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ICTAI
2006
IEEE
15 years 3 months ago
MI-Winnow: A New Multiple-Instance Learning Algorithm
We present MI-Winnow, a new multiple-instance learning (MIL) algorithm that provides a new technique to convert MIL data into standard supervised data. In MIL each example is a co...
Sharath R. Cholleti, Sally A. Goldman, Rouhollah R...
ICML
2010
IEEE
14 years 10 months ago
Gaussian Processes Multiple Instance Learning
This paper proposes a multiple instance learning (MIL) algorithm for Gaussian processes (GP). The GP-MIL model inherits two crucial benefits from GP: (i) a principle manner of lea...
Minyoung Kim, Fernando De la Torre
PAMI
2006
206views more  PAMI 2006»
14 years 9 months ago
MILES: Multiple-Instance Learning via Embedded Instance Selection
Multiple-instance problems arise from the situations where training class labels are attached to sets of samples (named bags), instead of individual samples within each bag (called...
Yixin Chen, Jinbo Bi, James Ze Wang
INFOCOM
2010
IEEE
14 years 8 months ago
Opportunistic Spectrum Access with Multiple Users: Learning under Competition
Abstract—The problem of cooperative allocation among multiple secondary users to maximize cognitive system throughput is considered. The channel availability statistics are initi...
Animashree Anandkumar, Nithin Michael, Ao Tang
ICCV
2009
IEEE
16 years 2 months ago
Robust Fitting of Multiple Structures: The Statistical Learning Approach
We propose an unconventional but highly effective approach to robust fitting of multiple structures by using statistical learning concepts. We design a novel Mercer kernel for t...
Tat-Jun Chin, Hanzi Wang, David Suter