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ICCV
2007
IEEE
16 years 9 months ago
Gradient Feature Selection for Online Boosting
Boosting has been widely applied in computer vision, especially after Viola and Jones's seminal work [23]. The marriage of rectangular features and integral-imageenabled fast...
Ting Yu, Xiaoming Liu 0002
DMIN
2006
131views Data Mining» more  DMIN 2006»
15 years 8 months ago
Use of Data Mining to Determine Cheating in Online Student Assessment
are proposing a model to help organizations detect and prevent cheats in online assessments. First we analyze different student personalities, stress situations generated by onlin...
Alberto Ochoa, Amol Wagholikar
IJOE
2011
118views more  IJOE 2011»
15 years 2 months ago
Three Online Neutron Beam Experiments Based on the iLab Shared Architecture
- Students at MIT have traditionally executed certain experiments in the containment building of the MIT nuclear reactor as part of courses in Nuclear Engineering and the third yea...
Kimberly DeLong, Judson V. Harward, Philip H. Bail...
ICAART
2010
INSTICC
16 years 4 months ago
Complexity of Stochastic Branch and Bound Methods for Belief Tree Search in Bayesian Reinforcement Learning
There has been a lot of recent work on Bayesian methods for reinforcement learning exhibiting near-optimal online performance. The main obstacle facing such methods is that in most...
Christos Dimitrakakis
ECAI
2006
Springer
15 years 11 months ago
Learning by Automatic Option Discovery from Conditionally Terminating Sequences
Abstract. This paper proposes a novel approach to discover options in the form of conditionally terminating sequences, and shows how they can be integrated into reinforcement learn...
Sertan Girgin, Faruk Polat, Reda Alhajj