BibSLEIGH — Avrim

Travelled to:

1 × France
16 × USA
4 × Canada

Collaborated with:

∅ S.Vempala M.Balcan S.Chawla S.Rudich K.Ligett A.Roth R.Ravi M.Hardt Y.Mansour P.Chalasani P.Raghavan N.Balcan H.B.McMahan G.J.Gordon A.Kalai H.Wasserman B.Schieber M.Hajiaghayi C.Dwork F.McSherry K.Nissim J.D.Lafferty M.R.Rwebangira R.Reddy N.Bansal A.Meyerson J.O'Sullivan J.Langford R.Caruana G.Konjevod Y.Bartal C.Burch A.Tomkins B.Awerbuch Y.Azar T.Jiang M.Li J.Tromp M.Yannakakis D.Coppersmith W.R.Pulleyblank M.Sudan M.L.Furst J.C.Jackson M.J.Kearns

Talks about:

learn (12) algorithm (7) approxim (7) problem (5) function (4) minimum (3) improv (3) queri (3) use (3) framework (2)

Person: Avrim Blum

DBLP: Blum:Avrim

Contributed to:

2015

2013

2008

2006

2005

2004

2003

2001

2000

1998

1997

1996

1995

1994

1992

1991

1990

1989

Wrote 26 papers:

ICML-2015-BlumH #contest #machine learning #reliability: The Ladder: A Reliable Leaderboard for Machine Learning Competitions (AB, MH), pp. 1006–1014.
ICML-c3-2013-BalcanBM #learning #ontology: Exploiting Ontology Structures and Unlabeled Data for Learning (NB, AB, YM), pp. 1112–1120.
STOC-2008-BalcanBV #clustering #framework #similarity: A discriminative framework for clustering via similarity functions (MFB, AB, SV), pp. 671–680.
STOC-2008-BlumHLR: Regret minimization and the price of total anarchy (AB, MH, KL, AR), pp. 373–382.
STOC-2008-BlumLR #approach #database #learning #privacy: A learning theory approach to non-interactive database privacy (AB, KL, AR), pp. 609–618.
ICML-2006-BalcanB #formal method #learning #on the #similarity: On a theory of learning with similarity functions (MFB, AB), pp. 73–80.
PODS-2005-BlumDMN #framework #privacy: Practical privacy: the SuLQ framework (AB, CD, FM, KN), pp. 128–138.
ICML-2004-BlumLRR #learning #random #using: Semi-supervised learning using randomized mincuts (AB, JDL, MRR, RR).
STOC-2004-BansalBCM #algorithm #approximate: Approximation algorithms for deadline-TSP and vehicle routing with time-windows (NB, AB, SC, AM), pp. 166–174.
ICML-2003-McMahanGB #cost analysis: Planning in the Presence of Cost Functions Controlled by an Adversary (HBM, GJG, AB), pp. 536–543.
ICML-2001-BlumC #graph #learning #using: Learning from Labeled and Unlabeled Data using Graph Mincuts (AB, SC), pp. 19–26.
ICML-2000-OSullivanLCB #algorithm #named #robust: FeatureBoost: A Meta-Learning Algorithm that Improves Model Robustness (JO, JL, RC, AB), pp. 703–710.
STOC-2000-BlumKW #learning #problem #query #statistics: Noise-tolerant learning, the parity problem, and the statistical query model (AB, AK, HW), pp. 435–440.
STOC-1998-BlumKRV #problem: Semi-Definite Relaxations for Minimum Bandwidth and other Vertex-Ordering Problems (AB, GK, RR, SV), pp. 100–105.
STOC-1997-BartalBBT #algorithm: A polylog(n)-Competitive Algorithm for Metrical Task Systems (YB, AB, CB, AT), pp. 711–719.
STOC-1996-BlumRV #algorithm #approximate #problem: A Constant-factor Approximation Algorithm for the k MST Problem (AB, RR, SV), pp. 442–448.
ICML-1995-Blum #algorithm #empirical #scheduling: Empirical Support for Winnow and Weighted-Majority Based Algorithms: Results on a Calendar Scheduling Domain (AB), pp. 64–72.
STOC-1995-AwerbuchABV #approximate: Improved approximation guarantees for minimum-weight k-trees and prize-collecting salesmen (BA, YA, AB, SV), pp. 277–283.
STOC-1995-BlumCV #approximate #problem: A constant-factor approximation for the k-MST problem in the plane (AB, PC, SV), pp. 294–302.
STOC-1994-BlumCCPRS #latency #problem: The minimum latency problem (AB, PC, DC, WRP, PR, MS), pp. 163–171.
STOC-1994-BlumFJKMR #analysis #fourier #learning #query #statistics #using: Weakly learning DNF and characterizing statistical query learning using Fourier analysis (AB, MLF, JCJ, MJK, YM, SR), pp. 253–262.
STOC-1992-BlumR #learning #performance #query: Fast Learning of k-Term DNF Formulas with Queries (AB, SR), pp. 382–389.
STOC-1991-BlumJLTY #approximate #linear #string: Linear Approximation of Shortest Superstrings (AB, TJ, ML, JT, MY), pp. 328–336.
STOC-1991-BlumRS #geometry #navigation: Navigating in Unfamiliar Geometric Terrain (AB, PR, BS), pp. 494–504.
STOC-1990-Blum #infinity #learning: Learning Boolean Functions in an Infinite Atribute Space (AB), pp. 64–72.
STOC-1989-Blum #algorithm #approximate: An O(n⁰⋅⁴)-Approximation Algorithm for 3-Coloring (and Improved Approximation Algorithm for k-Coloring) (AB), pp. 535–542.