Travelled to:1 × Austria
1 × China
1 × France
1 × Korea
10 × USA
2 × Greece
Collaborated with:S.Guha J.Widom U.Srivastava J.Yang S.Babu S.Gollapudi A.Silberstein A.Meyerson R.Motwani S.Im J.Kulkarni K.Bhawalkar Y.Zhang A.Goel S.Bhattacharya G.Goel M.Ahmad A.Aboulnaga A.E.Gelfand G.Puggioni I.Nishizawa V.Arya N.Garg R.Khandekar V.Pandit
Talks about:queri (4) problem (3) optim (3) data (3) algorithm (2) competit (2) approxim (2) network (2) exploit (2) system (2)
Person: Kamesh Munagala
DBLP: Munagala:Kamesh
Contributed to:
20142013
20112010
2009
2009
2009
2008200720072007200620062006200520042001Wrote 18 papers:
- STOC-2014-ImKM #algorithm #constraints #scheduling
- Competitive algorithms from competitive equilibria: non-clairvoyant scheduling under polyhedral constraints (SI, JK, KM), pp. 313–322.
- STOC-2013-BhawalkarGM #game studies
- Coevolutionary opinion formation games (KB, SG, KM), pp. 41–50.
- VLDB-2011-ZhangM0 #matrix #revisited #theory and practice
- Storing Matrices on Disk: Theory and Practice Revisited (YZ, KM, JY), pp. 1075–1086.
- STOC-2010-BhattacharyaGGM
- Budget constrained auctions with heterogeneous items (SB, GG, SG, KM), pp. 379–388.
- ICALP-v2-2009-GuhaM #metric #multi
- Multi-armed Bandits with Metric Switching Costs (SG, KM), pp. 496–507.
- PODS-2009-GuhaM #clustering #nondeterminism
- Exceeding expectations and clustering uncertain data (SG, KM), pp. 269–278.
- SIGMOD-2009-BabuGM #learning #nondeterminism #scalability
- Large-scale uncertainty management systems: learning and exploiting your data (SB, SG, KM), pp. 995–998.
- CIKM-2008-AhmadABM #database #interactive #modelling #query
- Modeling and exploiting query interactions in database systems (MA, AA, SB, KM), pp. 183–192.
- PODS-2007-MunagalaSW #optimisation #query
- Optimization of continuous queries with shared expensive filters (KM, US, JW), pp. 215–224.
- STOC-2007-GuhaM #algorithm #approximate #learning #problem
- Approximation algorithms for budgeted learning problems (SG, KM), pp. 104–113.
- VLDB-2007-SilbersteinGMPY #approach
- Making Sense of Suppressions and Failures in Sensor Data: A Bayesian Approach (AS, AEG, KM, GP, JY), pp. 842–853.
- PODS-2006-GoelGM #modelling #optimisation #using
- Asking the right questions: model-driven optimization using probes (AG, SG, KM), pp. 203–212.
- SIGMOD-2006-SilbersteinMY #energy #monitoring #network
- Energy-efficient monitoring of extreme values in sensor networks (AS, KM, JY), pp. 169–180.
- VLDB-2006-SrivastavaMWM #optimisation #query #web #web service
- Query Optimization over Web Services (US, KM, JW, RM), pp. 355–366.
- PODS-2005-SrivastavaMW #query
- Operator placement for in-network stream query processing (US, KM, JW), pp. 250–258.
- SIGMOD-2004-BabuMMNW #adaptation #pipes and filters
- Adaptive Ordering of Pipelined Stream Filters (SB, RM, KM, IN, JW), pp. 407–418.
- STOC-2001-AryaGKMP #heuristic #problem
- Local search heuristic for k-median and facility location problems (VA, NG, RK, AM, KM, VP), pp. 21–29.
- STOC-2001-GuhaMM #approximate #constant #problem
- A constant factor approximation for the single sink edge installation problems (SG, AM, KM), pp. 383–388.