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Found 7 papers, 2 papers with code
FedHyper: A Universal and Robust Learning Rate Scheduler for Federated Learning with Hypergradient Descent
The theoretical landscape of federated learning (FL) undergoes rapid evolution, but its practical application encounters a series of intricate challenges, and hyperparameter optimization is one of these critical challenges.
A Method to Judge the Style of Classical Poetry Based on Pre-trained Model
One of the important topics in the research field of Chinese classical poetry is to analyze the poetic style.
Generation of Chinese classical poetry based on pre-trained model
In order to test the model's results, the authors selected ancient poets, by combining it with BART's poetic model work, developed a set of AI poetry Turing problems, it was reviewed by a group of poets and poetry writing researchers.
A General Framework for Defending Against Backdoor Attacks via Influence Graph
In this work, we propose a new and general framework to defend against backdoor attacks, inspired by the fact that attack triggers usually follow a \textsc{specific} type of attacking pattern, and therefore, poisoned training examples have greater impacts on each other during training.
An MRC Framework for Semantic Role Labeling
We formalize predicate disambiguation as multiple-choice machine reading comprehension, where the descriptions of candidate senses of a given predicate are used as options to select the correct sense.
Ranked #1 on
Semantic Role Labeling
on CoNLL 2005
Learning from Incomplete Features by Simultaneous Training of Neural Networks and Sparse Coding
A new supervised learning method is developed to train a general classifier, such as a logistic regression or a deep neural network, using only a subset of features per sample, while assuming sparse representations of data vectors on an unknown dictionary.
Supervised learning with incomplete data via sparse representations
This paper addresses the problem of training a classifier on incomplete data and its application to a complete or incomplete test dataset.
