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ICDM
2008
IEEE
110views Data Mining» more  ICDM 2008»
13 years 10 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
CAL
2002
13 years 3 months ago
Migration in Single Chip Multiprocessors
Global communication costs in future single-chip multiprocessors will increase linearly with distance. In this paper, we revisit the issues of locality and load balance in order to...
K. A. Shaw, William J. Dally
ICIP
2009
IEEE
14 years 4 months ago
Improved Global Cardiac Tractography With Simulated Annealing
We propose a new fibre tracking algorithm for cardiac DTMRI that parts with the locally "greedy" paradigm intrinsic to conventional tracking algorithms. We formulate the...
IEEEPACT
1998
IEEE
13 years 8 months ago
A Matrix-Based Approach to the Global Locality Optimization Problem
Global locality analysis is a technique for improving the cache performance of a sequence of loop nests through a combination of loop and data layout optimizations. Pure loop tran...
Mahmut T. Kandemir, Alok N. Choudhary, J. Ramanuja...
AAAI
1998
13 years 5 months ago
Learning Evaluation Functions for Global Optimization and Boolean Satisfiability
This paper describes STAGE, a learning approach to automatically improving search performance on optimization problems.STAGElearns an evaluation function which predicts the outcom...
Justin A. Boyan, Andrew W. Moore