Travelled to:1 × France
1 × Israel
1 × United Kingdom
2 × USA
Collaborated with:A.Globerson Y.Jernite A.M.Rush X.Wang F.Wang T.Roughgarden C.Yildirim O.Meshi T.S.Jaakkola K.Collins-Thompson P.N.Bennett R.W.White S.d.l.Chica S.Arora R.Ge Y.Halpern D.M.Mimno A.Moitra Y.Wu M.Zhu
Talks about:model (3) learn (3) infer (2) unsupervis (1) algorithm (1) structur (1) progress (1) guarante (1) approxim (1) approach (1)
Person: David Sontag
DBLP: Sontag:David
Contributed to:
2015
20142013
20112010Wrote 6 papers:
- ICML-2015-GlobersonRSY #how #predict #question
- How Hard is Inference for Structured Prediction? (AG, TR, DS, CY), pp. 2181–2190.
- ICML-2015-JerniteRS #approach #learning #markov #modelling #performance #random
- A Fast Variational Approach for Learning Markov Random Field Language Models (YJ, AMR, DS), pp. 2209–2217.
- KDD-2014-WangSW #learning #modelling
- Unsupervised learning of disease progression models (XW, DS, FW), pp. 85–94.
- ICML-c2-2013-AroraGHMMSWZ #algorithm #modelling #topic
- A Practical Algorithm for Topic Modeling with Provable Guarantees (SA, RG, YH, DMM, AM, DS, YW, MZ), pp. 280–288.
- CIKM-2011-Collins-ThompsonBWCS #personalisation #web
- Personalizing web search results by reading level (KCT, PNB, RWW, SdlC, DS), pp. 403–412.
- ICML-2010-MeshiSJG #approximate #learning
- Learning Efficiently with Approximate Inference via Dual Losses (OM, DS, TSJ, AG), pp. 783–790.