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IDEAL
2004
Springer
14 years 3 months ago
Summarizing Time Series: Learning Patterns in 'Volatile' Series
Most financial time series processes are nonstationary and their frequency characteristics are time-dependant. In this paper we present a time series summarization and prediction ...
Saif Ahmad, Tugba Taskaya-Temizel, Khurshid Ahmad
ICMLA
2007
13 years 11 months ago
Machine learned regression for abductive DNA sequencing
We construct machine learned regressors to predict the behaviour of DNA sequencing data from the fluorescent labelled Sanger method. These predictions are used to assess hypothes...
David Thornley, Maxim Zverev, Stavros Petridis
NIPS
2003
13 years 11 months ago
Online Passive-Aggressive Algorithms
We present a family of margin based online learning algorithms for various prediction tasks. In particular we derive and analyze algorithms for binary and multiclass categorizatio...
Shai Shalev-Shwartz, Koby Crammer, Ofer Dekel, Yor...
PE
2010
Springer
212views Optimization» more  PE 2010»
13 years 4 months ago
Modeling TCP throughput: An elaborated large-deviations-based model and its empirical validation
In today's Internet, a large part of the traffic is carried using the TCP transport protocol. Characterization of the variations of TCP traffic is thus a major challenge, bot...
Patrick Loiseau, Paulo Gonçalves, Julien Ba...
AAAI
2011
12 years 10 months ago
Temporal Dynamics of User Interests in Tagging Systems
Collaborative tagging systems are now deployed extensively to help users share and organize resources. Tag prediction and recommendation systems generally model user behavior as r...
Dawei Yin, Liangjie Hong, Zhenzhen Xue, Brian D. D...