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» Improved bounds on the sample complexity of learning
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TIT
2010
128views Education» more  TIT 2010»
13 years 2 months ago
Shannon-theoretic limits on noisy compressive sampling
In this paper, we study the number of measurements required to recover a sparse signal in M with L nonzero coefficients from compressed samples in the presence of noise. We conside...
Mehmet Akçakaya, Vahid Tarokh
KDD
2008
ACM
178views Data Mining» more  KDD 2008»
14 years 8 months ago
Training structural svms with kernels using sampled cuts
Discriminative training for structured outputs has found increasing applications in areas such as natural language processing, bioinformatics, information retrieval, and computer ...
Chun-Nam John Yu, Thorsten Joachims
EDUTAINMENT
2007
Springer
14 years 1 months ago
Method of Motion Data Processing Based on Manifold Learning
Due to the high-dimensionality of motion captured data which resulted in the complexity in motion analysis, a method of motion data processing based on manifold learning was propos...
Fengxia Li, Tianyu Huang, Lijie Li
ML
2000
ACM
103views Machine Learning» more  ML 2000»
13 years 7 months ago
Nonparametric Time Series Prediction Through Adaptive Model Selection
We consider the problem of one-step ahead prediction for time series generated by an underlying stationary stochastic process obeying the condition of absolute regularity, describi...
Ron Meir
ICML
2008
IEEE
14 years 8 months ago
An object-oriented representation for efficient reinforcement learning
Rich representations in reinforcement learning have been studied for the purpose of enabling generalization and making learning feasible in large state spaces. We introduce Object...
Carlos Diuk, Andre Cohen, Michael L. Littman