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ACTAC
2006
126views more  ACTAC 2006»
13 years 9 months ago
Named Entity Recognition for Hungarian Using Various Machine Learning Algorithms
In this paper we introduce a statistical Named Entity recognizer (NER) system for the Hungarian language. We examined three methods for identifying and disambiguating proper nouns...
Richárd Farkas, György Szarvas, Andr&a...
AAAI
2008
13 years 11 months ago
Structure Learning on Large Scale Common Sense Statistical Models of Human State
Research has shown promise in the design of large scale common sense probabilistic models to infer human state from environmental sensor data. These models have made use of mined ...
William Pentney, Matthai Philipose, Jeff A. Bilmes
ARCS
2006
Springer
14 years 21 days ago
The Robustness of Resource Allocations in Parallel and Distributed Computing Systems
This corresponds to the material in the invited keynote presentation by H. J. Siegel, summarizing the research in [2, 23]. Resource allocation decisions in heterogeneous parallel a...
Vladimir Shestak, Howard Jay Siegel, Anthony A. Ma...
IJCV
2000
136views more  IJCV 2000»
13 years 8 months ago
A Trainable System for Object Detection
This paper presents a general, trainable system for object detection in unconstrained, cluttered scenes. The system derives much of its power from a representation that describes a...
Constantine Papageorgiou, Tomaso Poggio
IPPS
2002
IEEE
14 years 1 months ago
Memory-Intensive Benchmarks: IRAM vs. Cache-Based Machines
The increasing gap between processor and memory performance has led to new architectural models for memory-intensive applications. In this paper, we use a set of memory-intensive ...
Brian R. Gaeke, Parry Husbands, Xiaoye S. Li, Leon...