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EMNLP
2011
14 years 6 months ago
Training a Log-Linear Parser with Loss Functions via Softmax-Margin
Log-linear parsing models are often trained by optimizing likelihood, but we would prefer to optimise for a task-specific metric like Fmeasure. Softmax-margin is a convex objecti...
Michael Auli, Adam Lopez
HPCA
2005
IEEE
16 years 7 months ago
Transition Phase Classification and Prediction
Most programs are repetitive, where similar behavior can be seen at different execution times. Proposed on-line systems automatically group these similar intervals of execution in...
Jeremy Lau, Stefan Schoenmackers, Brad Calder
ICRA
2002
IEEE
147views Robotics» more  ICRA 2002»
15 years 11 months ago
Design of Asymptotically Stable Walking for a 5-Link Planar Biped Walker via Optimization
— Closed-loop, asymptotically stable walking motions are designed for a 5-link, planar bipedal robot model with one degree of underactuation. Parameter optimization is applied to...
E. R. Westervelt, J. W. Grizzle
ICML
1998
IEEE
16 years 7 months ago
Q2: Memory-Based Active Learning for Optimizing Noisy Continuous Functions
This paper introduces a new algorithm, Q2, foroptimizingthe expected output ofamultiinput noisy continuous function. Q2 is designed to need only a few experiments, it avoids stron...
Andrew W. Moore, Jeff G. Schneider, Justin A. Boya...
GECCO
2009
Springer
138views Optimization» more  GECCO 2009»
16 years 1 months ago
IMAD: in-execution malware analysis and detection
The sophistication of computer malware is becoming a serious threat to the information technology infrastructure, which is the backbone of modern e-commerce systems. We, therefore...
Syed Bilal Mehdi, Ajay Kumar Tanwani, Muddassar Fa...