Search Results for author:
Found 6 papers, 2 papers with code
VC Theoretical Explanation of Double Descent
There has been growing interest in generalization performance of large multilayer neural networks that can be trained to achieve zero training error, while generalizing well on test data.
Multiclass Learning from Contradictions
We introduce the notion of learning from contradictions, a. k. a Universum learning, for multiclass problems and propose a novel formulation for multiclass universum SVM (MU-SVM).
Single Class Universum-SVM
This paper extends the idea of Universum learning [1, 2] to single-class learning problems.
Multiclass Universum SVM
We introduce Universum learning for multiclass problems and propose a novel formulation for multiclass universum SVM (MU-SVM).
Universum Learning for Multiclass SVM
We introduce Universum learning for multiclass problems and propose a novel formulation for multiclass universum SVM (MU-SVM).
Universum Learning for SVM Regression
This paper extends the idea of Universum learning [18, 19] to regression problems.
