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» On the Complexity of Function Learning
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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...
FOCS
2008
IEEE
14 years 4 months ago
Hardness of Minimizing and Learning DNF Expressions
We study the problem of finding the minimum size DNF formula for a function f : {0, 1}d → {0, 1} given its truth table. We show that unless NP ⊆ DTIME(npoly(log n) ), there i...
Subhash Khot, Rishi Saket
JMLR
2006
134views more  JMLR 2006»
13 years 10 months ago
Considering Cost Asymmetry in Learning Classifiers
Receiver Operating Characteristic (ROC) curves are a standard way to display the performance of a set of binary classifiers for all feasible ratios of the costs associated with fa...
Francis R. Bach, David Heckerman, Eric Horvitz
RECSYS
2010
ACM
13 years 7 months ago
List-wise learning to rank with matrix factorization for collaborative filtering
A ranking approach, ListRank-MF, is proposed for collaborative filtering that combines a list-wise learning-to-rank algorithm with matrix factorization (MF). A ranked list of item...
Yue Shi, Martha Larson, Alan Hanjalic
COLT
1993
Springer
14 years 2 months ago
Parameterized Learning Complexity
We describe three applications in computational learning theory of techniques and ideas recently introduced in the study of parameterized computational complexity. (1) Using param...
Rodney G. Downey, Patricia A. Evans, Michael R. Fe...