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» Adaptive Sampling for Noisy Problems
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CVPR
2005
IEEE
14 years 9 months ago
Computer Vision for Music Identification
We describe how certain tasks in the audio domain can be effectively addressed using computer vision approaches. This paper focuses on the problem of music identification, where t...
Yan Ke, Derek Hoiem, Rahul Sukthankar
CVPR
2012
IEEE
11 years 10 months ago
Robust visual domain adaptation with low-rank reconstruction
Visual domain adaptation addresses the problem of adapting the sample distribution of the source domain to the target domain, where the recognition task is intended but the data d...
I-Hong Jhuo, Dong Liu, D. T. Lee, Shih-Fu Chang
ECCV
2008
Springer
14 years 9 months ago
Non-local Regularization of Inverse Problems
This article proposes a new framework to regularize linear inverse problems using the total variation on non-local graphs. This nonlocal graph allows to adapt the penalization to t...
Gabriel Peyré, Laurent D. Cohen, Séb...
SIGMOD
2004
ACM
118views Database» more  SIGMOD 2004»
14 years 7 months ago
Effective Use of Block-Level Sampling in Statistics Estimation
Block-level sampling is far more efficient than true uniform-random sampling over a large database, but prone to significant errors if used to create database statistics. In this ...
Surajit Chaudhuri, Gautam Das, Utkarsh Srivastava
COLT
1999
Springer
13 years 11 months ago
Uniform-Distribution Attribute Noise Learnability
We study the problem of PAC-learning Boolean functions with random attribute noise under the uniform distribution. We define a noisy distance measure for function classes and sho...
Nader H. Bshouty, Jeffrey C. Jackson, Christino Ta...