BibSLEIGH corpus
BibSLEIGH tags
BibSLEIGH bundles
BibSLEIGH people
Open Knowledge
XHTML 1.0 W3C Rec
CSS 2.1 W3C CanRec
email twitter
Travelled to:
1 × China
1 × Greece
12 × USA
2 × Australia
2 × France
Collaborated with:
B.Chen N.Kota X.Wang P.Elango L.Zhang D.Chakrabarti S.Merugu R.Khanna J.Yang V.Josifovski B.Long Y.Low A.J.Smola Z.Lu I.S.Dhillon S.Pandey S.Ghosh K.Wei S.You R.Agrawal Y.Moshfeghi B.Piwowarski J.M.Jose A.K.Menon K.P.Chitrapura S.Garg D.Chen L.Lin J.Shanmugasundaram E.Vee E.Gabrilovich R.Hall A.McGregor J.M.Phillips S.Venkatasubramanian Z.Zhu Q.He Y.Ma P.Shivaswamy A.Z.Broder D.Diklic M.Sayyadian D.Barman D.Gunopulos N.E.Young F.Korn D.Srivastava A.Gupta D.Tan J.Kulesza R.Pathak S.Stefani V.Srinivasan Z.Hua G.Lebanon H.Tseng R.Gupta J.Hartman A.Iyer S.Kolar A.Singh
Talks about:
model (5) data (5) recommend (4) multipl (4) latent (4) factor (4) multi (4) estim (4) rate (4) hierarchi (3)

Person: Deepak Agarwal

DBLP DBLP: Agarwal:Deepak

Facilitated 1 volumes:

KDD 2012Ed

Contributed to:

KDD 20152015
SIGMOD 20152015
KDD 20142014
KDD 20132013
CIKM 20122012
SIGIR 20122012
KDD 20112011
RecSys 20112011
SIGMOD 20112011
KDD 20102010
SIGMOD 20102010
CIKM 20092009
ECIR 20092009
KDD 20092009
RecSys 20092009
ICML 20072007
KDD 20072007
KDD 20062006

Wrote 27 papers:

KDD-2015-Agarwal #machine learning #scalability #statistics #web
Scaling Machine Learning and Statistics for Web Applications (DA), p. 1621.
KDD-2015-AgarwalCHHLMSTY #personalisation
Personalizing LinkedIn Feed (DA, BCC, QH, ZH, GL, YM, PS, HPT, JY, LZ), pp. 1651–1660.
Amazon Redshift and the Case for Simpler Data Warehouses (AG, DA, DT, JK, RP, SS, VS), pp. 1917–1923.
KDD-2014-AgarwalCGHHIKMSSZ #process #ranking
Activity ranking in LinkedIn feed (DA, BCC, RG, JH, QH, AI, SK, YM, PS, AS, LZ), pp. 1603–1612.
KDD-2014-AgarwalGWY #online
Budget pacing for targeted online advertisements at LinkedIn (DA, SG, KW, SY), pp. 1613–1619.
KDD-2013-YangCA #social
Estimating sharer reputation via social data calibration (JY, BCC, DA), pp. 59–67.
CIKM-2012-AgarwalCW #multi #ranking #using
Multi-faceted ranking of news articles using post-read actions (DA, BCC, XW), pp. 694–703.
SIGIR-2012-AgarwalCEW #online #personalisation #recommendation
Personalized click shaping through lagrangian duality for online recommendation (DA, BCC, PE, XW), pp. 485–494.
KDD-2011-AgarwalCEW #multi
Click shaping to optimize multiple objectives (DA, BCC, PE, XW), pp. 132–140.
KDD-2011-AgarwalCL #locality #modelling #multi #recommendation
Localized factor models for multi-context recommendation (DA, BCC, BL), pp. 609–617.
KDD-2011-KotaA #multi
Temporal multi-hierarchy smoothing for estimating rates of rare events (NK, DA), pp. 1361–1369.
KDD-2011-LowAS #multi #personalisation
Multiple domain user personalization (YL, DA, AJS), pp. 123–131.
KDD-2011-MenonCGAK #collaboration #predict #using
Response prediction using collaborative filtering with hierarchies and side-information (AKM, KPC, SG, DA, NK), pp. 141–149.
RecSys-2011-ZhangAC #flexibility #matrix
Generalizing matrix factorization through flexible regression priors (LZ, DA, BCC), pp. 13–20.
Latent OLAP: data cubes over latent variables (DA, BCC), pp. 877–888.
KDD-2010-AgarwalAKK #modelling #multi #scalability
Estimating rates of rare events with multiple hierarchies through scalable log-linear models (DA, RA, RK, NK), pp. 213–222.
KDD-2010-AgarwalCE #learning #online #performance #recommendation
Fast online learning through offline initialization for time-sensitive recommendation (DA, BCC, PE), pp. 703–712.
Forecasting high-dimensional data (DA, DC, LjL, JS, EV), pp. 1003–1012.
Translating relevance scores to probabilities for contextual advertising (DA, EG, RH, VJ, RK), pp. 1899–1902.
ECIR-2009-MoshfeghiAPJ #collaboration #predict #rating #recommendation #semantics
Movie Recommender: Semantically Enriched Unified Relevance Model for Rating Prediction in Collaborative Filtering (YM, DA, BP, JMJ), pp. 54–65.
KDD-2009-AgarwalC #modelling
Regression-based latent factor models (DA, BCC), pp. 19–28.
RecSys-2009-LuAD #approach #collaboration
A spatio-temporal approach to collaborative filtering (ZL, DA, ISD), pp. 13–20.
ICML-2007-PandeyCA #multi #problem
Multi-armed bandit problems with dependent arms (SP, DC, DA), pp. 721–728.
KDD-2007-AgarwalBCDJS #multi
Estimating rates of rare events at multiple resolutions (DA, AZB, DC, DD, VJ, MS), pp. 16–25.
KDD-2007-AgarwalBGYKS #effectiveness #performance #summary
Efficient and effective explanation of change in hierarchical summaries (DA, DB, DG, NEY, FK, DS), pp. 6–15.
KDD-2007-AgarwalM #modelling #predict #scalability
Predictive discrete latent factor models for large scale dyadic data (DA, SM), pp. 26–35.
KDD-2006-AgarwalMPVZ #approximate #performance #statistics
Spatial scan statistics: approximations and performance study (DA, AM, JMP, SV, ZZ), pp. 24–33.

Bibliography of Software Language Engineering in Generated Hypertext (BibSLEIGH) is created and maintained by Dr. Vadim Zaytsev.
Hosted as a part of SLEBOK on GitHub.