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» Parameterized Learning Complexity
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APCHI
2004
IEEE
15 years 6 months ago
Designing for Flow in a Complex Activity
One component of a user's interaction with computer systems is commonly referred to as `flow'. Flow is an important consideration in interactive system design as it enca...
Jon M. Pearce, Steve Howard
ICCV
2009
IEEE
15 years 6 days ago
Complex volume and pose tracking with probabilistic dynamical models and visual hull constraints
We propose a method for estimating the pose of a human body using its approximate 3D volume (visual hull) obtained in real time from synchronized videos. Our method can cope with ...
Norimichi Ukita, Michiro Hirai, Masatsugu Kidode
CVPR
2012
IEEE
13 years 4 months ago
Complex loss optimization via dual decomposition
We describe a novel max-margin parameter learning approach for structured prediction problems under certain non-decomposable performance measures. Structured prediction is a commo...
Mani Ranjbar, Arash Vahdat, Greg Mori
JMLR
2010
144views more  JMLR 2010»
14 years 9 months ago
Maximum Margin Learning with Incomplete Data: Learning Networks instead of Tables
In this paper we address the problem of predicting when the available data is incomplete. We show that changing the generally accepted table-wise view of the sample items into a g...
Sándor Szedmák, Yizhao Ni, Steve R. ...
ATAL
2005
Springer
15 years 8 months ago
Improving reinforcement learning function approximators via neuroevolution
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Shimon Whiteson