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CIE
2007
Springer
15 years 9 months ago
Input-Dependence in Function-Learning
In the standard model of inductive inference, a learner gets as input the graph of a function, and has to discover (in the limit) a program for the function. In this paper, we cons...
Sanjay Jain, Eric Martin, Frank Stephan
ALT
2007
Springer
15 years 12 months ago
Learning and Verifying Graphs Using Queries with a Focus on Edge Counting
We consider the problem of learning and verifying hidden graphs and their properties given query access to the graphs. We analyze various queries (edge detection, edge counting, sh...
Lev Reyzin, Nikhil Srivastava
108
Voted
FOCS
1994
IEEE
15 years 7 months ago
The Power of Team Exploration: Two Robots Can Learn Unlabeled Directed Graphs
We show that two cooperating robots can learn exactly any strongly-connected directed graph with n indistinguishable nodes in expected time polynomial in n. We introduce a new typ...
Michael A. Bender, Donna K. Slonim
JMLR
2010
144views more  JMLR 2010»
14 years 9 months ago
Maximum Margin Learning with Incomplete Data: Learning Networks instead of Tables
In this paper we address the problem of predicting when the available data is incomplete. We show that changing the generally accepted table-wise view of the sample items into a g...
Sándor Szedmák, Yizhao Ni, Steve R. ...
COLT
2004
Springer
15 years 8 months ago
Learning a Hidden Graph Using O(log n) Queries Per Edge
We consider the problem of learning a general graph using edge-detecting queries. In this model, the learner may query whether a set of vertices induces an edge of the hidden grap...
Dana Angluin, Jiang Chen