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ICDM
2007
IEEE
106views Data Mining» more  ICDM 2007»
15 years 4 months ago
High-Speed Function Approximation
We address a new learning problem where the goal is to build a predictive model that minimizes prediction time (the time taken to make a prediction) subject to a constraint on mod...
Biswanath Panda, Mirek Riedewald, Johannes Gehrke,...
PKDD
2007
Springer
146views Data Mining» more  PKDD 2007»
15 years 4 months ago
A Method for Multi-relational Classification Using Single and Multi-feature Aggregation Functions
This paper presents a novel method for multi-relational classification via an aggregation-based Inductive Logic Programming (ILP) approach. We extend the classical ILP representati...
Richard Frank, Flavia Moser, Martin Ester
AAAI
2008
15 years 9 days ago
Strategyproof Classification under Constant Hypotheses: A Tale of Two Functions
We consider the following setting: a decision maker must make a decision based on reported data points with binary labels. Subsets of data points are controlled by different selfi...
Reshef Meir, Ariel D. Procaccia, Jeffrey S. Rosens...
ICONIP
2010
14 years 7 months ago
Emergence of Highly Nonrandom Functional Synaptic Connectivity Through STDP
Abstract. We investigated the network topology organized through spike-timingdependent plasticity (STDP) using pair- and triad-connectivity patterns, considering di erence of excit...
Hideyuki Kato, Tohru Ikeguchi
TNN
2010
216views Management» more  TNN 2010»
14 years 4 months ago
Simplifying mixture models through function approximation
Finite mixture model is a powerful tool in many statistical learning problems. In this paper, we propose a general, structure-preserving approach to reduce its model complexity, w...
Kai Zhang, James T. Kwok