Applications of linear algebra in information retrieval and hypertext analysis
PODS '99 Proceedings of the eighteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Multi-fidelity algorithms for interactive mobile applications
DIALM '99 Proceedings of the 3rd international workshop on Discrete algorithms and methods for mobile computing and communications
Clustering in large graphs and matrices
Proceedings of the tenth annual ACM-SIAM symposium on Discrete algorithms
Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
SODA '01 Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms
Fast computation of low rank matrix approximations
STOC '01 Proceedings of the thirty-third annual ACM symposium on Theory of computing
Polynomial-time approximation schemes for geometric min-sum median clustering
Journal of the ACM (JACM)
Multi-fidelity algorithms for interactive mobile applications
Wireless Networks
Competitive recommendation systems
STOC '02 Proceedings of the thiry-fourth annual ACM symposium on Theory of computing
Near-optimal sparse fourier representations via sampling
STOC '02 Proceedings of the thiry-fourth annual ACM symposium on Theory of computing
Methods for binary multidimensional scaling
Neural Computation
Property testing of data dimensionality
SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
Pass efficient algorithms for approximating large matrices
SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
Approximating the Minimum Spanning Tree Weight in Sublinear Time
ICALP '01 Proceedings of the 28th International Colloquium on Automata, Languages and Programming,
Greedy approximation algorithms for finding dense components in a graph
APPROX '00 Proceedings of the Third International Workshop on Approximation Algorithms for Combinatorial Optimization
Clustering Data Streams: Theory and Practice
IEEE Transactions on Knowledge and Data Engineering
Sampling lower bounds via information theory
Proceedings of the thirty-fifth annual ACM symposium on Theory of computing
Correlating synchronous and asynchronous data streams
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Spectral Grouping Using the Nyström Method
IEEE Transactions on Pattern Analysis and Machine Intelligence
On clusterings: Good, bad and spectral
Journal of the ACM (JACM)
STOC '04 Proceedings of the thirty-sixth annual ACM symposium on Theory of computing
Estimating the weight of metric minimum spanning trees in sublinear-time
STOC '04 Proceedings of the thirty-sixth annual ACM symposium on Theory of computing
Clustering Large Graphs via the Singular Value Decomposition
Machine Learning
GPCA: an efficient dimension reduction scheme for image compression and retrieval
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Generalized low rank approximations of matrices
ICML '04 Proceedings of the twenty-first international conference on Machine learning
A spectral algorithm for learning mixture models
Journal of Computer and System Sciences - Special issue on FOCS 2002
Fast monte-carlo algorithms for finding low-rank approximations
Journal of the ACM (JACM)
Proto-value functions: developmental reinforcement learning
ICML '05 Proceedings of the 22nd international conference on Machine learning
Generalized Low Rank Approximations of Matrices
Machine Learning
Sampling algorithms for l2 regression and applications
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
Mining web navigations for intelligence
Decision Support Systems - Special issue: Intelligence and security informatics
On the Nyström Method for Approximating a Gram Matrix for Improved Kernel-Based Learning
The Journal of Machine Learning Research
Sampling-based dimension reduction for subspace approximation
Proceedings of the thirty-ninth annual ACM symposium on Theory of computing
Fast dimension reduction using Rademacher series on dual BCH codes
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
Spectral clustering in telephone call graphs
Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis
Sampling subproblems of heterogeneous Max-Cut problems and approximation algorithms
Random Structures & Algorithms
Improved Nyström low-rank approximation and error analysis
Proceedings of the 25th international conference on Machine learning
Unsupervised feature selection for principal components analysis
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Summarizing spatial data streams using ClusterHulls
Journal of Experimental Algorithmics (JEA)
Bound for the L2 Norm of Random Matrix and Succinct Matrix Approximation
ICCS '08 Proceedings of the 8th international conference on Computational Science, Part II
Dense Fast Random Projections and Lean Walsh Transforms
APPROX '08 / RANDOM '08 Proceedings of the 11th international workshop, APPROX 2008, and 12th international workshop, RANDOM 2008 on Approximation, Randomization and Combinatorial Optimization: Algorithms and Techniques
Clustered subset selection and its applications on it service metrics
Proceedings of the 17th ACM conference on Information and knowledge management
An improved approximation algorithm for the column subset selection problem
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
Spectral Clustering in Social Networks
Advances in Web Mining and Web Usage Analysis
On sampling-based approximate spectral decomposition
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Learning Representation and Control in Markov Decision Processes: New Frontiers
Foundations and Trends® in Machine Learning
Towards a Study of Low-Complexity Graphs
ICALP '09 Proceedings of the 36th International Colloquium on Automata, Languages and Programming: Part I
Learning representation and control in continuous Markov decision processes
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Samuel meets Amarel: automating value function approximation using global state space analysis
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 2
Foundations and Trends® in Theoretical Computer Science
An experimental evaluation of a Monte-Carlo algorithm for singular value decomposition
PCI'01 Proceedings of the 8th Panhellenic conference on Informatics
Spectral methods for matrices and tensors
Proceedings of the forty-second ACM symposium on Theory of computing
Clustered Nyström method for large scale manifold learning and dimension reduction
IEEE Transactions on Neural Networks
A Randomized Algorithm for Principal Component Analysis
SIAM Journal on Matrix Analysis and Applications
Fast Algorithms for Approximating the Singular Value Decomposition
ACM Transactions on Knowledge Discovery from Data (TKDD)
Efficient combination of probabilistic sampling approximations for robust image segmentation
DAGM'06 Proceedings of the 28th conference on Pattern Recognition
Approximating a gram matrix for improved kernel-based learning
COLT'05 Proceedings of the 18th annual conference on Learning Theory
Modified LSI model for efficient search by metric access methods
ECIR'05 Proceedings of the 27th European conference on Advances in Information Retrieval Research
Subspace sampling and relative-error matrix approximation: column-based methods
APPROX'06/RANDOM'06 Proceedings of the 9th international conference on Approximation Algorithms for Combinatorial Optimization Problems, and 10th international conference on Randomization and Computation
Sampling methods for the Nyström method
The Journal of Machine Learning Research
Simple and deterministic matrix sketching
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Large-scale SVD and manifold learning
The Journal of Machine Learning Research
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In several applications, the data consists of an m X n matrix A and it is of interest to find an approximation $\DD$ of a specified rank k to A where, k is much smaller than m and n. Traditional methods like the Singular Value Decomposition (SVD) help us find the ``best'' such approximation. However, these methods take time polynomial in m and n which is often too prohibitive.In this paper, we develop an algorithm which is qualitatively faster, provided we may sample the entries of the matrix according to a natural probability distribution. Indeed, in the applications such sampling is possible.