Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Bayesian active learning for choice models with deep Gaussian processes   In this paper, we propose an active learning algorithm and models which can
gradually learn individual's preference through pairwise comparisons. The
active learning scheme aims at finding individual's most preferred choice with
minimized number of pairwise comparisons. The pairwise comparisons are encoded
into probabilistic models based on assumptions of choice models and deep
Gaussian processes. The next-to-compare decision is determined by a novel
acquisition function. We benchmark the proposed algorithm and models using
functions with multiple local optima and one public airline itinerary dataset.
The experiments indicate the effectiveness of our active learning algorithm and
models.

32
The categories of this paper are: atom-ph
17
The categories of this paper are: q-fin
12
The categories of this paper are: nucl-th
30
The categories of this paper are: q-alg
11
The categories of this paper are: hep-lat
5
The categories of this paper are: gr-qc
13
The categories of this paper are: quant-ph
19
The categories of this paper are: eess
3
The categories of this paper are: physics
2
The categories of this paper are: math
4
The categories of this paper are: cond-mat
24
The categories of this paper are: dg-ga
33
The categories of this paper are: plasm-ph
14
The categories of this paper are: math-ph
23
The categories of this paper are: solv-int
31
The categories of this paper are: ao-sci