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SDM
2011
SIAM
233views Data Mining» more  SDM 2011»
12 years 11 months ago
Multi-Instance Mixture Models
Multi-instance (MI) learning is a variant of supervised learning where labeled examples consist of bags (i.e. multi-sets) of feature vectors instead of just a single feature vecto...
James R. Foulds, Padhraic Smyth
SIGECOM
2011
ACM
229views ECommerce» more  SIGECOM 2011»
12 years 11 months ago
A revealed preference approach to computational complexity in economics
Recent results in complexity theory suggest that various economic theories require agents to solve computationally intractable problems. However, such results assume the agents ar...
Federico Echenique, Daniel Golovin, Adam Wierman
SIGIR
2011
ACM
12 years 11 months ago
Learning to rank from a noisy crowd
We study how to best use crowdsourced relevance judgments learning to rank [1, 7]. We integrate two lines of prior work: unreliable crowd-based binary annotation for binary classi...
Abhimanu Kumar, Matthew Lease
SIGMOD
2011
ACM
152views Database» more  SIGMOD 2011»
12 years 11 months ago
Tracing data errors with view-conditioned causality
A surprising query result is often an indication of errors in the query or the underlying data. Recent work suggests using causal reasoning to find explanations for the surprisin...
Alexandra Meliou, Wolfgang Gatterbauer, Suman Nath...
SIGMOD
2011
ACM
206views Database» more  SIGMOD 2011»
12 years 11 months ago
Sampling based algorithms for quantile computation in sensor networks
We study the problem of computing approximate quantiles in large-scale sensor networks communication-efficiently, a problem previously studied by Greenwald and Khana [12] and Shri...
Zengfeng Huang, Lu Wang, Ke Yi, Yunhao Liu