Sciweavers

3556 search results - page 232 / 712
» Can machine learning be secure
Sort
View
ICML
2010
IEEE
15 years 6 months ago
Learning Efficiently with Approximate Inference via Dual Losses
Many structured prediction tasks involve complex models where inference is computationally intractable, but where it can be well approximated using a linear programming relaxation...
Ofer Meshi, David Sontag, Tommi Jaakkola, Amir Glo...
156
Voted
ICML
2009
IEEE
16 years 5 months ago
Convex variational Bayesian inference for large scale generalized linear models
We show how variational Bayesian inference can be implemented for very large generalized linear models. Our relaxation is proven to be a convex problem for any log-concave model. ...
Hannes Nickisch, Matthias W. Seeger
ICML
2009
IEEE
16 years 5 months ago
A simpler unified analysis of budget perceptrons
The kernel Perceptron is an appealing online learning algorithm that has a drawback: whenever it makes an error it must increase its support set, which slows training and testing ...
Ilya Sutskever
ICML
2008
IEEE
16 years 5 months ago
Non-parametric policy gradients: a unified treatment of propositional and relational domains
Policy gradient approaches are a powerful instrument for learning how to interact with the environment. Existing approaches have focused on propositional and continuous domains on...
Kristian Kersting, Kurt Driessens
ICML
2005
IEEE
16 years 5 months ago
Fast maximum margin matrix factorization for collaborative prediction
Maximum Margin Matrix Factorization (MMMF) was recently suggested (Srebro et al., 2005) as a convex, infinite dimensional alternative to low-rank approximations and standard facto...
Jason D. M. Rennie, Nathan Srebro