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ALT
1999
Springer
13 years 10 months ago
Extended Stochastic Complexity and Minimax Relative Loss Analysis
We are concerned with the problem of sequential prediction using a givenhypothesis class of continuously-manyprediction strategies. An e ectiveperformance measure is the minimax re...
Kenji Yamanishi
KDD
2010
ACM
218views Data Mining» more  KDD 2010»
13 years 9 months ago
Online multiscale dynamic topic models
We propose an online topic model for sequentially analyzing the time evolution of topics in document collections. Topics naturally evolve with multiple timescales. For example, so...
Tomoharu Iwata, Takeshi Yamada, Yasushi Sakurai, N...
CORR
2011
Springer
205views Education» more  CORR 2011»
12 years 9 months ago
Parallel Coordinate Descent for L1-Regularized Loss Minimization
We propose Shotgun, a parallel coordinate descent algorithm for minimizing L1regularized losses. Though coordinate descent seems inherently sequential, we prove convergence bounds...
Joseph K. Bradley, Aapo Kyrola, Danny Bickson, Car...
ISCI
2008
145views more  ISCI 2008»
13 years 5 months ago
Aggregation in sensor networks with a user-provided quality of service goal
Significant research has been devoted to aggregation in sensor networks with a view to optimize its performance. Existing research has mostly concentrated on maximizing network li...
Zhen He, Byung Suk Lee, Xiaoyang Sean Wang
KDD
2002
ACM
171views Data Mining» more  KDD 2002»
14 years 6 months ago
Mining complex models from arbitrarily large databases in constant time
In this paper we propose a scaling-up method that is applicable to essentially any induction algorithm based on discrete search. The result of applying the method to an algorithm ...
Geoff Hulten, Pedro Domingos