Travelled to:1 × Australia
1 × Germany
1 × Slovenia
7 × USA
Collaborated with:N.Cristianini M.Marchand C.Saunders K.P.Bennett P.Tsampouka A.D.Lehmann J.Leskovec S.Grünewälder A.Gretton H.Tschach H.Lodhi T.Joachims A.Demiriz M.Rychetsky M.Glesner P.Sykacek J.Rousu S.Szedmák M.Shah M.Sokolova D.Wu Y.Li H.Zaragoza R.Herbrich J.S.Kandola
Talks about:margin (4) kernel (4) algorithm (3) machin (3) uneven (2) space (2) model (2) learn (2) cover (2) boost (2)
Person: John Shawe-Taylor
DBLP: Shawe-Taylor:John
Contributed to:
2013200720062005200320022001200019991998Wrote 15 papers:
- ICML-c3-2013-GrunewalderAS
- Smooth Operators (SG, AG, JST), pp. 1184–1192.
- ICML-2007-TsampoukaS #algorithm #approximate
- Approximate maximum margin algorithms with rules controlled by the number of mistakes (PT, JST), pp. 903–910.
- ICML-2006-LehmannS #kernel #probability
- A probabilistic model for text kernels (ADL, JST), pp. 537–544.
- ICML-2005-RousuSSS #classification #learning #modelling #multi
- Learning hierarchical multi-category text classification models (JR, CS, SS, JST), pp. 744–751.
- ICML-2003-LeskovecS #dataset #linear #programming
- Linear Programming Boosting for Uneven Datasets (JL, JST), pp. 456–463.
- ICML-2003-MarchandSSS #set
- The Set Covering Machine with Data-Dependent Half-Spaces (MM, MS, JST, MS), pp. 520–527.
- ICML-2002-LiZHSK #algorithm
- The Perceptron Algorithm with Uneven Margins (YL, HZ, RH, JST, JSK), pp. 379–386.
- ICML-2002-SaundersTS #kernel #string
- Syllables and other String Kernel Extensions (CS, HT, JST), pp. 530–537.
- ICML-2001-CristianiniSL #kernel #semantics
- Latent Semantic Kernels (NC, JST, HL), pp. 66–73.
- ICML-2001-JoachimsCS #categorisation #hypermedia #kernel
- Composite Kernels for Hypertext Categorisation (TJ, NC, JST), pp. 250–257.
- ICML-2001-MarchandS #learning #set
- Learning with the Set Covering Machine (MM, JST), pp. 345–352.
- ICML-2000-BennetDS #algorithm #generative
- A Column Generation Algorithm For Boosting (KPB, AD, JST), pp. 65–72.
- ICML-2000-RychetskySG
- Direct Bayes Point Machines (MR, JST, MG), pp. 815–822.
- ICML-1999-WuBCS #induction #scalability
- Large Margin Trees for Induction and Transduction (DW, KPB, NC, JST), pp. 474–483.
- ICML-1998-CristianiniSS #classification #scalability
- Bayesian Classifiers Are Large Margin Hyperplanes in a Hilbert Space (NC, JST, PS), pp. 109–117.