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TIT
1998
70views more  TIT 1998»
13 years 7 months ago
The Importance of Convexity in Learning with Squared Loss
We show that if the closureof a function class F under the metric induced by some probability distribution is not convex, then the sample complexity for agnostically learning F wi...
Wee Sun Lee, Peter L. Bartlett, Robert C. Williams...
FPL
2010
Springer
104views Hardware» more  FPL 2010»
13 years 5 months ago
Multiplicative Square Root Algorithms for FPGAs
Abstract--Most current square root implementations for FPGAs use a digit recurrence algorithm which is well suited to their LUT structure. However, recent computing-oriented FPGAs ...
Florent de Dinechin, Mioara Joldes, Bogdan Pasca, ...
CDC
2010
IEEE
155views Control Systems» more  CDC 2010»
13 years 2 months ago
Linear parametric noise models for Least Squares Support Vector Machines
In the identification of nonlinear dynamical models it may happen that not only the system dynamics have to be modeled but also the noise has a dynamic character. We show how to ad...
Tillmann Falck, Johan A. K. Suykens, Bart De Moor
VLUDS
2010
187views Visualization» more  VLUDS 2010»
13 years 2 months ago
On Moving Least Squares Based Flow Visualization
Modern simulation and measurement methods tend to produce meshfree data sets if modeling of processes or objects with free surfaces or boundaries is desired. In Computational Flui...
Harald Obermaier, Martin Hering-Bertram, Jörg...
ICASSP
2011
IEEE
12 years 11 months ago
Robust binary least squares: Relaxations and algorithms
Finding the least squares (LS) solution s to a system of linear equations Hs = y where H, y are given and s is a vector of binary variables, is a well known NP-hard problem. In th...
Efthymios Tsakonas, Joakim Jalden, Björn E. O...