Sep 18, 2021 · In this paper, we attempt to improve universal user representation from two points of views. First, a contrastive self-supervised learning paradigm is ...
It provides a unified framework that allows for long-term or short-term interest representation learning in a data- driven manner. Moreover, a novel multi- ...
Oct 10, 2022 · We propose a self-supervision learning paradigm for building high-quality universal user representations with large-scale unlabeled behavior data.
A contrastive self-supervised learning paradigm is presented to guide the representation model training, and a novel multi-interest extraction module is ...
Jan 28, 2022 · In this study, we propose a novel framework called Lifelong User Representation Model (LURM) to tackle this challenge.
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A novel pretext task, namely interest-oriented contrastive learning, is proposed to guide the representation model training. Source publication. Figure 1: ...
Estimating ferric iron content in clinopyroxene using machine learning models ... 2023. Interest-oriented universal user representation via contrastive learning.
Universal user representation has received many interests recently, with which we can be free from the cumbersome work of training a specific model for each ...
This chapter discusses STEPPINGSTONE, a new general learning problem solver that can operate on such difficult real-world problems as scheduling and logic ...
Interest-oriented universal user representation via contrastive learning. Q ... Learning Interest-oriented Universal User Representation via Self-supervision.