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NIPS
1998
13 years 10 months ago
Controlling the Complexity of HMM Systems by Regularization
This paper introduces a method for regularization of HMM systems that avoids parameter overfitting caused by insufficient training data. Regularization is done by augmenting the E...
Christoph Neukirchen, Gerhard Rigoll
NIPS
1998
13 years 10 months ago
A High Performance k-NN Classifier Using a Binary Correlation Matrix Memory
This paper presents a novel and fast k-NN classifier that is based on a binary CMM (Correlation Matrix Memory) neural network. A robust encoding method is developed to meet CMM in...
Ping Zhou, Jim Austin, John Kennedy
RIAO
2000
13 years 10 months ago
Learning for Sequence Extraction Tasks
We consider the application of machine learning techniques for sequence modeling to Information Retrieval (IR) and surface Information Extraction (IE) tasks. We introduce a generi...
Massih-Reza Amini, Hugo Zaragoza, Patrick Gallinar...
NIPS
1996
13 years 10 months ago
Why did TD-Gammon Work?
Although TD-Gammon is one of the major successes in machine learning, it has not led to similar impressive breakthroughs in temporal difference learning for other applications or ...
Jordan B. Pollack, Alan D. Blair
MVA
1992
143views Computer Vision» more  MVA 1992»
13 years 10 months ago
A Real-Time Vision System Using Integrated Memory Array Processor Prototype LSI
This study reports on the performance of a Real-Time Vision System (RVS) and its use of an IMAP prototype LSI. This LSI integrates eight 8 bit processors and a 144 Kbit SRAM on a ...
Yoshihiro Fujita, Nobuyuki Yamashita, Shin'ichiro ...