`Travelled to:`

1 × Australia

1 × Austria

1 × France

1 × Germany

1 × Ireland

1 × Spain

1 × Turkey

2 × Canada

2 × China

8 × USA

`Collaborated with:`

M.Deodhar K.D.Bollacker S.Merugu I.S.Dhillon A.Banerjee S.Acharyya G.Jun G.Gupta S.Gunasekar Y.Park ∅ V.Ramamurti K.Tumer J.Sun S.Basu R.J.Mooney P.Ravikumar J.C.Ho O.Koyejo S.Raghavan V.Radosavljevic Z.Obradovic S.Daruru N.M.Marin M.Walker S.Sra K.V.Pasupuleti H.Cho C.Krumpelman D.S.Modha Y.Wang R.Chen J.C.Denny A.N.Kho Y.Chen B.A.Malin

`Talks about:`

data (10) cluster (7) mine (4) base (4) framework (3) knowledg (3) predict (3) matrix (3) health (3) famili (3)

## Person: Joydeep Ghosh

### DBLP: Ghosh:Joydeep

### Facilitated 1 volumes:

### Contributed to:

### Wrote 25 papers:

- KDD-2015-WangCGDKCMS #data analysis #health #named
- Rubik: Knowledge Guided Tensor Factorization and Completion for Health Data Analytics (YW, RC, JG, JCD, ANK, YC, BAM, JS), pp. 1265–1274.
- ICML-c2-2014-GunasekarRG #constraints #exponential #matrix #product line
- Exponential Family Matrix Completion under Structural Constraints (SG, PR, JG), pp. 1917–1925.
- KDD-2014-HoGS #health #named
- Marble: high-throughput phenotyping from electronic health records via sparse nonnegative tensor factorization (JCH, JG, JS), pp. 115–124.
- KDD-2014-ParkG #algorithm #health #named #rank #re-engineering
- LUDIA: an aggregate-constrained low-rank reconstruction algorithm to leverage publicly released health data (YP, JG), pp. 55–64.
- RecSys-2013-KoyejoAG #collaboration #matrix
- Retargeted matrix factorization for collaborative filtering (OK, SA, JG), pp. 49–56.
- RecSys-2012-RaghavanGG #collaboration #overview #quality
- Review quality aware collaborative filtering (SR, SG, JG), pp. 123–130.
- ICPR-2010-JunG #classification #process
- Nearest-Manifold Classification with Gaussian Processes (GJ, JG), pp. 914–917.
- KDIR-2010-Ghosh #locality #mining #modelling #multi #predict #scalability #using
- Actionable Mining of Large, Multi-relational Data using Localized Predictive Models (JG), pp. 9–10.
- KDIR-2010-JunGRO #image #predict #process
- Predicting Ground-based Aerosol Optical Depth with Satellite Images Via Gaussian Processes (GJ, JG, VR, ZO), pp. 370–375.
- ICML-2009-DeodharGGCD #clustering #framework #scalability #semistructured data
- A scalable framework for discovering coherent co-clusters in noisy data (MD, GG, JG, HC, ISD), pp. 241–248.
- KDD-2009-DaruruMWG #clustering #data flow #data mining #mining #parallel #pervasive #scalability
- Pervasive parallelism in data mining: dataflow solution to co-clustering large and sparse Netflix data (SD, NMM, MW, JG), pp. 1115–1124.
- KDD-2009-DeodharG #mining #predict
- Mining for the most certain predictions from dyadic data (MD, JG), pp. 249–258.
- CIKM-2008-AcharyyaG #analysis #product line
- A spam resistant family of concavo-convex ranks for link analysis (SA, JG), pp. 1505–1506.
- KDD-2007-DeodharG #clustering #framework #learning
- A framework for simultaneous co-clustering and learning from complex data (MD, JG), pp. 250–259.
- ICML-2005-GuptaG #clustering #hybrid #robust #using
- Robust one-class clustering using hybrid global and local search (GG, JG), pp. 273–280.
- KDD-2005-BanerjeeKGBM #clustering #modelling
- Model-based overlapping clustering (AB, CK, JG, SB, RJM), pp. 532–537.
- KDD-2005-MeruguG #data flow #distributed #framework #learning #semistructured data
- A distributed learning framework for heterogeneous data sources (SM, JG), pp. 208–217.
- ICML-2004-BanerjeeDGM #analysis #estimation #exponential #product line
- An information theoretic analysis of maximum likelihood mixture estimation for exponential families (AB, ISD, JG, SM).
- KDD-2004-BanerjeeDGMM #approach #approximate #clustering #matrix
- A generalized maximum entropy approach to bregman co-clustering and matrix approximation (AB, ISD, JG, SM, DSM), pp. 509–514.
- KDD-2003-BanerjeeDGS #clustering #generative #modelling
- Generative model-based clustering of directional data (AB, ISD, JG, SS), pp. 19–28.
- KDD-2001-BasuMPG #using
- Evaluating the novelty of text-mined rules using lexical knowledge (SB, RJM, KVP, JG), pp. 233–238.
- ICML-1998-BollackerG #architecture #classification #reuse #scalability
- A Supra-Classifier Architecture for Scalable Knowledge Reuse (KDB, JG), pp. 64–72.
- ICPR-1996-BollackerG #linear
- Linear feature extractors based on mutual information (KDB, JG), pp. 720–724.
- ICPR-1996-RamamurtiG #adaptation
- Structural adaptation in mixture of experts (VR, JG), pp. 704–708.
- ICPR-1996-TumerG #classification #fault
- Estimating the Bayes error rate through classifier combining (KT, JG), pp. 695–699.