26 citations · 64 across the 16 of their papers we have counts for
7 papers · 1 filter
UserBERT: Modeling Long- and Short-Term User Preferences via Self-Supervision
Tianyu Li, Ali Cevahir, Derek Cho +3
E-commerce platforms generate vast amounts of customer behavior data, such as clicks and purchases, from millions of unique users every day. However, effectively using this data fo…
Connecting Weighted Automata, Tensor Networks and Recurrent Neural Networks through Spectral Learning
Tianyu Li, Doina Precup, Guillaume Rabusseau
In this paper, we present connections between three models used in different research fields: weighted finite automata~(WFA) from formal languages and linguistics, recurrent neural…
Learning to Profile: User Meta-Profile Network for Few-Shot Learning
Hao Gong, Qifang Zhao, Tianyu Li +2
Meta-learning approaches have shown great success in vision and language domains. However, few studies discuss the practice of meta-learning for large-scale industrial applications…
Representation of Reinforcement Learning Policies in Reproducing Kernel Hilbert Spaces
Bogdan Mazoure, Thang Doan, Tianyu Li +4
We propose a general framework for policy representation for reinforcement learning tasks. This framework involves finding a low-dimensional embedding of the policy on a reproducin…
Learning Classifiers on Positive and Unlabeled Data with Policy Gradient
Tianyu Li, Chien-Chih Wang, Yukun Ma +4
Existing algorithms aiming to learn a binary classifier from positive (P) and unlabeled (U) data generally require estimating the class prior or label noises ahead of building a cl…
Deep Heterogeneous Autoencoders for Collaborative Filtering
Tianyu Li, Yukun Ma, Jiu Xu +3
This paper leverages heterogeneous auxiliary information to address the data sparsity problem of recommender systems. We propose a model that learns a shared feature space from het…
Connecting Weighted Automata and Recurrent Neural Networks through Spectral Learning
Guillaume Rabusseau, Tianyu Li, Doina Precup
In this paper, we unravel a fundamental connection between weighted finite automata~(WFAs) and second-order recurrent neural networks~(2-RNNs): in the case of sequences of discrete…