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» New Algorithms for Learning in Presence of Errors
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WSDM
2010
ACM
245views Data Mining» more  WSDM 2010»
14 years 6 months ago
Improving Quality of Training Data for Learning to Rank Using Click-Through Data
In information retrieval, relevance of documents with respect to queries is usually judged by humans, and used in evaluation and/or learning of ranking functions. Previous work ha...
Jingfang Xu, Chuanliang Chen, Gu Xu, Hang Li, Elbi...
IACR
2011
115views more  IACR 2011»
12 years 8 months ago
Pseudorandom Functions and Lattices
We give direct constructions of pseudorandom function (PRF) families based on conjectured hard lattice problems and learning problems. Our constructions are asymptotically effici...
Abhishek Banerjee, Chris Peikert, Alon Rosen
KDD
2003
ACM
157views Data Mining» more  KDD 2003»
14 years 9 months ago
Cross-training: learning probabilistic mappings between topics
Classification is a well-established operation in text mining. Given a set of labels A and a set DA of training documents tagged with these labels, a classifier learns to assign l...
Sunita Sarawagi, Soumen Chakrabarti, Shantanu Godb...
DAWAK
2010
Springer
13 years 8 months ago
Modelling Complex Data by Learning Which Variable to Construct
Abstract. This paper addresses a task of variable selection which consists in choosing a subset of variables that is sufficient to predict the target label well. Here instead of tr...
Françoise Fessant, Aurélie Le Cam, M...
FOCI
2007
IEEE
14 years 3 months ago
Almost All Learning Machines are Singular
— A learning machine is called singular if its Fisher information matrix is singular. Almost all learning machines used in information processing are singular, for example, layer...
Sumio Watanabe