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133
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ICML
2009
IEEE
16 years 4 months ago
Structure learning of Bayesian networks using constraints
This paper addresses exact learning of Bayesian network structure from data and expert's knowledge based on score functions that are decomposable. First, it describes useful ...
Cassio Polpo de Campos, Zhi Zeng, Qiang Ji
WINE
2005
Springer
206views Economy» more  WINE 2005»
15 years 9 months ago
Exchange Market Equilibria with Leontief's Utility: Freedom of Pricing Leads to Rationality
This paper studies the equilibrium property and algorithmic complexity of the exchange market equilibrium problem with concave piece-wise linear functions, which include linear an...
Yinyu Ye
IPPS
1998
IEEE
15 years 7 months ago
Processor Lower Bound Formulas for Array Computations and Parametric Diophantine Systems
Using a directed acyclic graph (dag) model of algorithms, we solve a problem related to precedenceconstrained multiprocessor schedules for array computations: Given a sequence of ...
Peter R. Cappello, Ömer Egecioglu
127
Voted
LISP
2008
104views more  LISP 2008»
15 years 3 months ago
Flattening tuples in an SSA intermediate representation
For functional programs, unboxing aggregate data structures such as tuples removes memory indirections and frees dead components of the decoupled structures. To explore the consequ...
Lukasz Ziarek, Stephen Weeks, Suresh Jagannathan
123
Voted
SIAMJO
2002
124views more  SIAMJO 2002»
15 years 3 months ago
The Sample Average Approximation Method for Stochastic Discrete Optimization
In this paper we study a Monte Carlo simulation based approach to stochastic discrete optimization problems. The basic idea of such methods is that a random sample is generated and...
Anton J. Kleywegt, Alexander Shapiro, Tito Homem-d...