BibSLEIGH — David_P

Travelled to:

1 × Australia
1 × Canada
1 × Japan
1 × Switzerland
1 × United Kingdom
10 × USA
2 × France

Collaborated with:

J.Nelson K.L.Clarkson ∅ Q.Zhang S.Tirthapura Y.Li D.M.Kane G.Yaroslavtsev O.Weinstein C.Boutsidis M.Hardt C.Sohler P.Indyk H.Zhou M.Molinaro Z.Wang R.Pagh M.Stöckel H.L.Nguyên B.Kimelfeld J.Vondrák A.V.Evfimievski R.Fagin D.V.Gucht R.Williams M.W.Mahoney P.Drineas M.Magdon-Ismail A.McGregor A.Pavan E.Porat P.Berman A.Bhattacharyya E.Grigorescu S.Raskhodnikova

Talks about:

stream (8) optim (6) approxim (5) data (5) matrix (4) complex (3) sketch (3) linear (3) applic (3) fast (3)

Person: David P. Woodruff

DBLP: Woodruff:David_P=

Contributed to:

2015

2014

2013

2012

2011

2010

2009

2008

2005

2004

Wrote 25 papers:

ICALP-v1-2015-MolinaroWY #complexity: Amplification of One-Way Information Complexity via Codes and Noise Sensitivity (MM, DPW, GY), pp. 960–972.
ICALP-v1-2015-WeinsteinW #communication #data type: The Simultaneous Communication of Disjointness with Applications to Data Streams (OW, DPW), pp. 1082–1093.
PODS-2015-GuchtWWZ #communication #complexity #distributed #matrix #multi: The Communication Complexity of Distributed Set-Joins with Applications to Matrix Multiplication (DVG, RW, DPW, QZ), pp. 199–212.
KDD-2014-LiWW #matrix #rank #testing: Improved testing of low rank matrices (YL, ZW, DPW), pp. 691–700.
PODS-2014-PaghSW #question #set: Is min-wise hashing optimal for summarizing set intersection? (RP, MS, DPW), pp. 109–120.
STOC-2014-BoutsidisW #matrix: Optimal CUR matrix decompositions (CB, DPW), pp. 353–362.
STOC-2014-LiNW #algorithm #linear #sketching #streaming: Turnstile streaming algorithms might as well be linear sketches (YL, HLN, DPW), pp. 174–183.
STOC-2013-ClarksonW #approximate #rank: Low rank approximation and regression in input sparsity time (KLC, DPW), pp. 81–90.
STOC-2013-HardtW #adaptation #how #linear #question #robust #sketching: How robust are linear sketches to adaptive inputs? (MH, DPW), pp. 121–130.
VLDB-2013-KimelfeldVW #approximate #complexity #multi: Multi-Tuple Deletion Propagation: Approximations and Complexity (BK, JV, DPW), pp. 1558–1569.
ICML-2012-MahoneyDMW #approximate #matrix #performance #statistics: Fast approximation of matrix coherence and statistical leverage (MWM, PD, MMI, DPW), p. 137.
PODS-2012-McGregorPTW #estimation #statistics: Space-efficient estimation of statistics over sub-sampled streams (AM, AP, ST, DPW), pp. 273–282.
PODS-2012-TirthapuraW #data type: Rectangle-efficient aggregation in spatial data streams (ST, DPW), pp. 283–294.
STOC-2012-WoodruffZ #bound #distributed #functional #monitoring: Tight bounds for distributed functional monitoring (DPW, QZ), pp. 941–960.
ICALP-v1-2011-BermanBGRWY #transitive: Steiner Transitive-Closure Spanners of Low-Dimensional Posets (PB, AB, EG, SR, DPW, GY), pp. 760–772.
STOC-2011-KaneNPW #data type #estimation #performance: Fast moment estimation in data streams in optimal space (DMK, JN, EP, DPW), pp. 745–754.
STOC-2011-SohlerW: Subspace embeddings for the L1-norm with applications (CS, DPW), pp. 755–764.
STOC-2011-Woodruff #approximate #black box #protocol: Near-optimal private approximation protocols via a black box transformation (DPW), pp. 735–744.
ICALP-v1-2010-Woodruff #polynomial: Additive Spanners in Nearly Quadratic Time (DPW), pp. 463–474.
PODS-2010-KaneNW #algorithm #problem: An optimal algorithm for the distinct elements problem (DMK, JN, DPW), pp. 41–52.
PODS-2010-NelsonW #data type #performance #sketching: Fast Manhattan sketches in data streams (JN, DPW), pp. 99–110.
STOC-2009-ClarksonW #algebra #linear #streaming: Numerical linear algebra in the streaming model (KLC, DPW), pp. 205–214.
PODS-2008-EvfimievskiFW #privacy: Epistemic privacy (AVE, RF, DPW), pp. 171–180.
STOC-2005-IndykW #approximate #data type: Optimal approximations of the frequency moments of data streams (PI, DPW), pp. 202–208.
PODS-2004-ZhouW #clustering #matrix: Clustering via Matrix Powering (HZ, DPW), pp. 136–142.