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» The Kernel Least-Mean-Square Algorithm
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TIP
2008
128views more  TIP 2008»
15 years 4 months ago
Wavelet Frame Accelerated Reduced Support Vector Machines
In this paper, a novel method for reducing the runtime complexity of a support vector machine classifier is presented. The new training algorithm is fast and simple. This is achiev...
Matthias Rätsch, Gerd Teschke, Sami Romdhani,...
SIMPRA
1998
99views more  SIMPRA 1998»
15 years 3 months ago
Rollback overhead reduction methods for time warp distributed simulation
Parallel discrete event simulation is a useful technique to improve performance of sequential discrete event simulation. We consider the Time Warp algorithm for asynchronous distr...
Simonetta Balsamo, C. Manconi
MFCS
2010
Springer
15 years 2 months ago
Solving minones-2-sat as Fast as vertex cover
The problem of finding a satisfying assignment for a 2-SAT formula that minimizes the number of variables that are set to 1 (min ones 2–sat) is NP-complete. It generalizes the w...
Neeldhara Misra, N. S. Narayanaswamy, Venkatesh Ra...
CORR
2010
Springer
163views Education» more  CORR 2010»
15 years 2 months ago
Faster Rates for training Max-Margin Markov Networks
Structured output prediction is an important machine learning problem both in theory and practice, and the max-margin Markov network (M3 N) is an effective approach. All state-of-...
Xinhua Zhang, Ankan Saha, S. V. N. Vishwanathan
ICML
2005
IEEE
16 years 5 months ago
Combining model-based and instance-based learning for first order regression
T ORDER REGRESSION (EXTENDED ABSTRACT) Kurt Driessensa Saso Dzeroskib a Department of Computer Science, University of Waikato, Hamilton, New Zealand (kurtd@waikato.ac.nz) b Departm...
Kurt Driessens, Saso Dzeroski