Crowdsourced data management: A survey
Any important data management and analytics tasks cannot be completely addressed by
automated processes. These tasks, such as entity resolution, sentiment analysis, and image …
automated processes. These tasks, such as entity resolution, sentiment analysis, and image …
An overview and empirical comparison of distance metric learning methods
P Moutafis, M Leng, IA Kakadiaris - IEEE transactions on …, 2016 - ieeexplore.ieee.org
In this paper, we first offer an overview of advances in the field of distance metric learning.
Then, we empirically compare selected methods using a common experimental protocol …
Then, we empirically compare selected methods using a common experimental protocol …
Making better use of the crowd: How crowdsourcing can advance machine learning research
JW Vaughan - Journal of Machine Learning Research, 2018 - jmlr.org
This survey provides a comprehensive overview of the landscape of crowdsourcing
research, targeted at the machine learning community. We begin with an overview of the …
research, targeted at the machine learning community. We begin with an overview of the …
A multiresolution watermark for digital images
We introduce a new multiresolution watermarking method for digital images. The method is
based on the discrete wavelet transform (DWT). Pseudo-random codes are added to the …
based on the discrete wavelet transform (DWT). Pseudo-random codes are added to the …
Clustering with outlier removal
Cluster analysis and outlier detection are two continuously rising topics in data mining area,
which in fact connect to each other deeply. Cluster structure is vulnerable to outliers; …
which in fact connect to each other deeply. Cluster structure is vulnerable to outliers; …
Self-biased high-bandwidth low-jitter 1-to-4096 multiplier clock generator PLL
JG Maneatis, J Kim, I McClatchie, J Maxey… - Proceedings of the 40th …, 2003 - dl.acm.org
A self-biased PLL uses a sampled feed-forward filter network and a multi-stage inverse-
linear programmable current mirror for constant loop dynamics that scale with reference …
linear programmable current mirror for constant loop dynamics that scale with reference …
Robust ensemble clustering by matrix completion
Data clustering is an important task and has found applications in numerous real-world
problems. Since no single clustering algorithm is able to identify all different types of cluster …
problems. Since no single clustering algorithm is able to identify all different types of cluster …
Deep clustering with incomplete noisy pairwise annotations: A geometric regularization approach
The recent integration of deep learning and pairwise similarity annotation-based
constrained clustering—ie, deep constrained clustering (DCC)—has proven effective for …
constrained clustering—ie, deep constrained clustering (DCC)—has proven effective for …
Constrained clustering: Current and new trends
Clustering is an unsupervised process which aims to discover regularities and underlying
structures in data. Constrained clustering extends clustering in such a way that expert …
structures in data. Constrained clustering extends clustering in such a way that expert …
Inferring users' preferences from crowdsourced pairwise comparisons: A matrix completion approach
Inferring user preferences over a set of items is an important problem that has found
numerous applications. This work focuses on the scenario where the explicit feature …
numerous applications. This work focuses on the scenario where the explicit feature …