workshop on Frontiers in Handwriting Recognition (IWFHR). IEEE Computer Society, Aug. 2004, pp. 557--562.