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Found 5 papers, 1 papers with code
Robust Representation Learning for Unified Online Top-K Recommendation
The robust representation learning employs domain adversarial learning and multi-view wasserstein distribution learning to learn robust representations.
Autoregressive Structured Prediction with Language Models
Recent years have seen a paradigm shift in NLP towards using pretrained language models ({PLM}) for a wide range of tasks.
Ranked #1 on
Relation Extraction
on CoNLL04
(RE+ Micro F1 metric)
Adaptive Domain Interest Network for Multi-domain Recommendation
Industrial recommender systems usually hold data from multiple business scenarios and are expected to provide recommendation services for these scenarios simultaneously.
Learnable Faster Kernel-PCA for Nonlinear Fault Detection: Deep Autoencoder-Based Realization
In this work, to deal with the two drawbacks, a learnable faster realization of the conventional KPCA is proposed.
BOSH: An Efficient Meta Algorithm for Decision-based Attacks
Adversarial example generation becomes a viable method for evaluating the robustness of a machine learning model.
