BibSLEIGH corpus
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Open Knowledge
XHTML 1.0 W3C Rec
CSS 2.1 W3C CanRec
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Travelled to:
1 × Australia
1 × Canada
1 × Germany
1 × Israel
1 × United Kingdom
2 × China
2 × France
9 × USA
Collaborated with:
A.Krause D.Shahaf K.El-Arini A.Kyrola J.K.Bradley D.Bickson E.B.Fox T.Johnson J.Huang J.Leskovec Y.Low J.M.Hellerstein T.Chen Y.Yue S.A.Hong E.Horvitz G.E.Blelloch A.P.Singh M.G.Lagoudakis R.Parr R.Patrascu D.Schuurmans M.Xu G.Veda B.Taskar V.Chatalbashev D.Koller J.E.Gonzalez H.Gu A.Deshpande S.Madden W.Hong J.Gonzalez C.Faloutsos J.M.VanBriesen N.S.Glance
Talks about:
learn (8) graph (6) explor (3) scale (3) model (3) distribut (2) algorithm (2) reinforc (2) parallel (2) hierarch (2)

Person: Carlos Guestrin

DBLP DBLP: Guestrin:Carlos

Contributed to:

ICML 20152015
ICML c2 20142014
CIKM 20132013
KDD 20132013
ICML 20122012
KDD 20122012
OSDI 20122012
VLDB 20122012
ICML 20112011
KDD 20112011
ICML 20102010
KDD 20102010
KDD 20092009
ICML 20072007
KDD 20072007
ICML 20062006
ICML 20052005
VLDB 20042004
ICML 20022002

Wrote 23 papers:

ICML-2015-JohnsonG #named #optimisation #scalability
Blitz: A Principled Meta-Algorithm for Scaling Sparse Optimization (TJ, CG), pp. 1171–1179.
ICML-c2-2014-ChenFG #monte carlo #probability
Stochastic Gradient Hamiltonian Monte Carlo (TC, EBF, CG), pp. 1683–1691.
CIKM-2013-Guestrin #machine learning #scalability #usability
Usability in machine learning at scale with graphlab (CG), pp. 5–6.
KDD-2013-El-AriniXFG #documentation #representation
Representing documents through their readers (KEA, MX, EBF, CG), pp. 14–22.
Hierarchical Exploration for Accelerating Contextual Bandits (YY, SAH, CG), p. 128.
Metro maps of science (DS, CG, EH), pp. 1122–1130.
OSDI-2012-GonzalezLGBG #distributed #graph #named
PowerGraph: Distributed Graph-Parallel Computation on Natural Graphs (JEG, YL, HG, DB, CG), pp. 17–30.
OSDI-2012-KyrolaBG #graph #named #scalability
GraphChi: Large-Scale Graph Computation on Just a PC (AK, GEB, CG), pp. 31–46.
VLDB-2012-LowGKBGH #distributed #framework #in the cloud #machine learning
Distributed GraphLab: A Framework for Machine Learning in the Cloud (YL, JG, AK, DB, CG, JMH), pp. 716–727.
ICML-2011-BradleyKBG #coordination #parallel
Parallel Coordinate Descent for L1-Regularized Loss Minimization (JKB, AK, DB, CG), pp. 321–328.
KDD-2011-El-AriniG #keyword
Beyond keyword search: discovering relevant scientific literature (KEA, CG), pp. 439–447.
ICML-2010-BradleyG #learning #random
Learning Tree Conditional Random Fields (JKB, CG), pp. 127–134.
ICML-2010-HuangG #independence #learning #ranking
Learning Hierarchical Riffle Independent Groupings from Rankings (JH, CG), pp. 455–462.
Connecting the dots between news articles (DS, CG), pp. 623–632.
Turning down the noise in the blogosphere (KEA, GV, DS, CG), pp. 289–298.
ICML-2007-KrauseG #approach #learning #process
Nonmyopic active learning of Gaussian processes: an exploration-exploitation approach (AK, CG), pp. 449–456.
KDD-2007-LeskovecKGFVG #detection #effectiveness #network
Cost-effective outbreak detection in networks (JL, AK, CG, CF, JMV, NSG), pp. 420–429.
ICML-2006-KrauseLG #topic
Data association for topic intensity tracking (AK, JL, CG), pp. 497–504.
ICML-2005-GuestrinKS #process
Near-optimal sensor placements in Gaussian processes (CG, AK, APS), pp. 265–272.
ICML-2005-TaskarCKG #approach #learning #modelling #predict #scalability
Learning structured prediction models: a large margin approach (BT, VC, DK, CG), pp. 896–903.
VLDB-2004-DeshpandeGMHH #modelling #network
Model-Driven Data Acquisition in Sensor Networks (AD, CG, SM, JMH, WH), pp. 588–599.
ICML-2002-GuestrinLP #coordination #learning
Coordinated Reinforcement Learning (CG, MGL, RP), pp. 227–234.
ICML-2002-GuestrinPS #learning #modelling
Algorithm-Directed Exploration for Model-Based Reinforcement Learning in Factored MDPs (CG, RP, DS), pp. 235–242.

Bibliography of Software Language Engineering in Generated Hypertext (BibSLEIGH) is created and maintained by Dr. Vadim Zaytsev.
Hosted as a part of SLEBOK on GitHub.