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EMNLP
2011
14 years 4 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 4 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 9 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
138
Voted
ICML
1998
IEEE
16 years 5 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»
15 years 11 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...