BibSLEIGH corpus
BibSLEIGH tags
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BibSLEIGH people
Open Knowledge
XHTML 1.0 W3C Rec
CSS 2.1 W3C CanRec
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Travelled to:
1 × Australia
1 × Canada
1 × China
1 × Finland
1 × Germany
1 × Italy
1 × United Kingdom
5 × USA
Collaborated with:
F.Peng F.Southey S.Wang R.Greiner R.Patrascu L.Xu C.Szepesvári J.Neufeld Y.Yu L.Cheng M.White C.Guestrin F.Lu L.H.Ungar D.P.Foster A.György H.Cheng D.F.Wilkinson F.Jiao T.Wang D.J.Lizotte M.H.Bowling Y.Zhao X.Zhang R.Kiros S.Wang X.Huang N.Cercone S.E.Robertson
Talks about:
model (6) learn (6) supervis (4) regular (3) unsupervis (2) character (2) bayesian (2) maximum (2) languag (2) factor (2)

Person: Dale Schuurmans

DBLP DBLP: Schuurmans:Dale

Contributed to:

ICML c2 20142014
ICML c1 20132013
ICML 20122012
ICML 20092009
ICML 20062006
ICML 20052005
ECIR 20032003
ICML 20032003
ICML 20022002
SIGIR 20022002
ICML 20002000
ICML 19971997
KR 19921992

Wrote 16 papers:

ICML-c2-2014-NeufeldGSS #adaptation #monte carlo
Adaptive Monte Carlo via Bandit Allocation (JN, AG, CS, DS), pp. 1944–1952.
ICML-c1-2013-YuCSS #theorem
Characterizing the Representer Theorem (YY, HC, DS, CS), pp. 570–578.
ICML-2012-NeufeldYZKS #reduction
Regularizers versus Losses for Nonlinear Dimensionality Reduction: A Factored View with New Convex Relaxations (JN, YY, XZ, RK, DS), p. 191.
ICML-2009-XuWS #learning #predict
Optimal reverse prediction: a unified perspective on supervised, unsupervised and semi-supervised learning (LX, MW, DS), pp. 1137–1144.
ICML-2006-XuWSS #learning #predict
Discriminative unsupervised learning of structured predictors (LX, DFW, FS, DS), pp. 1057–1064.
ICML-2005-ChengJSW #image #modelling
Variational Bayesian image modelling (LC, FJ, DS, SW), pp. 129–136.
ICML-2005-WangLBS #online #optimisation
Bayesian sparse sampling for on-line reward optimization (TW, DJL, MHB, DS), pp. 956–963.
ICML-2005-WangWGSC #markov #modelling #random #semantics
Exploiting syntactic, semantic and lexical regularities in language modeling via directed Markov random fields (SW, SW, RG, DS, LC), pp. 948–955.
ECIR-2003-PengS #classification #modelling #n-gram #naive bayes
Combining Naive Bayes and n-Gram Language Models for Text Classification (FP, DS), pp. 335–350.
ICML-2003-WangSPZ #learning #modelling #principle
Learning Mixture Models with the Latent Maximum Entropy Principle (SW, DS, FP, YZ), pp. 784–791.
ICML-2002-GuestrinPS #learning #modelling
Algorithm-Directed Exploration for Model-Based Reinforcement Learning in Factored MDPs (CG, RP, DS), pp. 235–242.
Investigating the Maximum Likelihood Alternative to TD(λ) (FL, RP, DS), pp. 403–410.
SIGIR-2002-PengHSCR #information retrieval #segmentation #self #using #word
Using self-supervised word segmentation in Chinese information retrieval (FP, XH, DS, NC, SER), pp. 349–350.
ICML-2000-SchuurmansS #adaptation #learning
An Adaptive Regularization Criterion for Supervised Learning (DS, FS), pp. 847–854.
ICML-1997-SchuurmansUF #performance
Characterizing the generalization performance of model selection strategies (DS, LHU, DPF), pp. 340–348.
KR-1992-GreinerS #approximate #learning
Learning Useful Horn Approximations (RG, DS), pp. 383–392.

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.