Travelled to:
1 × Finland
1 × France
2 × China
3 × USA
Collaborated with:
E.Yang H.H.Pareek A.C.Lozano R.Tandon J.D.Lafferty A.Prasad D.Inouye I.S.Dhillon A.Agarwal M.J.Wainwright
Talks about:
estim (3) elementari (2) structur (2) program (2) linear (2) model (2) learn (2) graph (2) distribut (1) dimension (1)
Person: Pradeep D. Ravikumar
DBLP: Ravikumar:Pradeep_D=
Contributed to:
Wrote 9 papers:
- ICML-2015-PrasadPR #analysis #axiom #rank
- Distributional Rank Aggregation, and an Axiomatic Analysis (AP, HHP, PDR), pp. 2104–2112.
- ICML-c1-2014-InouyeRD #dependence #topic #word
- Admixture of Poisson MRFs: A Topic Model with Word Dependencies (DI, PDR, ISD), pp. 683–691.
- ICML-c1-2014-TandonR #graph #learning
- Learning Graphs with a Few Hubs (RT, PDR), pp. 602–610.
- ICML-c2-2014-YangLR #linear
- Elementary Estimators for High-Dimensional Linear Regression (EY, ACL, PDR), pp. 388–396.
- ICML-c2-2014-YangLR14a #matrix
- Elementary Estimators for Sparse Covariance Matrices and other Structured Moments (EY, ACL, PDR), pp. 397–405.
- ICML-c1-2013-PareekR
- Human Boosting (HHP, PDR), pp. 338–346.
- ICML-2011-YangR #learning #on the #using #visual notation
- On the Use of Variational Inference for Learning Discrete Graphical Model (EY, PDR), pp. 1009–1016.
- ICML-2008-RavikumarAW #convergence #linear #message passing #source code
- Message-passing for graph-structured linear programs: proximal projections, convergence and rounding schemes (PDR, AA, MJW), pp. 800–807.
- ICML-2006-RavikumarL #estimation #markov #metric #polynomial #programming #random
- Quadratic programming relaxations for metric labeling and Markov random field MAP estimation (PDR, JDL), pp. 737–744.