BibSLEIGH — Dan

Travelled to:

1 × Finland
1 × France
1 × Germany
1 × Israel
1 × Italy
1 × United Kingdom
2 × Australia
2 × China
5 × USA

Collaborated with:

C.M.Cumby R.Samdani K.Chang C.Zhai A.Garg J.Han V.G.V.Vydiswaran C.Lee J.Pasternack W.Yih A.R.Golding X.Wang C.Zhai A.Klementiev K.Small S.Har-Peled R.Greiner A.J.Grove H.Zhuang A.G.Parameswaran Y.Lu H.Wang P.Pirolli M.Chang V.Srikumar D.Goldwasser Pranav Garg 0001 D.Neider P.Madhusudan C.Wang Y.Song A.El-Kishky M.Zhang Y.Li C.Wang F.Han X.Yan

Talks about:

learn (8) model (4) distribut (3) linear (3) unsupervis (2) structur (2) network (2) cluster (2) margin (2) trust (2)

Person: Dan Roth

DBLP: Roth:Dan

Contributed to:

2015

2014

2013

2012

2011

2010

2009

2008

2005

2003

2002

2000

1996

2016

Wrote 22 papers:

ICML-2015-LeeR #distributed #linear #optimisation #polynomial: Distributed Box-Constrained Quadratic Optimization for Dual Linear SVM (CPL, DR), pp. 987–996.
KDD-2015-WangSERZH #clustering #documentation #network: Incorporating World Knowledge to Document Clustering via Heterogeneous Information Networks (CW, YS, AEK, DR, MZ, JH), pp. 1215–1224.
KDD-2015-ZhuangPRH #crowdsourcing: Debiasing Crowdsourced Batches (HZ, AGP, DR, JH), pp. 1593–1602.
ICML-c1-2014-SamdaniCR #clustering #online: A Discriminative Latent Variable Model for Online Clustering (RS, KWC, DR), pp. 1–9.
KDD-2013-LiWHHRY #ambiguity #mining: Mining evidences for named entity disambiguation (YL, CW, FH, JH, DR, XY), pp. 1070–1078.
KDD-2013-WangZR #comprehension #evolution #generative #probability #research: Understanding evolution of research themes: a probabilistic generative model for citations (XW, CZ, DR), pp. 1115–1123.
CIKM-2012-LuWZR #network: Unsupervised discovery of opposing opinion networks from forum discussions (YL, HW, CZ, DR), pp. 1642–1646.
CIKM-2012-VydiswaranZRP #education #named #topic: BiasTrust: teaching biased users about controversial topics (VGVV, CZ, DR, PP), pp. 1905–1909.
ICML-2012-SamdaniR #learning #performance #predict: Efficient Decomposed Learning for Structured Prediction (RS, DR), p. 200.
KDD-2011-ChangR #convergence #linear #memory management #modelling #performance #scalability: Selective block minimization for faster convergence of limited memory large-scale linear models (KWC, DR), pp. 699–707.
KDD-2011-VydiswaranZR #framework #trust: Content-driven trust propagation framework (VGVV, CZ, DR), pp. 974–982.
ICML-2010-ChangSGR #learning: Structured Output Learning with Indirect Supervision (MWC, VS, DG, DR), pp. 199–206.
CIKM-2009-PasternackR #learning: Learning better transliterations (JP, DR), pp. 177–186.
ICML-2008-KlementievRS #modelling #rank: Unsupervised rank aggregation with distance-based models (AK, DR, KS), pp. 472–479.
ICML-2005-RothY #integer #linear #programming #random: Integer linear programming inference for conditional random fields (DR, WtY), pp. 736–743.
ICML-2003-CumbyR #kernel #learning #on the #relational: On Kernel Methods for Relational Learning (CMC, DR), pp. 107–114.
ICML-2003-GargR #learning: Margin Distribution and Learning (AG, DR), pp. 210–217.
ICML-2002-GargHR #bound #on the: On generalization bounds, projection profile, and margin distribution (AG, SHP, DR), pp. 171–178.
KR-2000-CumbyR #learning #relational: Relational Representations that Facilitate Learning (CMC, DR), pp. 425–434.
ICML-1996-GoldingR: Applying Winnow to Context-Sensitive Spelling Correction (ARG, DR), pp. 182–190.
ICML-1996-GreinerGR #classification #learning: Learning Active Classifiers (RG, AJG, DR), pp. 207–215.
POPL-2016-0001NMR #invariant #learning #using: Learning invariants using decision trees and implication counterexamples (PG0, DN, PM, DR), pp. 499–512.