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» Nested Ordered Sets and their Use for Data Modelling
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JMLR
2012
13 years 8 months ago
Structured Output Learning with High Order Loss Functions
Often when modeling structured domains, it is desirable to leverage information that is not naturally expressed as simply a label. Examples include knowledge about the evaluation ...
Daniel Tarlow, Richard S. Zemel
ICDE
2009
IEEE
159views Database» more  ICDE 2009»
16 years 7 months ago
Sketch-Based Summarization of Ordered XML Streams
XML streams, such as RSS feeds or complex event streams, are becoming increasingly pervasive as they provide the foundation for a wide range of emerging applications. An important...
Veronica Mayorga, Neoklis Polyzotis
BMCBI
2008
136views more  BMCBI 2008»
15 years 6 months ago
A comparison of machine learning algorithms for chemical toxicity classification using a simulated multi-scale data model
Background: Bioactivity profiling using high-throughput in vitro assays can reduce the cost and time required for toxicological screening of environmental chemicals and can also r...
Richard Judson, Fathi Elloumi, R. Woodrow Setzer, ...
HYBRID
1998
Springer
15 years 10 months ago
High Order Eigentensors as Symbolic Rules in Competitive Learning
We discuss properties of high order neurons in competitive learning. In such neurons, geometric shapes replace the role of classic `point' neurons in neural networks. Complex ...
Hod Lipson, Hava T. Siegelmann
ASIAMS
2009
IEEE
15 years 11 months ago
Evolutionary-Reduced Ordered Binary Decision Diagram
—Reduced ordered binary decision diagram (ROBDD) is a memory-efficient data structure which is used in many applications such as synthesis, digital system, verification, testing ...
Hossein Moeinzadeh, Mehdi Mohammadi, Hossein Pazho...