Attention models are typically learned by optimizing one of three standa...
Attention mechanisms form a core component of several successful deep
le...
We present consistent algorithms for multiclass learning with complex
pe...
Despite their massive success, training successful deep neural networks ...
Recent papers have shown that sufficiently overparameterized neural netw...
We analyze the inductive bias of gradient descent for weight normalized
...
The F-measure is a widely used performance measure for multi-label
class...
Converting an n-dimensional vector to a probability distribution over n
...
Mixture proportion estimation (MPE) is the problem of estimating the wei...
We consider the problem of n-class classification (n≥ 2), where the
clas...
We study consistency of learning algorithms for a multi-class performanc...