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ECCV
2010
Springer
15 years 6 months ago
MIForests: Multiple-Instance Learning with Randomized Trees
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
Christian Leistner, Amir Saffari, Horst Bischof
IJACDT
2011
125views more  IJACDT 2011»
14 years 10 months ago
Becoming Creative through Self Observation: A (Second Order) Cybernetic Learning Strategy for the Metaverse
This study wishes to describe some of the key components of an art educational domain entitled ground<c>, which is being developed specifically for three dimensional online ...
Elif E. Ayiter
HT
2000
ACM
15 years 11 months ago
Reusable hypertext structures for distance and JIT learning
Software components for distance and just-in-time (JIT) learning are an increasingly common method of encouraging reuse and facilitating the development process[58], but no analog...
Anne Morgan Spalter, Rosemary Michelle Simpson
CE
2008
128views more  CE 2008»
15 years 6 months ago
Beyond threaded discussion: Representational guidance in asynchronous collaborative learning environments
Although most online learning environments are predominately text based, researchers have argued that representational support for the conceptual structure of a problem would addr...
Daniel D. Suthers, Ravi K. Vatrapu, Richard Medina...
ICS
2005
Tsinghua U.
16 years 4 days ago
What is worth learning from parallel workloads?: a user and session based analysis
Learning useful and predictable features from past workloads and exploiting them well is a major source of improvement in many operating system problems. We review known parallel ...
Julia Zilber, Ofer Amit, David Talby