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Amit Deshpande: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Amit Deshpande, Santosh Vempala
    Adaptive Sampling and Fast Low-Rank Matrix Approximation. [Citation Graph (0, 0)][DBLP]
    APPROX-RANDOM, 2006, pp:292-303 [Conf]
  2. Amit Deshpande, Rahul Jain, Telikepalli Kavitha, Jaikumar Radhakrishnan, Satyanarayana V. Lokam
    Better Lower Bounds for Locally Decodable Codes. [Citation Graph (0, 0)][DBLP]
    IEEE Conference on Computational Complexity, 2002, pp:184-193 [Conf]
  3. Amit Deshpande, Daniel A. Spielman
    Improved Smoothed Analysis of the Shadow Vertex Simplex Method. [Citation Graph (0, 0)][DBLP]
    FOCS, 2005, pp:349-356 [Conf]
  4. S. A. M. Makki, Niki Pissinou, Tirthankar Ghosh, Amit Deshpande
    Study of Network Performance in a Simulated Network for Optimized Node Degree and Network Cost. [Citation Graph (0, 0)][DBLP]
    International Conference on Internet Computing, 2003, pp:747-752 [Conf]
  5. Amit Deshpande, Luis Rademacher, Santosh Vempala, Grant Wang
    Matrix approximation and projective clustering via volume sampling. [Citation Graph (0, 0)][DBLP]
    SODA, 2006, pp:1117-1126 [Conf]
  6. Amit Deshpande, Rahul Jain, Telikepalli Kavitha, Satyanarayana V. Lokam, Jaikumar Radhakrishnan
    Lower bounds for adaptive locally decodable codes. [Citation Graph (0, 0)][DBLP]
    Random Struct. Algorithms, 2005, v:27, n:3, pp:358-378 [Journal]
  7. Amit Deshpande, Kasturi R. Varadarajan
    Sampling-based dimension reduction for subspace approximation. [Citation Graph (0, 0)][DBLP]
    STOC, 2007, pp:641-650 [Conf]

  8. Sampling s-Concave Functions: The Limit of Convexity Based Isoperimetry. [Citation Graph (, )][DBLP]

  9. Adaptive Sampling for k-Means Clustering. [Citation Graph (, )][DBLP]

  10. Finding Dense Subgraphs in G(n, 1/2). [Citation Graph (, )][DBLP]

  11. Finding Dense Subgraphs in G(n,1/2) [Citation Graph (, )][DBLP]

  12. The Limit of Convexity Based Isoperimetry: Sampling Harmonic-Concave Functions [Citation Graph (, )][DBLP]

  13. Algorithms and Hardness for Subspace Approximation [Citation Graph (, )][DBLP]

  14. Efficient volume sampling for row/column subset selection [Citation Graph (, )][DBLP]

  15. Adaptive Sampling and Fast Low-Rank Matrix Approximation. [Citation Graph (, )][DBLP]

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