Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Unifying Heterogeneous Classifiers with Distillation   In this paper, we study the problem of unifying knowledge from a set of
classifiers with different architectures and target classes into a single
classifier, given only a generic set of unlabelled data. We call this problem
Unifying Heterogeneous Classifiers (UHC). This problem is motivated by
scenarios where data is collected from multiple sources, but the sources cannot
share their data, e.g., due to privacy concerns, and only privately trained
models can be shared. In addition, each source may not be able to gather data
to train all classes due to data availability at each source, and may not be
able to train the same classification model due to different computational
resources. To tackle this problem, we propose a generalisation of knowledge
distillation to merge HCs. We derive a probabilistic relation between the
outputs of HCs and the probability over all classes. Based on this relation, we
propose two classes of methods based on cross-entropy minimisation and matrix
factorisation, which allow us to estimate soft labels over all classes from
unlabelled samples and use them in lieu of ground truth labels to train a
unified classifier. Our extensive experiments on ImageNet, LSUN, and Places365
datasets show that our approaches significantly outperform a naive extension of
distillation and can achieve almost the same accuracy as classifiers that are
trained in a centralised, supervised manner.

24
The categories of this paper are: dg-ga
16
The categories of this paper are: stat
30
The categories of this paper are: q-alg
33
The categories of this paper are: plasm-ph
32
The categories of this paper are: atom-ph
12
The categories of this paper are: nucl-th
10
The categories of this paper are: q-bio
4
The categories of this paper are: cond-mat
15
The categories of this paper are: nucl-ex
17
The categories of this paper are: q-fin
36
The categories of this paper are: cmp-lg
26
The categories of this paper are: bayes-an
2
The categories of this paper are: math
28
The categories of this paper are: alg-geom
18
The categories of this paper are: econ
19
The categories of this paper are: eess