Sparse graph codes for compression, sensing, and secrecy
暂无分享,去创建一个
[1] Yevgeniy Dodis,et al. Non-malleable extractors and symmetric key cryptography from weak secrets , 2009, STOC '09.
[2] Venkatesan Guruswami,et al. Unbalanced expanders and randomness extractors from Parvaresh--Vardy codes , 2009, JACM.
[3] Andrea Montanari,et al. Counter braids: a novel counter architecture for per-flow measurement , 2008, SIGMETRICS '08.
[4] I. Sergeev,et al. The complexity and depth of Boolean circuits for multiplication and inversion in some fields GF(2n) , 2009 .
[5] Venkatesan Guruswami,et al. Euclidean Sections of with Sublinear Randomness and Error-Correction over the Reals , 2008, APPROX-RANDOM.
[6] A. Lubotzky,et al. Ramanujan graphs , 2017, Comb..
[7] S. Srinivasa Rao,et al. Space Efficient Suffix Trees , 1998, J. Algorithms.
[8] David L Donoho,et al. Compressed sensing , 2006, IEEE Transactions on Information Theory.
[9] T. Etzion,et al. Which codes have cycle-free Tanner graphs? , 1998, Proceedings. 1998 IEEE International Symposium on Information Theory (Cat. No.98CH36252).
[10] Daniel A. Spielman,et al. Linear-time encodable and decodable error-correcting codes , 1995, STOC '95.
[11] Weiyu Xu,et al. Efficient Compressive Sensing with Deterministic Guarantees Using Expander Graphs , 2007, 2007 IEEE Information Theory Workshop.
[12] A. D. Wyner,et al. The wire-tap channel , 1975, The Bell System Technical Journal.
[13] Andrea Montanari,et al. Message passing algorithms for compressed sensing: II. analysis and validation , 2009, 2010 IEEE Information Theory Workshop on Information Theory (ITW 2010, Cairo).
[14] Rüdiger L. Urbanke,et al. Efficient encoding of low-density parity-check codes , 2001, IEEE Trans. Inf. Theory.
[15] Vivek K. Goyal,et al. Malleable Coding: Compressed Palimpsests , 2008, ArXiv.
[16] Jon Feldman,et al. Decoding error-correcting codes via linear programming , 2003 .
[17] Graham Cormode,et al. Combinatorial Algorithms for Compressed Sensing , 2006 .
[18] Silvio Micali,et al. Probabilistic encryption & how to play mental poker keeping secret all partial information , 1982, STOC '82.
[19] David Zuckerman,et al. DETERMINISTIC EXTRACTORS FOR BIT-FIXING SOURCES AND EXPOSURE-RESILIENT CRYPTOGRAPHY , 2003 .
[20] Moses Charikar,et al. Finding frequent items in data streams , 2004, Theor. Comput. Sci..
[21] Alexandros G. Dimakis,et al. Sparse Recovery of Nonnegative Signals With Minimal Expansion , 2011, IEEE Transactions on Signal Processing.
[22] Andrea Montanari,et al. Smooth compression, Gallager bound and nonlinear sparse-graph codes , 2008, 2008 IEEE International Symposium on Information Theory.
[23] Venkatesan Guruswami,et al. Explicit interleavers for a Repeat Accumulate Accumulate (RAA) code construction , 2008, 2008 IEEE International Symposium on Information Theory.
[24] Noga Alon,et al. The Probabilistic Method , 2015, Fundamentals of Ramsey Theory.
[25] C. SIAMJ.. LOW REDUNDANCY IN STATIC DICTIONARIES WITH CONSTANT QUERY TIME , 2001 .
[26] Martin J. Wainwright,et al. LP Decoding Corrects a Constant Fraction of Errors , 2004, IEEE Transactions on Information Theory.
[27] Graham Cormode,et al. An Improved Data Stream Summary: The Count-Min Sketch and Its Applications , 2004, LATIN.
[28] P. Indyk. 895 : Sketching , Streaming and Sub-linear Space Algorithms , 2008 .
[29] Rüdiger L. Urbanke,et al. The capacity of low-density parity-check codes under message-passing decoding , 2001, IEEE Trans. Inf. Theory.
[30] P. Vontobel,et al. Constructions of LDPC Codes using Ramanujan Graphs and Ideas from Margulis , 2000 .
[31] R. Vershynin,et al. One sketch for all: fast algorithms for compressed sensing , 2007, STOC '07.
[32] G. Forney,et al. Codes on graphs: normal realizations , 2000, 2000 IEEE International Symposium on Information Theory (Cat. No.00CH37060).
[33] Alexandros G. Dimakis,et al. Sparse Recovery of Positive Signals with Minimal Expansion , 2009, ArXiv.
[34] Thomas J. Richardson,et al. An Introduction to the Analysis of Iterative Coding Systems , 2001 .
[35] Oded Goldreich,et al. The bit extraction problem or t-resilient functions , 1985, 26th Annual Symposium on Foundations of Computer Science (sfcs 1985).
[36] S. Muthukrishnan,et al. Data streams: algorithms and applications , 2005, SODA '03.
[37] Thomas M. Cover,et al. Elements of Information Theory , 2005 .
[38] Eli Ben-Sasson,et al. Affine dispersers from subspace polynomials , 2009, STOC '09.
[39] Imre Csiszár,et al. Broadcast channels with confidential messages , 1978, IEEE Trans. Inf. Theory.
[40] Simon Litsyn,et al. On ensembles of low-density parity-check codes: Asymptotic distance distributions , 2002, IEEE Trans. Inf. Theory.
[41] Robert G. Gallager,et al. Low-density parity-check codes , 1962, IRE Trans. Inf. Theory.
[42] Mohammad Mahdian,et al. The Minimum Distance of Turbo-Like Codes , 2009, IEEE Transactions on Information Theory.
[43] Michael Luby,et al. LT codes , 2002, The 43rd Annual IEEE Symposium on Foundations of Computer Science, 2002. Proceedings..
[44] David R. Clark,et al. Efficient suffix trees on secondary storage , 1996, SODA '96.
[45] Piotr Indyk,et al. Sparse Recovery Using Sparse Random Matrices , 2010, LATIN.
[46] D.J.C. MacKay,et al. Good error-correcting codes based on very sparse matrices , 1997, Proceedings of IEEE International Symposium on Information Theory.
[47] Burton H. Bloom,et al. Space/time trade-offs in hash coding with allowable errors , 1970, CACM.
[48] Thomas M. Cover,et al. Enumerative source encoding , 1973, IEEE Trans. Inf. Theory.
[49] Elwyn R. Berlekamp,et al. On the inherent intractability of certain coding problems (Corresp.) , 1978, IEEE Trans. Inf. Theory.
[50] Aaron D. Wyner,et al. Coding Theorems for a Discrete Source With a Fidelity CriterionInstitute of Radio Engineers, International Convention Record, vol. 7, 1959. , 1993 .
[51] Joel A. Tropp,et al. Greed is good: algorithmic results for sparse approximation , 2004, IEEE Transactions on Information Theory.
[52] Daniel A. Spielman,et al. Efficient erasure correcting codes , 2001, IEEE Trans. Inf. Theory.
[53] Rüdiger L. Urbanke,et al. Parity-check density versus performance of binary linear block codes over memoryless symmetric channels , 2003, IEEE Transactions on Information Theory.
[54] János Komlós,et al. Storing a sparse table with O(1) worst case access time , 1982, 23rd Annual Symposium on Foundations of Computer Science (sfcs 1982).
[55] Dariush Divsalar,et al. Coding theorems for 'turbo-like' codes , 1998 .
[56] Claude E. Shannon,et al. Communication theory of secrecy systems , 1949, Bell Syst. Tech. J..
[57] Rüdiger L. Urbanke,et al. Modern Coding Theory , 2008 .
[58] Sergey Yekhanin,et al. Secure Biometrics Via Syndromes , 2005 .
[59] Andrea Montanari,et al. Message passing algorithms for compressed sensing: I. motivation and construction , 2009, 2010 IEEE Information Theory Workshop on Information Theory (ITW 2010, Cairo).
[60] H. Yamamoto,et al. A coding theorem for lossy data compression by LDPC codes , 2002, Proceedings IEEE International Symposium on Information Theory,.
[61] Guy Kindler,et al. Simulating independence: new constructions of condensers, ramsey graphs, dispersers, and extractors , 2005, STOC '05.
[62] Alexander Barg,et al. Complexity Issues in Coding Theory , 1997, Electron. Colloquium Comput. Complex..
[63] Abraham Lempel,et al. A universal algorithm for sequential data compression , 1977, IEEE Trans. Inf. Theory.
[64] Robert J. McEliece,et al. The generalized distributive law , 2000, IEEE Trans. Inf. Theory.
[65] Leonid A. Levin,et al. Pseudo-random generation from one-way functions , 1989, STOC '89.
[66] Peter Elias,et al. Universal codeword sets and representations of the integers , 1975, IEEE Trans. Inf. Theory.
[67] G. Hardy,et al. An Introduction to the Theory of Numbers , 1938 .
[68] Avi Wigderson,et al. Randomness conductors and constant-degree lossless expanders , 2002, Proceedings 17th IEEE Annual Conference on Computational Complexity.
[69] Rüdiger L. Urbanke,et al. Design of capacity-approaching irregular low-density parity-check codes , 2001, IEEE Trans. Inf. Theory.
[70] Noga Alon,et al. Explicit unique-neighbor expanders , 2002, The 43rd Annual IEEE Symposium on Foundations of Computer Science, 2002. Proceedings..
[71] Achilleas Anastasopoulos,et al. Capacity-Achieving Codes with Bounded Graphical Complexity on Noisy Channels , 2005, ArXiv.
[72] A. Glavieux,et al. Near Shannon limit error-correcting coding and decoding: Turbo-codes. 1 , 1993, Proceedings of ICC '93 - IEEE International Conference on Communications.
[73] Rajeev Motwani,et al. Randomized algorithms , 1996, CSUR.
[74] X. Jin. Factor graphs and the Sum-Product Algorithm , 2002 .
[75] Imre Csiszár,et al. Information Theory - Coding Theorems for Discrete Memoryless Systems, Second Edition , 2011 .
[76] S. Srinivasa Rao,et al. An optimal Bloom filter replacement , 2005, SODA '05.
[77] Martin J. Wainwright,et al. Lossy source encoding via message-passing and decimation over generalized codewords of LDGM codes , 2005, Proceedings. International Symposium on Information Theory, 2005. ISIT 2005..
[78] David Burshtein,et al. Expander graph arguments for message-passing algorithms , 2001, IEEE Trans. Inf. Theory.
[79] L. H. Harper. Optimal numberings and isoperimetric problems on graphs , 1966 .
[80] Piotr Indyk,et al. Combining geometry and combinatorics: A unified approach to sparse signal recovery , 2008, 2008 46th Annual Allerton Conference on Communication, Control, and Computing.
[81] Ueli Maurer,et al. Information-Theoretic Key Agreement: From Weak to Strong Secrecy for Free , 2000, EUROCRYPT.
[82] Sae-Young Chung,et al. On the design of low-density parity-check codes within 0.0045 dB of the Shannon limit , 2001, IEEE Communications Letters.
[83] Guy Jacobson,et al. Space-efficient static trees and graphs , 1989, 30th Annual Symposium on Foundations of Computer Science.
[84] Hui Jin,et al. Irregular Repeat – Accumulate Codes 1 , 2000 .
[85] Rüdiger L. Urbanke,et al. Polar Codes for Channel and Source Coding , 2009, ArXiv.
[86] N. Linial,et al. Expander Graphs and their Applications , 2006 .
[87] Rajeev Raman,et al. On the Redundancy of Succinct Data Structures , 2008, SWAT.
[88] Sang Joon Kim,et al. A Mathematical Theory of Communication , 2006 .
[89] Amin Shokrollahi,et al. LDPC Codes: An Introduction , 2004 .
[90] Igal Sason,et al. Accumulate-Repeat-Accumulate Codes: Systematic Codes Achieving the Binary Erasure Channel Capacity with Bounded Complexity , 2005, ArXiv.
[91] Борис Сергеевич Кашин,et al. Замечание о задаче сжатого измерения@@@A Remark on Compressed Sensing , 2007 .
[92] D. Spielman,et al. Expander codes , 1996 .
[93] Rasmus Pagh,et al. Cuckoo Hashing , 2001, Encyclopedia of Algorithms.
[94] Emmanuel J. Candès,et al. Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information , 2004, IEEE Transactions on Information Theory.
[95] Rajeev Raman,et al. Succinct indexable dictionaries with applications to encoding k-ary trees and multisets , 2002, SODA '02.
[96] Piotr Indyk. Explicit constructions for compressed sensing of sparse signals , 2008, SODA '08.
[97] Enkatesan G Uruswami. Unbalanced expanders and randomness extractors from Parvaresh-Vardy codes , 2008 .
[98] Larry Carter,et al. Exact and approximate membership testers , 1978, STOC.
[99] Deanna Needell,et al. CoSaMP: Iterative signal recovery from incomplete and inaccurate samples , 2008, ArXiv.
[100] John L. Smith. Tables , 1969, Neuromuscular Disorders.
[101] Emmanuel J. Candès,et al. Decoding by linear programming , 2005, IEEE Transactions on Information Theory.
[102] E. Candès,et al. Stable signal recovery from incomplete and inaccurate measurements , 2005, math/0503066.
[103] Piotr Indyk,et al. Sequential Sparse Matching Pursuit , 2009, 2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton).
[104] Michael I. Jordan,et al. Graphical Models, Exponential Families, and Variational Inference , 2008, Found. Trends Mach. Learn..
[105] Michael Lentmaier,et al. An analysis of the block error probability performance of iterative decoding , 2005, IEEE Transactions on Information Theory.
[106] Zvi Galil,et al. Explicit Constructions of Linear-Sized Superconcentrators , 1981, J. Comput. Syst. Sci..
[107] Amin Shokrollahi,et al. Capacity-achieving sequences for the erasure channel , 2002, IEEE Trans. Inf. Theory.
[108] Ronald A. DeVore,et al. Deterministic constructions of compressed sensing matrices , 2007, J. Complex..
[109] Graham Cormode,et al. An improved data stream summary: the count-min sketch and its applications , 2004, J. Algorithms.
[110] R. DeVore,et al. A Simple Proof of the Restricted Isometry Property for Random Matrices , 2008 .
[111] P. Indyk,et al. Near-Optimal Sparse Recovery in the L1 Norm , 2008, 2008 49th Annual IEEE Symposium on Foundations of Computer Science.
[112] Emin Martinian,et al. Iterative Quantization Using Codes On Graphs , 2004, ArXiv.
[113] H. Vincent Poor,et al. Secure Nested Codes for Type II Wiretap Channels , 2007, 2007 IEEE Information Theory Workshop.
[114] Martin J. Wainwright,et al. Low density codes achieve the rate-distortion bound , 2006, Data Compression Conference (DCC'06).
[115] Joel A. Tropp,et al. Algorithmic linear dimension reduction in the l_1 norm for sparse vectors , 2006, ArXiv.
[116] Rajeev Raman,et al. On the Size of Succinct Indices , 2007, ESA.
[117] Shlomo Shamai,et al. Compound Wiretap Channels , 2009, EURASIP J. Wirel. Commun. Netw..
[118] A. Robert Calderbank,et al. Applications of LDPC Codes to the Wiretap Channel , 2004, IEEE Transactions on Information Theory.
[119] Rüdiger L. Urbanke,et al. Capacity-achieving ensembles for the binary erasure channel with bounded complexity , 2004, International Symposium onInformation Theory, 2004. ISIT 2004. Proceedings..
[120] S. Muthukrishnan. Some Algorithmic Problems and Results in Compressed Sensing , 2006 .
[121] Yevgeniy Dodis,et al. Correcting errors without leaking partial information , 2005, STOC '05.