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IPM
2008
100views more  IPM 2008»
15 years 3 months ago
Query-level loss functions for information retrieval
Many machine learning technologies such as support vector machines, boosting, and neural networks have been applied to the ranking problem in information retrieval. However, since...
Tao Qin, Xu-Dong Zhang, Ming-Feng Tsai, De-Sheng W...
BMCBI
2007
114views more  BMCBI 2007»
15 years 4 months ago
False occurrences of functional motifs in protein sequences highlight evolutionary constraints
Background: False occurrences of functional motifs in protein sequences can be considered as random events due solely to the sequence composition of a proteome. Here we use a nume...
Allegra Via, Pier Federico Gherardini, Enrico Ferr...
SODA
2008
ACM
104views Algorithms» more  SODA 2008»
15 years 5 months ago
Ranged hash functions and the price of churn
Ranged hash functions generalize hash tables to the setting where hash buckets may come and go over time, a typical case in distributed settings where hash buckets may correspond ...
James Aspnes, Muli Safra, Yitong Yin
TSMC
2008
102views more  TSMC 2008»
15 years 3 months ago
Generalized Cost-Function-Based Forecasting for Periodically Measured Nonstationary Traffic
Abstract-- In this paper, we address the issue of forecasting for periodically measured nonstationary traffic based on statistical time series modeling. Often with time series base...
Balaji Krithikaivasan, Yong Zeng, Deep Medhi
ESA
2010
Springer
246views Algorithms» more  ESA 2010»
15 years 5 months ago
Estimating the Average of a Lipschitz-Continuous Function from One Sample
We study the problem of estimating the average of a Lipschitz continuous function f defined over a metric space, by querying f at only a single point. More specifically, we explore...
Abhimanyu Das, David Kempe