| |
 |      |
                                               |
Note: Links lead to the DBLP on the Web. Martin Strauss S. Muthukrishnan , Martin Strauss, X. Zheng : Workload-Optimal Histograms on Streams. ESA 2005 : 734-745 A. Robert Calderbank , Anna C. Gilbert , Kirill Levchenko , S. Muthukrishnan , Martin Strauss: Improved range-summable random variable construction algorithms. SODA 2005 : 840-849 Jessica H. Fong , Anna C. Gilbert , Sampath Kannan , Martin J. Strauss: Better Alternatives to OSPF Routing. Algorithmica 43 (1-2): 113-131 (2005) Anna C. Gilbert , Yannis Kotidis , S. Muthukrishnan , Martin Strauss: Domain-Driven Data Synopses for Dynamic Quantiles. IEEE Trans. Knowl. Data Eng. 17 (7): 927-938 (2005) S. Muthukrishnan , Martin Strauss: Maintenance of Multidimensional Histograms. FSTTCS 2003 : 352-362 Joel A. Tropp , Anna C. Gilbert , S. Muthukrishnan , Martin Strauss: Improved sparse approximation over quasiincoherent dictionaries. ICIP (1) 2003 : 37-40 Edith Cohen , Martin Strauss: Maintaining time-decaying stream aggregates. PODS 2003 : 223-233 S. Muthukrishnan , Martin Strauss: Rangesum histograms. SODA 2003 : 233-242 Anna C. Gilbert , S. Muthukrishnan , Martin Strauss: Approximation of functions over redundant dictionaries using coherence. SODA 2003 : 243-252 Anna C. Gilbert , Yannis Kotidis , S. Muthukrishnan , Martin Strauss: One-Pass Wavelet Decompositions of Data Streams. IEEE Trans. Knowl. Data Eng. 15 (3): 541-554 (2003) Sudipto Guha , Piotr Indyk , S. Muthukrishnan , Martin Strauss: Histogramming Data Streams with Fast Per-Item Processing. ICALP 2002 : 681-692 Anna C. Gilbert , Sudipto Guha , Piotr Indyk , S. Muthukrishnan , Martin Strauss: Near-optimal sparse fourier representations via sampling. STOC 2002 : 152-161 Anna C. Gilbert , Sudipto Guha , Piotr Indyk , Yannis Kotidis , S. Muthukrishnan , Martin Strauss: Fast, small-space algorithms for approximate histogram maintenance. STOC 2002 : 389-398 Anna C. Gilbert , Yannis Kotidis , S. Muthukrishnan , Martin Strauss: How to Summarize the Universe: Dynamic Maintenance of Quantiles. VLDB 2002 : 454-465 Joan Feigenbaum , Sampath Kannan , Martin Strauss, Mahesh Viswanathan : Testing and Spot-Checking of Data Streams. Algorithmica 34 (1): 67-80 (2002) Joan Feigenbaum , Sampath Kannan , Martin Strauss, Mahesh Viswanathan : An Approximate L1-Difference Algorithm for Massive Data Streams. SIAM J. Comput. 32 (1): 131-151 (2002) Joan Feigenbaum , Yuval Ishai , Tal Malkin , Kobbi Nissim , Martin Strauss, Rebecca N. Wright : Secure Multiparty Computation of Approximations. ICALP 2001 : 927-938 Anna C. Gilbert , Yannis Kotidis , S. Muthukrishnan , Martin Strauss: Optimal and Approximate Computation of Summary Statistics for Range Aggregates. PODS 2001 Anna C. Gilbert , Yannis Kotidis , S. Muthukrishnan , Martin Strauss: Surfing Wavelets on Streams: One-Pass Summaries for Approximate Aggregate Queries. VLDB 2001 : 79-88 Jessica H. Fong , Martin Strauss: An Approximate Lp Difference Algorithm for Massive Data Streams. Discrete Mathematics & Theoretical Computer Science 4 (2): 301-322 (2001) Joan Feigenbaum , Sampath Kannan , Martin Strauss, Mahesh Viswanathan : Testing and spot-checking of data streams (extended abstract). SODA 2000 : 165-174 Jessica H. Fong , Martin Strauss: An Approximate L p -Difference Algorithm for Massive Data Streams. STACS 2000 : 193-204 Jack H. Lutz , Martin Strauss: Bias Invariance of Small Upper Spans. STACS 2000 : 74-86 Harry Buhrman , Dieter van Melkebeek , Kenneth W. Regan , D. Sivakumar , Martin Strauss: A Generalization of Resource-Bounded Measure, with Application to the BPP vs. EXP Problem. SIAM J. Comput. 30 (2): 576-601 (2000) William Aiello , Aviel D. Rubin , Martin Strauss: Using Smartcards to Secure a Personalized Gambling Device. ACM Conference on Computer and Communications Security 1999 : 128-137 Joan Feigenbaum , Sampath Kannan , Martin Strauss, Mahesh Viswanathan : An Approximate L 1 -Difference Algorithm for Massive Data Streams. FOCS 1999 : 501-511 Haim Kaplan , Martin Strauss, Mario Szegedy : Just the Fax - Differentiating Voice and Fax Phone Lines Using Call Billing Data. SODA 1999 : 935-936 Matt Blaze , Gerrit Bleumer , Martin Strauss: Divertible Protocols and Atomic Proxy Cryptography. EUROCRYPT 1998 : 127-144 Matt Blaze , Joan Feigenbaum , Martin Strauss: Compliance Checking in the PolicyMaker Trust Management System. Financial Cryptography 1998 : 254-274 Harry Buhrman , Dieter van Melkebeek , Kenneth W. Regan , D. Sivakumar , Martin Strauss: A Generalization of Resource-Bounded Measure, With an Application (Extended Abstract). STACS 1998 : 161-171 Harry Buhrman , Dieter van Melkebeek , Kenneth W. Regan , Martin Strauss, D. Sivakumar : A Generalization of Resource-Bounded Measure, With Application to the BPP vs. EXP Problem Electronic Colloquium on Computational Complexity (ECCC) 5 (58): (1998) Jin-yi Cai , D. Sivakumar , Martin Strauss: Constant Depth Circuits and the Lutz Hypothesis. FOCS 1997 : 595-604 Joan Feigenbaum , Martin Strauss: An Information-Theoretic Treatment of Random-Self-Reducibility (Extended Abstract). STACS 1997 : 523-534 Yang-Hua Chu , Joan Feigenbaum , Brian A. LaMacchia , Paul Resnick , Martin Strauss: REFEREE: Trust Management for Web Applications. Computer Networks 29 (8-13): 953-964 (1997) Martin Strauss: Measure on P: Strength of the Notion. Inf. Comput. 136 (1): 1-23 (1997) Martin Strauss: Normal Numbers and Sources for BPP. Theor. Comput. Sci. 178 (1-2): 155-169 (1997) Eric Allender , Martin Strauss: Measure on P: Robustness of the Notion. MFCS 1995 : 129-138 Martin Strauss: Normal Numbers and Sources for BPP. STACS 1995 : 515-526 Eric Allender , Martin Strauss: Measure on P: Robustness of the Notion Electronic Colloquium on Computational Complexity (ECCC) 2 (28): (1995) Eric Allender , Martin Strauss: Measure on Small Complexity Classes, with Applications for BPP FOCS 1994 : 807-818 Eric Allender , Martin Strauss: Measure on Small Complexity Classes, with Applications for BPP Electronic Colloquium on Computational Complexity (ECCC) 1 (4): (1994) 1 [ 17 ] 2 [ 1 ] [ 2 ] [ 3 ] [ 5 ] 3 [ 13 ] [ 14 ] 4 [ 14 ] 5 [ 11 ] [ 12 ] [ 18 ] 6 [ 10 ] 7 [ 40 ] 8 [ 8 ] 9 [ 35 ] 10 [ 8 ] [ 9 ] [ 13 ] [ 16 ] [ 21 ] [ 25 ] [ 26 ] [ 27 ] 11 [ 20 ] [ 22 ] [ 39 ] 12 [ 23 ] [ 24 ] [ 28 ] [ 29 ] [ 30 ] [ 32 ] [ 33 ] [ 36 ] [ 38 ] [ 39 ] [ 40 ] 13 [ 29 ] [ 30 ] [ 31 ] 14 [ 29 ] [ 30 ] [ 31 ] 15 [ 25 ] 16 [ 16 ] [ 21 ] [ 26 ] [ 27 ] [ 39 ] 17 [ 15 ] 18 [ 23 ] [ 24 ] [ 28 ] [ 29 ] [ 32 ] [ 38 ] 19 [ 8 ] 20 [ 40 ] 21 [ 19 ] 22 [ 25 ] 23 [ 11 ] [ 12 ] [ 18 ] 24 [ 23 ] [ 24 ] [ 28 ] [ 29 ] [ 30 ] [ 31 ] [ 32 ] [ 33 ] [ 34 ] [ 36 ] [ 37 ] [ 38 ] [ 40 ] [ 41 ] 25 [ 25 ] 26 [ 11 ] [ 12 ] [ 18 ] 27 [ 8 ] 28 [ 17 ] 29 [ 10 ] [ 11 ] [ 12 ] [ 18 ] 30 [ 15 ] 31 [ 36 ] 32 [ 16 ] [ 21 ] [ 26 ] [ 27 ] 33 [ 25 ] 34 [ 41 ]  ©2006 Association for Computing Machinery |
