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» Forecasting high-dimensional data
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ICCV
2011
IEEE
13 years 9 months ago
A Linear Subspace Learning Approach via Sparse Coding
Linear subspace learning (LSL) is a popular approach to image recognition and it aims to reveal the essential features of high dimensional data, e.g., facial images, in a lower di...
Lei Zhang, Pengfei Zhu, Qinghu Hu, David Zhang
JMLR
2012
13 years 4 days ago
Maximum Margin Temporal Clustering
Temporal Clustering (TC) refers to the factorization of multiple time series into a set of non-overlapping segments that belong to k temporal clusters. Existing methods based on e...
Minh Hoai Nguyen, Fernando De la Torre
ICAC
2006
IEEE
15 years 3 months ago
Learning Application Models for Utility Resource Planning
Abstract— Shared computing utilities allocate compute, network, and storage resources to competing applications on demand. An awareness of the demands and behaviors of the hosted...
Piyush Shivam, Shivnath Babu, Jeffrey S. Chase
81
Voted
DATE
2010
IEEE
181views Hardware» more  DATE 2010»
15 years 2 months ago
Temperature-aware dynamic resource provisioning in a power-optimized datacenter
- The current energy and environmental cost trends of datacenters are unsustainable. It is critically important to develop datacenter-wide power and thermal management (PTM) soluti...
Ehsan Pakbaznia, Mohammad Ghasemazar, Massoud Pedr...
72
Voted
WSC
2008
15 years 11 hour ago
Coping with typical unpredictable incidents in a logic fab
Within the last months the semiconductor plant of Infineon in Dresden has converted to a pure manufacturer of logic products. With it, premises for production control have changed...
Wolfgang Scholl