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» MILIS: Multiple Instance Learning with Instance Selection
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CVPR
2010
IEEE
14 years 3 months ago
Breaking the interactive bottleneck in multi-class classification with active selection and binary feedback
Multi-class classification schemes typically require human input in the form of precise category names or numbers for each example to be annotated – providing this can be impra...
Ajay Joshi, Fatih Porikli, Nikolaos Papanikolopoul...
SDM
2007
SIAM
137views Data Mining» more  SDM 2007»
13 years 9 months ago
Semi-supervised Feature Selection via Spectral Analysis
Feature selection is an important task in effective data mining. A new challenge to feature selection is the so-called “small labeled-sample problem” in which labeled data is...
Zheng Zhao, Huan Liu
NAACL
2007
13 years 9 months ago
A Systematic Exploration of the Feature Space for Relation Extraction
Relation extraction is the task of finding semantic relations between entities from text. The state-of-the-art methods for relation extraction are mostly based on statistical lea...
Jing Jiang, ChengXiang Zhai
SIGMOD
2010
ACM
171views Database» more  SIGMOD 2010»
14 years 15 days ago
Variance aware optimization of parameterized queries
Parameterized queries are commonly used in database applications. In a parameterized query, the same SQL statement is potentially executed multiple times with different parameter ...
Surajit Chaudhuri, Hongrae Lee, Vivek R. Narasayya
AAAI
2006
13 years 9 months ago
Distributed Interactive Learning in Multi-Agent Systems
Both explanation-based and inductive learning techniques have proven successful in a variety of distributed domains. However, learning in multi-agent systems does not necessarily ...
Jian Huang, Adrian R. Pearce