Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Sequential Scenario-Specific Meta Learner for Online Recommendation   Cold-start problems are long-standing challenges for practical
recommendations. Most existing recommendation algorithms rely on extensive
observed data and are brittle to recommendation scenarios with few
interactions. This paper addresses such problems using few-shot learning and
meta learning. Our approach is based on the insight that having a good
generalization from a few examples relies on both a generic model
initialization and an effective strategy for adapting this model to newly
arising tasks. To accomplish this, we combine the scenario-specific learning
with a model-agnostic sequential meta-learning and unify them into an
integrated end-to-end framework, namely Scenario-specific Sequential Meta
learner (or s^2 meta). By doing so, our meta-learner produces a generic initial
model through aggregating contextual information from a variety of prediction
tasks while effectively adapting to specific tasks by leveraging
learning-to-learn knowledge. Extensive experiments on various real-world
datasets demonstrate that our proposed model can achieve significant gains over
the state-of-the-arts for cold-start problems in online recommendation.
Deployment is at the Guess You Like session, the front page of the Mobile
Taobao.

14
The categories of this paper are: math-ph
35
The categories of this paper are: mtrl-th
4
The categories of this paper are: cond-mat
25
The categories of this paper are: patt-sol
22
The categories of this paper are: chao-dyn
15
The categories of this paper are: nucl-ex
37
The categories of this paper are: supr-con
28
The categories of this paper are: alg-geom
34
The categories of this paper are: chem-ph
11
The categories of this paper are: hep-lat
29
The categories of this paper are: funct-an
26
The categories of this paper are: bayes-an
10
The categories of this paper are: q-bio
31
The categories of this paper are: ao-sci
13
The categories of this paper are: quant-ph
23
The categories of this paper are: solv-int