Piotr Indyk

Piotr Indyk is Thomas D. and Virginia W. Cabot Professor in the Theory of Computation Group at the Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Provided by Wikipedia
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  1. 21
    Sparse Recovery Using Sparse Matrices

    Sparse Recovery Using Sparse Matrices by Gilbert, Anna, Indyk, Piotr

    Published 2012
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  2. 22
    Almost-Euclidean Subspaces of ℓ1N via Tensor Products: A Simple Approach to Randomness Reduction

    Almost-Euclidean Subspaces of ℓ1N via Tensor Products: A Simple Approach to Randomness Reduction by Indyk, Piotr, Szarek, Stanislaw

    Published 2012
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  3. 23
    On Model-Based RIP-1 Matrices

    On Model-Based RIP-1 Matrices by Indyk, Piotr, Razenshteyn, Ilya

    Published 2014
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  4. 24
    Compressive sensing using locality-preserving matrices

    Compressive sensing using locality-preserving matrices by Grant, Elyot, Indyk, Piotr

    Published 2014
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  5. 25
    Approximate congruence in nearly linear time

    Approximate congruence in nearly linear time by Indyk, Piotr, Venkatasubramanian, Suresh

    Published 2014
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  6. 26
    6.046J Introduction to Algorithms (SMA 5503), Fall 2004

    6.046J Introduction to Algorithms (SMA 5503), Fall 2004 by Leiserson, Charles Eric, Indyk, Piotr

    Published 2004
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  7. 27
    K-median clustering, model-based compressive sensing, and sparse recovery for earth mover distance

    K-median clustering, model-based compressive sensing, and sparse recovery for earth mover distance by Indyk, Piotr, Price, Eric C.

    Published 2012
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  8. 28
    Sparse recovery with partial support knowledge

    Sparse recovery with partial support knowledge by Do Ba, Khanh, Indyk, Piotr

    Published 2012
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  9. 29
    Nearest-neighbor methods in learning and vision : theory and practice /

    Nearest-neighbor methods in learning and vision : theory and practice / by Shakhnarovich, Gregory, Darrell, Trevor, Indyk, Piotr

    Published 2005
  10. 30
    Better approximations for Tree Sparsity in Nearly-Linear Time

    Better approximations for Tree Sparsity in Nearly-Linear Time by Backurs, Arturs, Indyk, Piotr, Schmidt, Ludwig

    Published 2017
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  11. 31
    Nearly Linear-Time Model-Based Compressive Sensing

    Nearly Linear-Time Model-Based Compressive Sensing by Hegde, Chinmay, Indyk, Piotr, Schmidt, Ludwig

    Published 2018
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  12. 32
    Nearly optimal linear embeddings into very low dimensions

    Nearly optimal linear embeddings into very low dimensions by Grant, Elyot, Hegde, Chinmay, Indyk, Piotr

    Published 2018
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  13. 33
    Approximation Algorithms for Model-Based Compressive Sensing

    Approximation Algorithms for Model-Based Compressive Sensing by Hegde, Chinmay, Indyk, Piotr, Schmidt, Ludwig

    Published 2018
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  14. 34
    Approximation-tolerant model-based compressive sensing

    Approximation-tolerant model-based compressive sensing by Hegde, Chinmay, Indyk, Piotr, Schmidt, Ludwig

    Published 2018
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  15. 35
    Practical data-dependent metric compression with provable guarantees

    Practical data-dependent metric compression with provable guarantees by Indyk, Piotr, Razenshteyn, Ilya, Wagner, Tal

    Published 2019
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  16. 36
    Approxiamate Nearest Neighbor Search in High Dimensions

    Approxiamate Nearest Neighbor Search in High Dimensions by Andoni, Alexandr, Indyk, Piotr, Razenshteyn, Ilya

    Published 2021
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  17. 37
    Fast recovery from a union of subspaces

    Fast recovery from a union of subspaces by Hegde, Chinmay, Indyk, Piotr, Schmidt, Ludwig

    Published 2021
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  18. 38
    On the fine-grained complexity of empirical risk minimization: Kernel methods and neural networks

    On the fine-grained complexity of empirical risk minimization: Kernel methods and neural networks by Indyk, Piotr, Schmidt, Ludwig, Backurs, Arturs

    Published 2021
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  19. 39
    On the fine-grained complexity of empirical risk minimization: Kernel methods and neural networks

    On the fine-grained complexity of empirical risk minimization: Kernel methods and neural networks by Indyk, Piotr, Schmidt, Ludwig, Backurs, Arturs

    Published 2021
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  20. 40
    A Constant-Factor Approximation Algorithm for Embedding Unweighted Graphs into Trees

    A Constant-Factor Approximation Algorithm for Embedding Unweighted Graphs into Trees by Badoiu, Mihai, Indyk, Piotr, Sidiropoulos, Anastasios

    Published 2005
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