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Displaying 1-50 out of 80 total
Message from the workshop chairs
Found in: Parallel and Distributed Processing Workshops and PhD Forum, 2011 IEEE International Symposium on
By George Karypis,Srinivas Aluru,David A. Bader
Issue Date:April 2010
pp. 1-2
Welcome to the 9th International Workshop on High Performance Computational Biology (HiCOMB). Computational Biology and related disciplines are fast emerging as an important area for academic research and industrial application. The large size of biologica...
 
Highly Scalable Parallel Algorithms for Sparse Matrix Factorization
Found in: IEEE Transactions on Parallel and Distributed Systems
By Anshul Gupta, George Karypis, Vipin Kumar
Issue Date:May 1997
pp. 502-520
<p><b>Abstract</b>—In this paper, we describe scalable parallel algorithms for symmetric sparse matrix factorization, analyze their performance and scalability, and present experimental results for up to 1,024 processors on a Cray T3D par...
 
Frequent Sub-Structure-Based Approaches for Classifying Chemical Compounds
Found in: Data Mining, IEEE International Conference on
By Mukund Deshpande, Michihiro Kuramochi, George Karypis
Issue Date:November 2003
pp. 35
In this paper we study the problem of classifying chemical compound datasets. We present a sub-structure-based classification algorithm that decouples the sub-structure discovery process from the classification model construction and uses frequent subgraph...
 
Parallel Multilevel k-way Partitioning Scheme for Irregular Graphs
Found in: SC Conference
By George Karypis, Vipin Kumar
Issue Date:January 1996
pp. 35
In this paper we present a parallel formulation of a multilevel k-way graph partitioning algorithm. The multilevel k-way partitioning algorithm reduces the size of the graph by collapsing vertices and edges (coarsening phase), finds a k-way partition of th...
 
Multilevel Algorithms for Generating Coarse Grids for Multigrid Methods
Found in: SC Conference
By Irene Moulitsas, George Karypis
Issue Date:November 2001
pp. 15
Geometric Multigrid methods have gained widespread acceptance for solving large systems of linear equations, especially for structured grids. One of the challenges in successfully extending these methods to unstructured grids is the problem of generating a...
 
Analysis of Multilevel Graph Partitioning
Found in: SC Conference
By George Karypis, Vipin Kumar
Issue Date:December 1995
pp. 29
Recently, a number of researchers have investigated a class of algorithms that are based on multilevel graph partitioning that have moderate computational complexity, and provide excellent graph partitions. However, there exists little theoretical analysis...
 
Genome Alignments Using MPI-LAGAN
Found in: Bioinformatics and Biomedicine, IEEE International Conference on
By Ruinan Zhang, Huzefa Rangwala, George Karypis
Issue Date:November 2008
pp. 437-440
We develop a parallel algorithm for a widely used whole genome alignment method called LAGAN. We use the MPI-based protocol to develop parallel solutions for two phases of the algorithm which take up a significant portion of the total runtime, and also hav...
 
Multi-Constraint Mesh Partitioning for Contact/Impact Computations
Found in: SC Conference
By George Karypis
Issue Date:November 2003
pp. 56
We present a novel approach for decomposing contact/impact computations in which the mesh elements come in contact with each other during the course of the simulation. Effective decomposition of these computations poses a number of challenges as it needs t...
 
Dynamic Repartitioning of Adaptively Refined Meshes
Found in: SC Conference
By Kirk Schloegel, George Karypis, Vipin Kumar
Issue Date:November 1998
pp. 29
One ingredient which is viewed as vital to the successful conduct of many large-scale numerical simulations is the ability to dynamically repartition the underlying adaptive finite element mesh among the processors so that the computations are balanced and...
 
Parallel Threshold-based ILU Factorization
Found in: SC Conference
By George Karypis, Vipin Kumar
Issue Date:November 1997
pp. 28
Factorization algorithms based on threshold incomplete LU factorization have been found to be quite effective in preconditioning iterative system solvers. However, because these factorizations allow the fill elements to be created dynamically, they have be...
 
Parallel Multilevel Graph Partitioning
Found in: Parallel Processing Symposium, International
By George Karypis, Vipin Kumar
Issue Date:April 1996
pp. 314
In this paper we present a parallel formulation of a graph partitioning and sparse matrix ordering algorithm that is based on a multilevel algorithm we developed recently. Our parallel algorithm achieves a speedup of up to 56 on a 128-processor Cray T3D fo...
 
A Versatile Graph-Based Approach to Package Recommendation
Found in: 2013 IEEE 25th International Conference on Tools with Artificial Intelligence (ICTAI)
By Roberto Interdonato,Salvatore Romeo,Andrea Tagarelli,George Karypis
Issue Date:November 2013
pp. 857-864
An emerging trend in research on recommender systems is the design of methods capable of recommending packages instead of single items. The problem is challenging due to a variety of critical aspects, including context-based and user-provided constraints f...
 
Multi-threaded Graph Partitioning
Found in: 2013 IEEE International Symposium on Parallel & Distributed Processing (IPDPS)
By Dominique Lasalle,George Karypis
Issue Date:May 2013
pp. 225-236
In this paper we explore the design space of creating a multi-threaded graph partitioner. We present and compare multiple approaches for parallelizing each of the three phases of multilevel graph partitioning: coarsening, initial partitioning, and uncoarse...
 
Pareto Optimal Pairwise Sequence Alignment
Found in: IEEE/ACM Transactions on Computational Biology and Bioinformatics
By Kevin W. DeRonne,George Karypis
Issue Date:March 2013
pp. 481-493
Sequence alignment using evolutionary profiles is a commonly employed tool when investigating a protein. Many profile-profile scoring functions have been developed for use in such alignments, but there has not yet been a comprehensive study of Pareto optim...
 
Algorithms for Mining the Evolution of Conserved Relational States in Dynamic Networks
Found in: Data Mining, IEEE International Conference on
By Rezwan Ahmed,George Karypis
Issue Date:December 2011
pp. 1-10
Dynamic networks have recently being recognized as a powerful abstraction to model and represent the temporal changes and dynamic aspects of the data underlying many complex systems. Significant insights regarding the stable relational patterns among the e...
 
SLIM: Sparse Linear Methods for Top-N Recommender Systems
Found in: Data Mining, IEEE International Conference on
By Xia Ning,George Karypis
Issue Date:December 2011
pp. 497-506
This paper focuses on developing effective and efficient algorithms for top-N recommender systems. A novel Sparse Linear Method (SLIM) is proposed, which generates top-N recommendations by aggregating from user purchase/rating profiles. A sparse aggregatio...
 
Content-Based Methods for Predicting Web-Site Demographic Attributes
Found in: Data Mining, IEEE International Conference on
By Santosh Kabbur, Eui-Hong Han, George Karypis
Issue Date:December 2010
pp. 863-868
Demographic information plays an important role in gaining valuable insights about a web-site's user-base and is used extensively to target online advertisements and promotions. This paper investigates machine-learning approaches for predicting the demogra...
 
The Set Classification Problem and Solution Methods
Found in: Data Mining Workshops, International Conference on
By Xia Ning, George Karypis
Issue Date:December 2008
pp. 720-729
This paper focuses on developing classification algorithms for problems in which there is a need to predict the class based on multiple observations (examples) of the same phenomenon (class). These problems give rise to a new classification problem, referr...
 
A Multi-Level Parallel Implementation of a Program for Finding Frequent Patterns in a Large Sparse Graph
Found in: Parallel and Distributed Processing Symposium, International
By Steve Reinhardt, George Karypis
Issue Date:March 2007
pp. 214
Graphs capture the essential elements of many problems broadly defined as searching or categorizing. With the rapid increase of data volumes from sensors, many application disciplines need to process larger graphs quickly. This paper presents the results o...
 
Comparison of Descriptor Spaces for Chemical Compound Retrieval and Classification
Found in: Data Mining, IEEE International Conference on
By Nikil Wale, George Karypis
Issue Date:December 2006
pp. 678-689
In recent years the development of computational techniques that build models to correctly assign chemical compounds to various classes or to retrieve potential drug-like compounds has been an active area of research. Many of the best-performing techniques...
 
On Mining Instance-Centric Classification Rules
Found in: IEEE Transactions on Knowledge and Data Engineering
By Jianyong Wang, George Karypis
Issue Date:November 2006
pp. 1497-1511
Many studies have shown that rule-based classifiers perform well in classifying categorical and sparse high-dimensional databases. However, a fundamental limitation with many rule-based classifiers is that they find the rules by employing various heuristic...
 
Frequent Substructure-Based Approaches for Classifying Chemical Compounds
Found in: IEEE Transactions on Knowledge and Data Engineering
By Mukund Deshpande, Michihiro Kuramochi, Nikil Wale, George Karypis
Issue Date:August 2005
pp. 1036-1050
Computational techniques that build models to correctly assign chemical compounds to various classes of interest have many applications in pharmaceutical research and are used extensively at various phases during the drug development process. These techniq...
 
GREW-A Scalable Frequent Subgraph Discovery Algorithm
Found in: Data Mining, IEEE International Conference on
By Michihiro Kuramochi, George Karypis
Issue Date:November 2004
pp. 439-442
Existing algorithms that mine graph datasets to discover patterns corresponding to frequently occurring subgraphs can operate efficiently on graphs that are sparse, contain a large number of relatively small connected components, have vertices with low and...
 
SUMMARY: Efficiently Summarizing Transactions for Clustering
Found in: Data Mining, IEEE International Conference on
By Jianyong Wang, George Karypis
Issue Date:November 2004
pp. 241-248
Frequent itemset mining was initially proposed and has been studied extensively in the context of association rule mining. In recent years, several studies have also extended its application to the transaction (or document) classification and clustering. H...
 
An Efficient Algorithm for Discovering Frequent Subgraphs
Found in: IEEE Transactions on Knowledge and Data Engineering
By Michihiro Kuramochi, George Karypis
Issue Date:September 2004
pp. 1038-1051
Over the years, frequent itemset discovery algorithms have been used to find interesting patterns in various application areas. However, as data mining techniques are being increasingly applied to nontraditional domains, existing frequent pattern discovery...
 
Multi-Resource Aware Partitioning Algorithms for FPGAs with Heterogeneous Resources
Found in: Design Automation Conference
By Navaratnasothie Selvakkumaran, Abhishek Ranjan, Salil Raje, George Karypis
Issue Date:June 2004
pp. 741-746
As FPGA densities increase, partitioning-based FPGA placement approaches are becoming increasingly important as they can be used to provide high-quality and computationally scalable placement solutions. However, modern FPGA architectures incorporate hetero...
 
Multi.Objective Hypergraph Partitioning Algorithms for Cut and Maximum Subdomain Degree Minimization
Found in: Computer-Aided Design, International Conference on
By Navaratnasothie Selvakkumaran, George Karypis
Issue Date:November 2003
pp. 726
In this paper we present a family of multi-objective hypergraph partitioning algorithms based on the multilevel paradigm, which are capable of producing solutions in which both the cut and the maximum subdomain degree are simultaneously minimized. This typ...
 
Prediction of Contact Maps Using Support Vector Machines
Found in: Bioinformatic and Bioengineering, IEEE International Symposium on
By Ying Zhao, George Karypis
Issue Date:March 2003
pp. 26
Contact map prediction is of great interest for its application in fold recognition and protein 3D structure determination. In this paper we present a contact-map prediction algorithm that employs Support Vector Machines as the machine learning tool and in...
 
Discovering Frequent Geometric Subgraphs
Found in: Data Mining, IEEE International Conference on
By Michihiro Kuramochi, George Karypis
Issue Date:December 2002
pp. 258
As data mining techniques are being increasingly applied to non-traditional domains, existing approaches for finding frequent itemsets cannot be used as they cannot model the requirement of these domains. An alternate way of modeling the objects in these d...
 
SLPMiner: An Algorithm for Finding Frequent Sequential Patterns Using Length-Decreasing Support Constraint
Found in: Data Mining, IEEE International Conference on
By Masakazu Seno, George Karypis
Issue Date:December 2002
pp. 418
Over the years, a variety of algorithms for finding frequent sequential patterns in very large sequential databases have been developed. The key feature in most of these algorithms is that they use a constant support constraint to control the inherently ex...
 
Multi-objective circuit partitioning for cutsize and path-based delay minimization
Found in: Computer-Aided Design, International Conference on
By Kia Bazargan, Navaratnasothie Selvakkumaran, George Karypis, Cristinel Ababei
Issue Date:November 2002
pp. 181-185
In this paper we present multi-objective hMetis partitioning for simultaneous cutsize and circuit delay minimization. We change the partitioning process itself by introducing a new objective function that incorporates a truly path-based delay component for...
 
Guest Editor's Introduction: Data Mining
Found in: Computing in Science and Engineering
By George Karypis
Issue Date:July 2002
pp. 12-13
<p>Data mining is the process of automatically extracting new and useful knowledge hidden in large data sets. This emerging discipline is becoming increasingly important as advances in data collection lead to the explosive growth in the amount of ava...
 
Improve Precategorized Collection Retrieval by Using Supervised Term Weighting Schemes
Found in: Information Technology: Coding and Computing, International Conference on
By Ying Zhao, George Karypis
Issue Date:April 2002
pp. 0016
The emergence of the world-wide-web has led to an increased interest in methods for searching for information. A key characteristic of many of the online document collections is that the documents have predefined category information, for example, the vari...
 
A Scalable Algorithm for Clustering Sequential Data
Found in: Data Mining, IEEE International Conference on
By Valerie Guralnik, George Karypis
Issue Date:December 2001
pp. 179
In recent years, we have seen an enormous growth in the amount of available commercial and scientific data. Data from domains such as protein sequences, retail transactions, intrusion detection, and web-logs have an inherent sequential nature. Clustering o...
 
LPMiner: An Algorithm for Finding Frequent Itemsets Using Length-Decreasing Support Constraint
Found in: Data Mining, IEEE International Conference on
By Masakazu Seno, George Karypis
Issue Date:December 2001
pp. 505
Over the years, a variety of algorithms or finding frequent itemsets in very large transaction databases have been developed. The key feature in most to these algorithms is that they use a constant support constraint to control the inherently exponential c...
 
Frequent Subgraph Discovery
Found in: Data Mining, IEEE International Conference on
By Michihiro Kuramochi, George Karypis
Issue Date:December 2001
pp. 313
As data mining techniques are being increasingly applied to non-traditional domains, existing approaches for finding frequent itemsets cannot be used as they cannot model the requirement of these domains. An alternate way of modeling the objects in these d...
 
Privacy Risks in Recommender Systems
Found in: IEEE Internet Computing
By Naren Ramakrishnan, Benjamin J. Keller, Batul J. Mirza, Ananth Y. Grama, George Karypis
Issue Date:November 2001
pp. 54-62
<p>The authors explore the conflict between personalization and privacy that arises from the existence of straddlers - users with eclectic tastes who rates products across several different types or domains -- in recommender systems. While straddlers...
 
Graph Partitioning for Dynamic, Adaptive and Multi-phase Scientific Simulations
Found in: Cluster Computing, IEEE International Conference on
By Kirk Schloegel, George Karypis, Vipin Kumar
Issue Date:October 2001
pp. 271
The efficient execution of scientific simulations on HPC systems requires a partitioning of the underlying mesh among the processors such that the load is balanced and the inter-processor communication is minimized. Graph partitioning algorithms have been ...
 
Wavefront Diffusion and LMSR: Algorithms for Dynamic Repartitioning of Adaptive Meshes
Found in: IEEE Transactions on Parallel and Distributed Systems
By Kirk Schloegel, George Karypis, Vipin Kumar
Issue Date:May 2001
pp. 451-466
<p><b>Abstract</b>—Current multilevel repartitioning schemes tend to perform well on certain types of problems while obtaining worse results for other types of problems. We present two new multilevel algorithms for repartitioning adaptive...
 
Gene Classification Using Expression Profiles: A Feasibility Study
Found in: Bioinformatic and Bioengineering, IEEE International Symposium on
By Michihiro Kuramochi, George Karypis
Issue Date:March 2001
pp. 191
As various genome sequencing projects have already been completed or are near completion, genome researchers are shifting their focus to functional genomics. Functional genomics represents the next phase, that expands the biological investigation to studyi...
 
A Unified Algorithm for Load-balancing Adaptive Scientific Simulations
Found in: SC Conference
By Kirk Schloegel, George Karypis, Vipin Kumar
Issue Date:November 2000
pp. 59
Adaptive scientific simulations require that periodic repartitioning occur dynamically throughout the course of the computation. The repartitionings should be computed so as to minimize both the inter-processor communications incurred during the iterative ...
 
Scalable Parallel Data Mining for Association Rules
Found in: IEEE Transactions on Knowledge and Data Engineering
By Eui-Hong (Sam) Han, George Karypis, Vipin Kumar
Issue Date:May 2000
pp. 337-352
<p><b>Abstract</b>—In this paper, we propose two new parallel formulations of the Apriori algorithm that is used for computing association rules. These new formulations, <it>IDD</it> and <it>HD</it>, address the sh...
 
Load Balancing across Near-Homogeneous Multi-Resource Servers
Found in: Heterogeneous Computing Workshop
By William Leinberger, George Karypis, Vipin Kumar, Rupak Biswas
Issue Date:May 2000
pp. 60
An emerging model for computational grids interconnects similar multi-resource servers from distributed sites. A job submitted to the grid can be executed by any of the servers; however, resource size or balance may be different across servers. One approac...
 
Job Scheduling in the presence of Multiple Resource Requirements
Found in: SC Conference
By William Leinberger, George Karypis, Vipin Kumar
Issue Date:November 1999
pp. 47
In past massively parallel processing systems, such as the Intel Paragon and the Thinking Machines CM-5, the scheduling problem consisted of allocating a single type of resource among the waiting jobs; the processing node. A job was allocated the minimum n...
 
Multi-Capacity Bin Packing Algorithms with Applications to Job Scheduling under Multiple Constraints
Found in: Parallel Processing, International Conference on
By William Leinberger, George Karypis, Vipin Kumar
Issue Date:September 1999
pp. 404
Multi-capacity bin-packing is a generalization of the classical one-dimensional bin-packing problem in which the bin capacity and the item sizes are represented by d-dimensional vectors. Previous work in d-capacity bin-packing algorithms analyzed variants ...
 
Chameleon: Hierarchical Clustering Using Dynamic Modeling
Found in: Computer
By George Karypis, Eui-Hong (Sam) Han, Vipin Kumar
Issue Date:August 1999
pp. 68-75
<p>Many advanced algorithms have difficulty dealing with highly variable clusters that do not follow a preconceived model. By basing its selections on both interconnectivity and closeness, the Chameleon algorithm yields accurate results for these hig...
 
Multilevel k-Way Hypergraph Partitioning
Found in: Design Automation Conference
By George Karypis, Vipin Kumar
Issue Date:June 1999
pp. 343-348
In this paper, we present a new multilevel k-way hypergraph partitioning algorithm that substantially outperforms the existing state-of-the-art K-PM/LR algorithm for multi-way partitioning. both for optimizing local as well as global objectives. Experiment...
 
Multilevel Algorithms for Multi-Constraint Graph Partitioning
Found in: SC Conference
By George Karypis, Vipin Kumar
Issue Date:November 1998
pp. 28
Traditional graph partitioning algorithms compute a k-way partitioning of a graph such that the number of edges that are cut by the partitioning is minimized and each partition has an equal number of vertices. The task of minimizing the edge-cut can be con...
 
Multilevel Hypergraph Partitioning: Application in VLSI Domain
Found in: Design Automation Conference
By George Karypis, Rajat Aggarwal, Vipin Kumar, Shashi Shekhar
Issue Date:June 1997
pp. 526
In this paper, we present a new hypergraph partitioning algorithm that is based on the multilevel paradigm. In the multilevel paradigm, a sequence of successively coarser hypergraphs is constructed. A bisection of the smallest hypergraph is computed and it...
 
L2AP: Fast cosine similarity search with prefix L-2 norm bounds
Found in: 2014 IEEE 30th International Conference on Data Engineering (ICDE)
By David C. Anastasiu,George Karypis
Issue Date:March 2014
pp. 784-795
The All-Pairs similarity search, or self-similarity join problem, finds all pairs of vectors in a high dimensional sparse dataset with a similarity value higher than a given threshold. The problem has been classically solved using a dynamically built inver...
   
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