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NIPS
1997
15 years 1 months ago
Relative Loss Bounds for Multidimensional Regression Problems
We study on-line generalized linear regression with multidimensional outputs, i.e., neural networks with multiple output nodes but no hidden nodes. We allow at the final layer tra...
Jyrki Kivinen, Manfred K. Warmuth
NIPS
2008
15 years 1 months ago
On the Complexity of Linear Prediction: Risk Bounds, Margin Bounds, and Regularization
This work characterizes the generalization ability of algorithms whose predictions are linear in the input vector. To this end, we provide sharp bounds for Rademacher and Gaussian...
Sham M. Kakade, Karthik Sridharan, Ambuj Tewari
CORR
2011
Springer
148views Education» more  CORR 2011»
14 years 6 months ago
How well can we estimate a sparse vector?
The estimation of a sparse vector in the linear model is a fundamental problem in signal processing, statistics, and compressive sensing. This paper establishes a lower bound on t...
Emmanuel J. Candès, Mark A. Davenport
FOCS
2003
IEEE
15 years 5 months ago
A Lattice Problem in Quantum NP
We consider coGapSV P√ n, a gap version of the shortest vector in a lattice problem. This problem is known to be in AM ∩coNP but is not known to be in NP or in MA. We prove th...
Dorit Aharonov, Oded Regev
ALT
2008
Springer
15 years 8 months ago
Generalization Bounds for K-Dimensional Coding Schemes in Hilbert Spaces
We give a bound on the expected reconstruction error for a general coding method where data in a Hilbert space are represented by finite dimensional coding vectors. The result can...
Andreas Maurer, Massimiliano Pontil