Travelled to:1 × Brazil
1 × China
1 × India
1 × Israel
1 × Japan
1 × United Kingdom
4 × USA
Collaborated with:M.Ranzato L.Bottou P.Haffner S.Zhang K.Gregor S.Chopra P.G.Howard J.B.Estrach A.Szlam T.Schaul P.Sermanet S.Chintala Y.Boureau J.Ponce C.Farabet C.Couprie L.Najman F.J.Huang L.Wan M.D.Zeiler R.Fergus T.Thampy J.Leahy A.Caplin H.Drucker C.Cortes L.D.Jackel V.Vapnik P.Y.Simard Y.Bengio
Talks about:document (5) learn (4) featur (3) recognit (2) network (2) neural (2) spars (2) model (2) digit (2) appli (2)
Person: Yann LeCun
DBLP: LeCun:Yann
Contributed to:
201420132012
20122010
2007
2007200119991994
1998Wrote 14 papers:
- ICML-c2-2014-EstrachSL
- Signal recovery from Pooling Representations (JBE, AS, YL), pp. 307–315.
- ICML-c3-2013-SchaulZL #learning
- No more pesky learning rates (TS, SZ, YL), pp. 343–351.
- ICML-c3-2013-WanZZLF #network #using
- Regularization of Neural Networks using DropConnect (LW, MDZ, SZ, YL, RF), pp. 1058–1066.
- ICML-2012-FarabetCNL #learning #multi #parsing
- Scene parsing with Multiscale Feature Learning, Purity Trees, and Optimal Covers (CF, CC, LN, YL), p. 241.
- ICPR-2012-SermanetCL #classification #network
- Convolutional neural networks applied to house numbers digit classification (PS, SC, YL), pp. 3288–3291.
- ICML-2010-BoureauPL #analysis #recognition #visual notation
- A Theoretical Analysis of Feature Pooling in Visual Recognition (YLB, JP, YL), pp. 111–118.
- ICML-2010-GregorL #approximate #learning #performance
- Learning Fast Approximations of Sparse Coding (KG, YL), pp. 399–406.
- ICDAR-2007-LeCunCRH #documentation #energy #modelling #recognition
- Energy-Based Models in Document Recognition and Computer Vision (YL, SC, MR, FJH), pp. 337–341.
- ICDAR-2007-RanzatoL #documentation #image #invariant
- A Sparse and Locally Shift Invariant Feature Extractor Applied to Document Images (MR, YL), pp. 1213–1217.
- KDD-2007-ChopraTLCL #parametricity
- Discovering the hidden structure of house prices with a non-parametric latent manifold model (SC, TT, JL, AC, YL), pp. 173–182.
- ICDAR-2001-BottouHL #documentation #multi #performance
- Efficient Conversion of Digital Documents to Multilayer Raster Formats (LB, PH, YL), pp. 444–449.
- ICDAR-1999-HaffnerBHL #documentation #internet #named
- DjVu: Analyzing and Compressing Scanned Documents for Internet Distribution (PH, LB, PGH, YL), pp. 625–628.
- ICML-1994-DruckerCJCV #algorithm #machine learning
- Boosting and Other Machine Learning Algorithms (HD, CC, LDJ, YL, VV), pp. 53–61.
- ADL-1998-HaffnerBHSBC #documentation #image #quality
- Browsing through High Quality Document Images with DjVu (PH, LB, PGH, PYS, YB, YL), pp. 309–318.