- Journal of Machine Learning Research 10 (2009) 1913-1936 Submitted 10/08; Revised 3/09; Published 8/09 Learning Approximate Sequential Patterns for Classification
- Sparse recovery using sparse random matrices Radu Berinde
- Sparse Recovery for Earth Mover Distance Rishi Gupta
- Fast Approximate Pattern Matching with Few Indels via Embeddings Mihai Badoiu Piotr Indyk
- Finding Interesting Associations without Support Pruning Edith Cohen \Lambda Mayur Datar y Shinji Fujiwara z Aristides Gionis x Piotr Indyk --
- Embedding Ultrametrics Into LowDimensional Spaces mihai@mit.edu
- Sublinear Time Algorithms for Metric Space Problems piotr indyk \Lambda
- Tree pattern matching and subset matching in deterministic O(n log 3 n)time
- Localitysensitive hashing using stable distributions
- Faster algorithms for string matching problems: matching the convolution bound
- Nearoptimal lineartime codes for unique decoding and new listdecodable codes over smaller alphabets
- Closest Pair Problems in Very High Dimensions Piotr Indyk 1 , Moshe Lewenstein 2 Ohad Lipsky 2 , and Ely Porat 2
- A small approximately minwise independent family of hash functions Piotr Indyk \Lambda
- Approximate Line Nearest Neighbor in High Dimensions Alexandr Andoni
- Efficiently Decodable Codes Meeting GilbertVarshamov Bound for Low Rates
- Uncertainty Principles, Extractors, and Explicit Embeddings of L2 into L1
- Sampling in Dynamic Data Streams and Applications Gereon Frahling #
- Embeddings and Nonapproximability of Geometric Problems Venkatesan Guruswami Piotr Indyk y
- Efficient Regular Data Structures and Algorithms for Location and Proximity Problems
- Approximate Clustering via CoreSets Mihai B adoiu Sariel HarPeled + Piotr Indyk #
- Efficiently Decodable Non-adaptive Group Testing Piotr Indyk
- Lowdistortion Embeddings of General Metrics Into the Julia Chuzhoy
- Algorithmic Applications of Lowdistortion Geometric
- Explicit constructions of selectors and related combinatorial structures, with applications
- Polylogarithmic Private Approximations and Efficient Matching Piotr Indyk
- Optimal Approximations of the Frequency Moments of Data Streams
- Tight Lower Bounds for the Distinct Elements Problem Piotr Indyk
- 1 Introduction Gregory Shakhnarovich, Piotr Indyk, and Trevor Darrell
- On Approximate Nearest Neighbors under l 1 Piotr Indyk \Lambda
- Mining The Stock Market: Which Measure Is Best ? [Extended Abstract]
- Algorithms for Dynamic Geometric Problems over Data Piotr Indyk
- Sparse Recovery Using Sparse Matrices Anna Gilbert, Piotr Indyk
- Near-Optimal Hashing Algorithms for Approximate Nearest Neighbor in High Dimensions
- Sequential Sparse Matching Pursuit Radu Berinde
- Overcoming the 1 Non-Embeddability Barrier: Algorithms for Product Metrics
- 39 NEAREST NEIGHBORS IN HIGH-DIMENSIONAL Piotr Indyk
- 8 LOW-DISTORTION EMBEDDINGS OF FINITE METRIC SPACES
- Near-Optimal Sparse Recovery in the L1 norm Piotr Indyk
- Facility Location in Sublinear Time Mihai Badoiu1
- Compressive Sensing with Local Geometric Features Rishi Gupta
- Lower Bounds for Sparse Recovery Khanh Do Ba
- Space-optimal Heavy Hitters with Strong Error Bounds Radu Berinde
- Earth Mover Distance over High-Dimensional Spaces Alexandr Andoni
- Approximation Algorithms for Embedding General Metrics Into Trees Mihai Badoiu
- On the Optimality of the Dimensionality Reduction Method Alexandr Andoni
- Approximate Nearest Neighbors: Towards Removing the Curse of Dimensionality
- Fast, SmallSpace Algorithms for Approximate Histogram Maintenance
- Motif Discovery in Physiological Datasets: A Methodology for Inferring Predictive
- NearOptimal Sparse Fourier Representations via Sampling [Extended Abstract]
- HIGHDIMENSIONAL COMPUTATIONAL GEOMETRY a dissertation
- Scalable Techniques for Clustering the Web Extended Abstract
- Better Algorithms for High-dimensional Proximity Problems via Asymmetric Embeddings
- Efficient Sketches for Earth-Mover Distance, with Applications Alexandr Andoni
- Algorithmic Applications of Low-distortion Geometric
- Dynamic MultidimensionalHistograms Nitin Thaper
- Approximate Nearest Neighbor Algorithms for Frechet Distance via Product Metrics
- Explicit Constructions for Compressed Sensing of Sparse Signals Piotr Indyk
- Streaming Algorithms for Geometric Problems Piotr Indyk
- Dimensionality Reduction Techniques for Proximity piotr indyk \Lambda
- E#cient Regular Data Structures and Algorithms for Dilation, Location and Proximity Problems
- Stable Distributions, Pseudorandom Generators, Embeddings and Data Stream Computation
- Lower Bounds for Embedding Edit Distance into Normed Spaces ENS, France
- Algorithmic applications of low-distortion geometric embeddings Piotr Indyk
- A Sublinear Time Approximation Scheme for Clustering in Metric Spaces
- Stable Distributions, Pseudorandom Generators, Embeddings, and Data Stream Computation
- Approximate Nearest Neighbor under Edit Distance via Product Piotr Indyk
- K-Median Clustering, Model-Based Compressive Sensing, and Sparse Recovery for Earth Mover Distance
- Practical Near-optimal Sparse Recovery in the L1 Norm R. Berinde, P. Indyk and M. Ruzic
- Approximate (Euclidean)
- Similarity Search in High Dimensions via Hashing Aristides Gionis \Lambda Piotr Indyk y Rajeev Motwani z
- Dimensionality Reduction Techniques for Proximity piotr indyk \Lambda
- Combining geometry and combinatorics: a unified approach to sparse signal R. Berinde, A. C. Gilbert, P. Indyk, H. Karloff, and M. J. Strauss
