Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Meta-free few-shot learning via representation learning with weight
  averaging   Recent studies on few-shot classification using transfer learning pose
challenges to the effectiveness and efficiency of episodic meta-learning
algorithms. Transfer learning approaches are a natural alternative, but they
are restricted to few-shot classification. Moreover, little attention has been
on the development of probabilistic models with well-calibrated uncertainty
from few-shot samples, except for some Bayesian episodic learning algorithms.
To tackle the aforementioned issues, we propose a new transfer learning method
to obtain accurate and reliable models for few-shot regression and
classification. The resulting method does not require episodic meta-learning
and is called meta-free representation learning (MFRL). MFRL first finds
low-rank representation generalizing well on meta-test tasks. Given the learned
representation, probabilistic linear models are fine-tuned with few-shot
samples to obtain models with well-calibrated uncertainty. The proposed method
not only achieves the highest accuracy on a wide range of few-shot learning
benchmark datasets but also correctly quantifies the prediction uncertainty. In
addition, weight averaging and temperature scaling are effective in improving
the accuracy and reliability of few-shot learning in existing meta-learning
algorithms with a wide range of learning paradigms and model architectures.

16
The categories of this paper are: stat
10
The categories of this paper are: q-bio
31
The categories of this paper are: ao-sci
23
The categories of this paper are: solv-int
9
The categories of this paper are: nlin
26
The categories of this paper are: bayes-an
17
The categories of this paper are: q-fin
32
The categories of this paper are: atom-ph
37
The categories of this paper are: supr-con
24
The categories of this paper are: dg-ga
3
The categories of this paper are: physics
29
The categories of this paper are: funct-an
15
The categories of this paper are: nucl-ex
30
The categories of this paper are: q-alg
2
The categories of this paper are: math
0
The categories of this paper are: hep-ph