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» Evaluating algorithms that learn from data streams
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AI
2001
Springer
15 years 9 months ago
Learning Bayesian Belief Network Classifiers: Algorithms and System
Abstract. This paper investigates the methods for learning predictive classifiers based on Bayesian belief networks (BN) – primarily unrestricted Bayesian networks and Bayesian m...
Jie Cheng, Russell Greiner
AAAI
2000
15 years 6 months ago
Learning the Common Structure of Data
The proliferation of online information sources has accentuated the need for tools that automatically validate and recognize data. We present an efficient algorithm that learns st...
Kristina Lerman, Steven Minton
UAI
2001
15 years 6 months ago
Aggregating Learned Probabilistic Beliefs
We consider the task of aggregating beliefs of several experts. We assume that these beliefs are represented as probability distributions. We argue that the evaluation of any aggr...
Pedrito Maynard-Reid II, Urszula Chajewska
140
Voted
JSAC
2007
97views more  JSAC 2007»
15 years 4 months ago
R2: Random Push with Random Network Coding in Live Peer-to-Peer Streaming
— In information theory, it has been shown that network coding can effectively improve the throughput of multicast communication sessions in directed acyclic graphs. More practic...
Mea Wang, Baochun Li
117
Voted
GECCO
2003
Springer
103views Optimization» more  GECCO 2003»
15 years 9 months ago
MILA - Multilevel Immune Learning Algorithm
The biological immune system is an intricate network of specialized tissues, organs, cells, and chemical molecules. T-cell-dependent humoral immune response is one of the complex i...
Dipankar Dasgupta, Senhua Yu, Nivedita Sumi Majumd...