Travelled to:1 × Canada
1 × China
1 × United Kingdom
4 × USA
Collaborated with:K.Sohn A.Y.Ng A.Khosla R.Mittelman B.Kuipers S.Savarese S.Reed Y.Zhang G.Zhou C.Lee R.B.Grosse R.Ranganath R.Raina A.Battle B.Packer J.Ngiam M.Kim J.Nam Y.Cao C.C.Lin H.Chiu J.Hu
Talks about:learn (8) machin (3) represent (2) boltzmann (2) deep (2) unsupervis (1) disentangl (1) transform (1) transfer (1) structur (1)
Person: Honglak Lee
DBLP: Lee:Honglak
Contributed to:
2014201320122011
201020092007Wrote 8 papers:
- ICML-c2-2014-MittelmanKSL #strict
- Structured Recurrent Temporal Restricted Boltzmann Machines (RM, BK, SS, HL), pp. 1647–1655.
- ICML-c2-2014-ReedSZL #interactive #learning
- Learning to Disentangle Factors of Variation with Manifold Interaction (SR, KS, YZ, HL), pp. 1431–1439.
- ICML-c2-2013-SohnZLL #learning
- Learning and Selecting Features Jointly with Point-wise Gated Boltzmann Machines (KS, GZ, CL, HL), pp. 217–225.
- ICML-2012-SohnL #invariant #learning
- Learning Invariant Representations with Local Transformations (KS, HL), p. 174.
- ICML-2011-NgiamKKNLN #learning #multimodal
- Multimodal Deep Learning (JN, AK, MK, JN, HL, AYN), pp. 689–696.
- KDD-2010-KhoslaCLCHL #approach #machine learning #predict
- An integrated machine learning approach to stroke prediction (AK, YC, CCYL, HKC, JH, HL), pp. 183–192.
- ICML-2009-LeeGRN #learning #network #scalability
- Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations (HL, RBG, RR, AYN), pp. 609–616.
- ICML-2007-RainaBLPN #learning #self
- Self-taught learning: transfer learning from unlabeled data (RR, AB, HL, BP, AYN), pp. 759–766.