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KDD
2006
ACM
163views Data Mining» more  KDD 2006»
16 years 6 months ago
New EM derived from Kullback-Leibler divergence
We introduce a new EM framework in which it is possible not only to optimize the model parameters but also the number of model components. A key feature of our approach is that we...
Longin Jan Latecki, Marc Sobel, Rolf Lakämper
KDD
2006
ACM
136views Data Mining» more  KDD 2006»
16 years 6 months ago
Very sparse random projections
There has been considerable interest in random projections, an approximate algorithm for estimating distances between pairs of points in a high-dimensional vector space. Let A Rn...
Ping Li, Trevor Hastie, Kenneth Ward Church
STOC
2002
ACM
149views Algorithms» more  STOC 2002»
16 years 6 months ago
The complexity of choosing an H-colouring (nearly) uniformly at random
Cooper, Dyer and Frieze studied the problem of sampling H-colourings (nearly) uniformly at random. Special cases of this problem include sampling colourings and independent sets a...
Leslie Ann Goldberg, Steven Kelk, Mike Paterson
OSDI
2008
ACM
16 years 6 months ago
Probabilistic Inference in Queueing Networks
Although queueing models have long been used to model the performance of computer systems, they are out of favor with practitioners, because they have a reputation for requiring u...
Charles A. Sutton, Michael I. Jordan
VLDB
2007
ACM
181views Database» more  VLDB 2007»
16 years 6 months ago
STAR: Self-Tuning Aggregation for Scalable Monitoring
We present STAR, a self-tuning algorithm that adaptively sets numeric precision constraints to accurately and efficiently answer continuous aggregate queries over distributed data...
Navendu Jain, Michael Dahlin, Yin Zhang, Dmitry Ki...