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» Introduction to Functional Programming
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ICS
1999
Tsinghua U.
15 years 10 months ago
Improving virtual function call target prediction via dependence-based pre-computation
We introduce dependence-based pre-computation as a complement to history-based target prediction schemes. We present pre-computation in the context of virtual function calls (v-ca...
Amir Roth, Andreas Moshovos, Gurindar S. Sohi
179
Voted
DAC
2004
ACM
15 years 10 months ago
Probabilistic regression suites for functional verification
Random test generators are often used to create regression suites on-the-fly. Regression suites are commonly generated by choosing several specifications and generating a number o...
Shai Fine, Shmuel Ur, Avi Ziv
179
Voted
ECAI
2010
Springer
15 years 7 months ago
Learning Aggregation Functions for Expert Search
Abstract. Machine learning techniques are increasingly being applied to problems in the domain of information retrieval and text mining. In this paper we present an application of ...
Ronan Cummins, Mounia Lalmas, Colm O'Riordan
ICRA
2010
IEEE
100views Robotics» more  ICRA 2010»
15 years 4 months ago
Weighted barrier functions for computation of force distributions with friction cone constraints
— We present a novel Weighted Barrier Function (WBF) method of efficiently computing optimal grasping force distributions for multifingered hands. Second-order conic friction c...
Per Henrik Borgstrom, Maxim A. Batalin, Gaurav S. ...
150
Voted
CEC
2009
IEEE
16 years 1 months ago
Self modifying Cartesian Genetic Programming: Parity
— Self Modifying CGP (SMCGP) is a developmental form of Cartesian Genetic Programming(CGP). It differs from CGP by including primitive functions which modify the program. Beginni...
Simon Harding, Julian Francis Miller, Wolfgang Ban...