Improving random projections using marginal information

Authors:
Ping Li;Trevor J. Hastie;Kenneth W. Church
Affiliations:
Department of Statistics, Stanford University, Stanford, CA;Department of Statistics, Stanford University, Stanford, CA;Microsoft Research, Redmond, WA
Venue:
COLT'06 Proceedings of the 19th annual conference on Learning Theory
Year:
2006

Citing 11
Cited 10

Latent semantic indexing: a probabilistic analysis

PODS '98 Proceedings of the seventeenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Approximate nearest neighbors: towards removing the curse of dimensionality

STOC '98 Proceedings of the thirtieth annual ACM symposium on Theory of computing
Random projection in dimensionality reduction: applications to image and text data

Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Similarity estimation techniques from rounding algorithms

STOC '02 Proceedings of the thiry-fourth annual ACM symposium on Theory of computing
Learning Mixtures of Gaussians

FOCS '99 Proceedings of the 40th Annual Symposium on Foundations of Computer Science
An Algorithmic Theory of Learning: Robust Concepts and Random Projection

FOCS '99 Proceedings of the 40th Annual Symposium on Foundations of Computer Science
Database-friendly random projections: Johnson-Lindenstrauss with binary coins

Journal of Computer and System Sciences - Special issu on PODS 2001
Experiments with random projections for machine learning

Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Random Projection-Based Multiplicative Data Perturbation for Privacy Preserving Distributed Data Mining

IEEE Transactions on Knowledge and Data Engineering
Randomized algorithms and NLP: using locality sensitive hash function for high speed noun clustering

ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
On the distribution of SINR for the MMSE MIMO receiver and performance analysis

IEEE Transactions on Information Theory

Very sparse random projections

Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Very sparse stable random projections for dimension reduction in lα (0

Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
A Sketch Algorithm for Estimating Two-Way and Multi-Way Associations

Computational Linguistics
Estimators and tail bounds for dimension reduction in lα (0

Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
On low dimensional random projections and similarity search

Proceedings of the 17th ACM conference on Information and knowledge management
Beta Random Projection

Bio-Inspired Computing and Communication
A pioneering cryptic random projection based approach for privacy preserving data mining

IRI'09 Proceedings of the 10th IEEE international conference on Information Reuse & Integration
Nonlinear estimators and tail bounds for dimension reduction in l1 using Cauchy random projections

COLT'07 Proceedings of the 20th annual conference on Learning theory
Theory and applications of b-bit minwise hashing

Communications of the ACM
Fast near neighbor search in high-dimensional binary data

ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part I

Quantified Score

Hi-index	0.02

Visualization

Abstract

We present an improved version of random projections that takes advantage of marginal norms. Using a maximum likelihood estimator (MLE), margin-constrained random projections can improve estimation accuracy considerably. Theoretical properties of this estimator are analyzed in detail.