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JMLR
2010
160views more  JMLR 2010»
14 years 6 months ago
Neural conditional random fields
We propose a non-linear graphical model for structured prediction. It combines the power of deep neural networks to extract high level features with the graphical framework of Mar...
Trinh Minh Tri Do, Thierry Artières
ACL
2003
15 years 1 months ago
Deep Syntactic Processing by Combining Shallow Methods
We present a novel approach for finding discontinuities that outperforms previously published results on this task. Rather than using a deeper grammar formalism, our system combi...
Péter Dienes, Amit Dubey
ACL
2009
14 years 9 months ago
Cross-Domain Dependency Parsing Using a Deep Linguistic Grammar
Pure statistical parsing systems achieves high in-domain accuracy but performs poorly out-domain. In this paper, we propose two different approaches to produce syntactic dependenc...
Yi Zhang, Rui Wang
CORR
2010
Springer
121views Education» more  CORR 2010»
14 years 6 months ago
Deep Self-Taught Learning for Handwritten Character Recognition
Recent theoretical and empirical work in statistical machine learning has demonstrated the importance of learning algorithms for deep architectures, i.e., function classes obtaine...
Frédéric Bastien, Yoshua Bengio, Arn...
ANCS
2006
ACM
15 years 3 months ago
Efficient memory utilization on network processors for deep packet inspection
Deep Packet Inspection (DPI) refers to examining both packet header and payload to look for predefined patterns, which is essential for network security, intrusion detection and c...
Piti Piyachon, Yan Luo