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» Learning from General Label Constraints
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EH
1999
IEEE
351views Hardware» more  EH 1999»
14 years 2 months ago
Evolvable Hardware or Learning Hardware? Induction of State Machines from Temporal Logic Constraints
Here we advocate an approach to learning hardware based on induction of finite state machines from temporal logic constraints. The method involves training on examples, constraint...
Marek A. Perkowski, Alan Mishchenko, Anatoli N. Ch...
SIGIR
2012
ACM
12 years 7 days ago
Top-k learning to rank: labeling, ranking and evaluation
In this paper, we propose a novel top-k learning to rank framework, which involves labeling strategy, ranking model and evaluation measure. The motivation comes from the difficul...
Shuzi Niu, Jiafeng Guo, Yanyan Lan, Xueqi Cheng
ENGL
2007
148views more  ENGL 2007»
13 years 9 months ago
A General Reflex Fuzzy Min-Max Neural Network
—“A General Reflex Fuzzy Min-Max Neural Network” (GRFMN) is presented. GRFMN is capable to extract the underlying structure of the data by means of supervised, unsupervised a...
Abhijeet V. Nandedkar, Prabir Kumar Biswas
UIST
1994
ACM
14 years 1 months ago
Evolutionary Learning of Graph Layout Constraints from Examples
We propose a new evolutionary method of extracting user preferences from examples shown to an automatic graph layout system. Using stochastic methods such as simulated annealing a...
Toshiyuki Masui
GFKL
2007
Springer
148views Data Mining» more  GFKL 2007»
14 years 4 months ago
Information Integration of Partially Labeled Data
Abstract. A central task when integrating data from different sources is to detect identical items. For example, price comparison websites have to identify offers for identical p...
Steffen Rendle, Lars Schmidt-Thieme