BibSLEIGH — Le

Travelled to:

1 × Australia
1 × Canada
1 × China
1 × Finland
1 × Israel
5 × USA

Collaborated with:

A.J.Smola E.P.Xing M.Gomez-Rodriguez A.Gretton M.Ishteva H.Park A.P.Parikh J.Epps N.Du B.Schölkopf K.M.Borgwardt E.B.Khalil B.N.Dilkina K.Zhou H.Zha W.Fu H.Daneshmand Y.Liang M.Balcan A.Anandkumar B.Dai B.Xie J.Huang K.Fukumizu M.Farajtabar A.Ahmed A.Agarwal S.M.Kakade N.Karampatziakis G.Valiant B.Boots S.M.Siddiqi G.J.Gordon X.Zhang J.Bedo

Talks about:

network (5) model (5) latent (4) diffus (4) learn (4) estim (4) multi (3) dynam (3) tree (3) algorithm (2)

Person: Le Song

DBLP: Song:Le

Contributed to:

2015

2014

2013

2011

2010

2009

2008

2007

2006

Wrote 18 papers:

KDD-2015-DuFASS #clustering #documentation #process: Dirichlet-Hawkes Processes with Applications to Clustering Continuous-Time Document Streams (ND, MF, AA, AJS, LS), pp. 219–228.
KDD-2015-Gomez-Rodriguez #machine learning #modelling #network #probability #problem #research #social: Diffusion in Social and Information Networks: Research Problems, Probabilistic Models and Machine Learning Methods (MGR, LS), pp. 2315–2316.
ICML-c2-2014-AgarwalKKSV #multi #predict #scalability: Least Squares Revisited: Scalable Approaches for Multi-class Prediction (AA, SMK, NK, LS, GV), pp. 541–549.
ICML-c2-2014-DaneshmandGSS #algorithm #complexity #network: Estimating Diffusion Network Structures: Recovery Conditions, Sample Complexity & Soft-thresholding Algorithm (HD, MGR, LS, BS), pp. 793–801.
ICML-c2-2014-DuLBS #information management #learning #network: Influence Function Learning in Information Diffusion Networks (ND, YL, MFB, LS), pp. 2016–2024.
ICML-c2-2014-SongADX #estimation #modelling #multi #parametricity: Nonparametric Estimation of Multi-View Latent Variable Models (LS, AA, BD, BX), pp. 640–648.
KDD-2014-KhalilDS #network #optimisation #scalability: Scalable diffusion-aware optimization of network topology (EBK, BND, LS), pp. 1226–1235.
ICML-c3-2013-IshtevaPS #order #using: Unfolding Latent Tree Structures using 4th Order Tensors (MI, HP, LS), pp. 316–324.
ICML-c3-2013-SongIPXP #composition #modelling #visual notation: Hierarchical Tensor Decomposition of Latent Tree Graphical Models (LS, MI, APP, EPX, HP), pp. 334–342.
ICML-c3-2013-ZhouZS #kernel #learning #multi #process: Learning Triggering Kernels for Multi-dimensional Hawkes Processes (KZ, HZ, LS), pp. 1301–1309.
ICML-2011-ParikhSX #algorithm #modelling #visual notation: A Spectral Algorithm for Latent Tree Graphical Models (APP, LS, EPX), pp. 1065–1072.
ICML-2010-SongSGS #markov #modelling: Hilbert Space Embeddings of Hidden Markov Models (LS, BB, SMS, GJG, AJS), pp. 991–998.
ICML-2009-FuSX #evolution #network: Dynamic mixed membership blockmodel for evolving networks (WF, LS, EPX), pp. 329–336.
ICML-2009-SongHSF: Hilbert space embeddings of conditional distributions with applications to dynamical systems (LS, JH, AJS, KF), pp. 961–968.
ICML-2008-SongZSGS #estimation #kernel: Tailoring density estimation via reproducing kernel moment matching (LS, XZ, AJS, AG, BS), pp. 992–999.
ICML-2007-SongSGB #clustering #dependence: A dependence maximization view of clustering (LS, AJS, AG, KMB), pp. 815–822.
ICML-2007-SongSGBB #dependence #estimation #feature model: Supervised feature selection via dependence estimation (LS, AJS, AG, KMB, JB), pp. 823–830.
ICML-2006-SongE #human-computer #interface #learning: Classifying EEG for brain-computer interfaces: learning optimal filters for dynamical system features (LS, JE), pp. 857–864.