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NIPS
1997
13 years 9 months ago
Learning Generative Models with the Up-Propagation Algorithm
Up-propagation is an algorithm for inverting and learning neural network generative models. Sensory input is processed by inverting a model that generates patterns from hidden var...
Jong-Hoon Oh, H. Sebastian Seung
VLSISP
2008
159views more  VLSISP 2008»
13 years 8 months ago
Effective Code Generation for Distributed and Ping-Pong Register Files: A Case Study on PAC VLIW DSP Cores
The compiler is generally regarded as the most important software component that supports a processor design to achieve success. This paper describes our application of the open re...
Yung-Chia Lin, Chia-Han Lu, Chung-Ju Wu, Chung-Lin...
NOCS
2007
IEEE
14 years 2 months ago
NoC-Based FPGA: Architecture and Routing
We present a novel network-on-chip-based architecture for future programmable chips (FPGAs). A key challenge for FPGA design is supporting numerous highly variable design instance...
Roman Gindin, Israel Cidon, Idit Keidar
WWW
2001
ACM
14 years 8 months ago
IEPAD: information extraction based on pattern discovery
The research in information extraction (IE) regards the generation of wrappers that can extract particular information from semistructured Web documents. Similar to compiler gener...
Chia-Hui Chang, Shao-Chen Lui
CORR
2010
Springer
141views Education» more  CORR 2010»
13 years 5 months ago
Modeling Dynamical Influence in Human Interaction Patterns
We present a new way for modeling 1) social influence and 2) the well-observed property of social influence
Wei Pan, Manuel Cebrián, Wen Dong, Taemie K...