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FOCS
2008
IEEE
15 years 10 months ago
What Can We Learn Privately?
Learning problems form an important category of computational tasks that generalizes many of the computations researchers apply to large real-life data sets. We ask: what concept ...
Shiva Prasad Kasiviswanathan, Homin K. Lee, Kobbi ...
SIAMSC
2010
129views more  SIAMSC 2010»
15 years 2 months ago
A Micro-Macro Decomposition-Based Asymptotic-Preserving Scheme for the Multispecies Boltzmann Equation
In this paper we extend the micro-macro decomposition based asymptotic-preserving scheme developed in [3] for the single species Boltzmann equation to the multispecies problems. A...
Shi Jin, Yingzhe Shi
CP
2007
Springer
15 years 10 months ago
Encodings of the Sequence Constraint
Abstract. The SEQUENCE constraint is useful in modelling car sequencing, rostering, scheduling and related problems. We introduce half a dozen new encodings of the SEQUENCE constra...
Sebastian Brand, Nina Narodytska, Claude-Guy Quimp...
JMLR
2008
209views more  JMLR 2008»
15 years 3 months ago
Bayesian Inference and Optimal Design for the Sparse Linear Model
The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maxim...
Matthias W. Seeger
KDD
2006
ACM
159views Data Mining» more  KDD 2006»
16 years 4 months ago
Global distance-based segmentation of trajectories
This work introduces distance-based criteria for segmentation of object trajectories. Segmentation leads to simplification of the original objects into smaller, less complex primi...
Aris Anagnostopoulos, Michail Vlachos, Marios Hadj...