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ICML
2006
IEEE
16 years 20 days ago
Agnostic active learning
We state and analyze the first active learning algorithm which works in the presence of arbitrary forms of noise. The algorithm, A2 (for Agnostic Active), relies only upon the ass...
Maria-Florina Balcan, Alina Beygelzimer, John Lang...
ACL
2009
14 years 9 months ago
Handling phrase reorderings for machine translation
We propose a distance phrase reordering model (DPR) for statistical machine translation (SMT), where the aim is to capture phrase reorderings using a structure learning framework....
Yizhao Ni, Craig Saunders, Sándor Szedm&aac...
ECBS
2007
IEEE
188views Hardware» more  ECBS 2007»
15 years 1 months ago
Behavior Analysis-Based Learning Framework for Host Level Intrusion Detection
Machine learning has great utility within the context of network intrusion detection systems. In this paper, a behavior analysis-based learning framework for host level network in...
Haiyan Qiao, Jianfeng Peng, Chuan Feng, Jerzy W. R...
CORR
2000
Springer
92views Education» more  CORR 2000»
14 years 11 months ago
Predicting the expected behavior of agents that learn about agents: the CLRI framework
We describe a framework and equations used to model and predict the behavior of multi-agent systems (MASs) with learning agents. A difference equation is used for calculating the ...
José M. Vidal, Edmund H. Durfee
ECML
2004
Springer
15 years 5 months ago
Dynamic Asset Allocation Exploiting Predictors in Reinforcement Learning Framework
Given the pattern-based multi-predictors of the stock price, we study a method of dynamic asset allocation to maximize the trading performance. To optimize the proportion of asset ...
Jangmin O, Jae Won Lee, Jongwoo Lee, Byoung-Tak Zh...