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PAKDD
2009
ACM
171views Data Mining» more  PAKDD 2009»
14 years 3 months ago
Detecting Abnormal Events via Hierarchical Dirichlet Processes
Abstract. Detecting abnormal event from video sequences is an important problem in computer vision and pattern recognition and a large number of algorithms have been devised to tac...
Xian-Xing Zhang, Hua Liu, Yang Gao, Derek Hao Hu
DAC
2010
ACM
14 years 2 months ago
On the costs and benefits of stochasticity in stream processing
With the end of clock-frequency scaling, parallelism has emerged as the key driver of chip-performance growth. Yet, several factors undermine efficient simultaneous use of onchip ...
Raj R. Nadakuditi, Igor L. Markov

Publication
233views
12 years 9 months ago
Sparse reward processes
We introduce a class of learning problems where the agent is presented with a series of tasks. Intuitively, if there is relation among those tasks, then the information gained duri...
Christos Dimitrakakis
CORR
2012
Springer
183views Education» more  CORR 2012»
12 years 6 months ago
Learning Determinantal Point Processes
Determinantal point processes (DPPs), which arise in random matrix theory and quantum physics, are natural models for subset selection problems where diversity is preferred. Among...
Alex Kulesza, Ben Taskar
ICCV
2007
IEEE
15 years 22 days ago
Real-time Body Tracking Using a Gaussian Process Latent Variable Model
In this paper, we present a tracking framework for capturing articulated human motions in real-time, without the need for attaching markers onto the subject's body. This is a...
Shaobo Hou, Aphrodite Galata, Fabrice Caillette, N...