BibSLEIGH — Jason

Travelled to:

1 × Australia
1 × Canada
1 × Finland
1 × France
1 × Germany
1 × Israel
1 × The Netherlands
1 × United Kingdom
3 × China
3 × USA

Collaborated with:

R.Collobert H.Yee R.J.Weiss L.Bottou A.Bordes Y.Qi F.H.Sinz B.Bai D.Grangier A.Makadia N.Usunier H.Mobahi F.Ratle C.Cortes M.Mohri S.G.Das C.Wang A.Berenzweig Y.Bengio J.Louradour M.Karlen A.Erkan P.Gallinari E.Ie W.S.Noble C.S.Leslie E.Denton M.Paluri L.D.Bourdev R.Fergus P.P.Kuksa K.Kavukcuoglu V.Vapnik K.Sadamasa O.Chapelle K.Q.Weinberger

Talks about:

learn (9) supervis (4) rank (4) deep (4) semant (3) label (3) embed (3) transduct (2) latent (2) index (2)

Person: Jason Weston

DBLP: Weston:Jason

Contributed to:

2015

2014

2013

2012

2010

2009

2008

2007

2006

2005

Wrote 21 papers:

KDD-2015-DentonWPBF #hashtag #image #predict: User Conditional Hashtag Prediction for Images (ED, JW, MP, LDB, RF), pp. 1731–1740.
ECIR-2014-QiDCW #information management #learning: Deep Learning for Character-Based Information Extraction (YQ, SGD, RC, JW), pp. 668–674.
ICML-c2-2014-WestonWY: Affinity Weighted Embedding (JW, RJW, HY), pp. 1215–1223.
ICML-c2-2013-WestonMY #clustering #ranking #sublinear: Label Partitioning For Sublinear Ranking (JW, AM, HY), pp. 181–189.
RecSys-2013-WestonWY #multi: Nonlinear latent factorization by embedding multiple user interests (JW, RJW, HY), pp. 65–68.
RecSys-2013-WestonYW #learning #rank #recommendation #statistics: Learning to rank recommendations with the k-order statistic loss (JW, HY, RJW), pp. 245–248.
ICML-2012-WestonWWB #collaboration #retrieval: Latent Collaborative Retrieval (JW, CW, RJW, AB), p. 61.
ICML-2010-BordesUW #ambiguity #learning #ranking #semantics: Label Ranking under Ambiguous Supervision for Learning Semantic Correspondences (AB, NU, JW), pp. 103–110.
CIKM-2009-BaiWGCSQCW #semantics: Supervised semantic indexing (BB, JW, DG, RC, KS, YQ, OC, KQW), pp. 187–196.
CIKM-2009-QiCKKW #learning: Combining labeled and unlabeled data with word-class distribution learning (YQ, RC, PPK, KK, JW), pp. 1737–1740.
ECIR-2009-BaiWCG #semantics: Supervised Semantic Indexing (BB, JW, RC, DG), pp. 761–765.
ICML-2009-BengioLCW #education #learning: Curriculum learning (YB, JL, RC, JW), pp. 41–48.
ICML-2009-MobahiCW #learning #video: Deep learning from temporal coherence in video (HM, RC, JW), pp. 737–744.
ICML-2008-CollobertW #architecture #learning #multi #natural language #network: A unified architecture for natural language processing: deep neural networks with multitask learning (RC, JW), pp. 160–167.
ICML-2008-KarlenWEC #scalability: Large scale manifold transduction (MK, JW, AE, RC), pp. 448–455.
ICML-2008-WestonRC #learning: Deep learning via semi-supervised embedding (JW, FR, RC), pp. 1168–1175.
ICML-2007-BordesBGW #multi: Solving multiclass support vector machines with LaRank (AB, LB, PG, JW), pp. 89–96.
ICML-2006-CollobertSWB #scalability: Trading convexity for scalability (RC, FHS, JW, LB), pp. 201–208.
ICML-2006-WestonCSBV: Inference with the Universum (JW, RC, FHS, LB, VV), pp. 1009–1016.
ICML-2005-CortesMW #learning: A general regression technique for learning transductions (CC, MM, JW), pp. 153–160.
ICML-2005-IeWNL #adaptation #multi #recognition #using: Multi-class protein fold recognition using adaptive codes (EI, JW, WSN, CSL), pp. 329–336.