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SIGIR
2012
ACM
12 years 11 days ago
Top-k learning to rank: labeling, ranking and evaluation
In this paper, we propose a novel top-k learning to rank framework, which involves labeling strategy, ranking model and evaluation measure. The motivation comes from the difficul...
Shuzi Niu, Jiafeng Guo, Yanyan Lan, Xueqi Cheng
SAB
2010
Springer
187views Optimization» more  SAB 2010»
13 years 8 months ago
Learning Robot-Environment Interaction Using Echo State Networks
Learning robot-environment interaction with echo state networks (ESNs) is presented in this paper. ESNs are asked to bootstrap a robot’s control policy from human teacher’s dem...
Mohamed Oubbati, Bahram Kord, Günther Palm
CICC
2011
106views more  CICC 2011»
12 years 10 months ago
A 45nm CMOS neuromorphic chip with a scalable architecture for learning in networks of spiking neurons
Efforts to achieve the long-standing dream of realizing scalable learning algorithms for networks of spiking neurons in silicon have been hampered by (a) the limited scalability of...
Jae-sun Seo, Bernard Brezzo, Yong Liu, Benjamin D....
CVPR
2012
IEEE
12 years 11 days ago
Steerable part models
We describe a method for learning steerable deformable part models. Our models exploit the fact that part templates can be written as linear filter banks. We demonstrate that one...
Hamed Pirsiavash, Deva Ramanan
VEE
2012
ACM
322views Virtualization» more  VEE 2012»
12 years 5 months ago
Modeling virtualized applications using machine learning techniques
With the growing adoption of virtualized datacenters and cloud hosting services, the allocation and sizing of resources such as CPU, memory, and I/O bandwidth for virtual machines...
Sajib Kundu, Raju Rangaswami, Ajay Gulati, Ming Zh...