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MTRGL:Effective Temporal Correlation Discerning through Multi-modal Temporal Relational Graph Learning
In this study, we explore the synergy of deep learning and financial market applications, focusing on pair trading.
Semantic-aware Contrastive Learning for More Accurate Semantic Parsing
Since the meaning representations are detailed and accurate annotations which express fine-grained sequence-level semtantics, it is usually hard to train discriminative semantic parsers via Maximum Likelihood Estimation (MLE) in an autoregressive fashion.
From Paraphrasing to Semantic Parsing: Unsupervised Semantic Parsing via Synchronous Semantic Decoding
During synchronous decoding: the utterance paraphrasing is constrained by the structure of the logical form, therefore the canonical utterance can be paraphrased controlledly; the semantic decoding is guided by the semantics of the canonical utterance, therefore its logical form can be generated unsupervisedly.
Variational Recurrent Neural Machine Translation
Partially inspired by successful applications of variational recurrent neural networks, we propose a novel variational recurrent neural machine translation (VRNMT) model in this paper.
Deep Facial Action Unit Recognition From Partially Labeled Data
To address this, we propose a deep facial action unit recognition approach learning from partially AU-labeled data.
