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ICANN
2005
Springer
15 years 5 months ago
A Neural Network Model for Inter-problem Adaptive Online Time Allocation
One aim of Meta-learning techniques is to minimize the time needed for problem solving, and the effort of parameter hand-tuning, by automating algorithm selection. The predictive m...
Matteo Gagliolo, Jürgen Schmidhuber
RTCSA
2008
IEEE
15 years 6 months ago
Impact of Cache Partitioning on Multi-tasking Real Time Embedded Systems
Cache partitioning techniques have been proposed in the past as a solution for the cache interference problem. Due to qualitative differences with general purpose platforms, real-...
Bach Duy Bui, Marco Caccamo, Lui Sha, Joseph Marti...
88
Voted
POPL
2010
ACM
15 years 6 months ago
Compress-and-conquer for optimal multicore computing
We propose a programming paradigm called compress-and-conquer (CC) that leads to optimal performance on multicore platforms. Given a multicore system of p cores and a problem of s...
Zhijing G. Mou, Hai Liu, Paul Hudak
JAIR
2000
102views more  JAIR 2000»
14 years 11 months ago
A Model of Inductive Bias Learning
A major problem in machine learning is that of inductive bias: how to choose a learner's hypothesis space so that it is large enough to contain a solution to the problem bein...
Jonathan Baxter
ICDM
2008
IEEE
110views Data Mining» more  ICDM 2008»
15 years 6 months ago
Start Globally, Optimize Locally, Predict Globally: Improving Performance on Imbalanced Data
Class imbalance is a ubiquitous problem in supervised learning and has gained wide-scale attention in the literature. Perhaps the most prevalent solution is to apply sampling to t...
David A. Cieslak, Nitesh V. Chawla