90,376 research outputs found
Pac-Learning Recursive Logic Programs: Efficient Algorithms
We present algorithms that learn certain classes of function-free recursive
logic programs in polynomial time from equivalence queries. In particular, we
show that a single k-ary recursive constant-depth determinate clause is
learnable. Two-clause programs consisting of one learnable recursive clause and
one constant-depth determinate non-recursive clause are also learnable, if an
additional ``basecase'' oracle is assumed. These results immediately imply the
pac-learnability of these classes. Although these classes of learnable
recursive programs are very constrained, it is shown in a companion paper that
they are maximally general, in that generalizing either class in any natural
way leads to a computationally difficult learning problem. Thus, taken together
with its companion paper, this paper establishes a boundary of efficient
learnability for recursive logic programs.Comment: See http://www.jair.org/ for any accompanying file
Automatic Classification of Text Databases through Query Probing
Many text databases on the web are "hidden" behind search interfaces, and
their documents are only accessible through querying. Search engines typically
ignore the contents of such search-only databases. Recently, Yahoo-like
directories have started to manually organize these databases into categories
that users can browse to find these valuable resources. We propose a novel
strategy to automate the classification of search-only text databases. Our
technique starts by training a rule-based document classifier, and then uses
the classifier's rules to generate probing queries. The queries are sent to the
text databases, which are then classified based on the number of matches that
they produce for each query. We report some initial exploratory experiments
that show that our approach is promising to automatically characterize the
contents of text databases accessible on the web.Comment: 7 pages, 1 figur
High Performance Turboalternator and Associated Hardware. 1 - Design of Turboalternator
Performance of two stage axial flow turbogenerator with gas bearing rotor support syste
Pac-learning Recursive Logic Programs: Negative Results
In a companion paper it was shown that the class of constant-depth
determinate k-ary recursive clauses is efficiently learnable. In this paper we
present negative results showing that any natural generalization of this class
is hard to learn in Valiant's model of pac-learnability. In particular, we show
that the following program classes are cryptographically hard to learn:
programs with an unbounded number of constant-depth linear recursive clauses;
programs with one constant-depth determinate clause containing an unbounded
number of recursive calls; and programs with one linear recursive clause of
constant locality. These results immediately imply the non-learnability of any
more general class of programs. We also show that learning a constant-depth
determinate program with either two linear recursive clauses or one linear
recursive clause and one non-recursive clause is as hard as learning boolean
DNF. Together with positive results from the companion paper, these negative
results establish a boundary of efficient learnability for recursive
function-free clauses.Comment: See http://www.jair.org/ for any accompanying file
The face, beauty, and symmetry: Perceiving asymmetry in beautiful faces
The relationship between bilateral facial symmetry and beauty remains to be clarified. Here, straight head-on photographs of “beautiful” faces from the collections of professional modeling agencies were selected. First, beauty ratings were obtained for these faces. Then, the authors created symmetrical left-left and right-right composites of the beautiful faces and asked a new group of subjects to choose the most attractive pair member. “Same” responses were allowed. No difference between the left-left and right-right composites was revealed but significant differences were obtained between “same” and the left-left or right-right. These results show that subjects detected asymmetry in beauty and suggest that very beautiful faces can be functionally asymmetrical
Calculation of skin-stiffener interface stresses in stiffened composite panels
A method for computing the skin-stiffener interface stresses in stiffened composite panels is developed. Both geometrically linear and nonlinear analyses are considered. Particular attention is given to the flange termination region where stresses are expected to exhibit unbounded characteristics. The method is based on a finite-element analysis and an elasticity solution. The finite-element analysis is standard, while the elasticity solution is based on an eigenvalue expansion of the stress functions. The eigenvalue expansion is assumed to be valid in the local flange termination region and is coupled with the finite-element analysis using collocation of stresses on the local region boundaries. Accuracy and convergence of the local elasticity solution are assessed using a geometrically linear analysis. Using this analysis procedure, the influence of geometric nonlinearities and stiffener parameters on the skin-stiffener interface stresses is evaluated
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