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Found 4 papers, 0 papers with code
Efficient Learning of Multiple NLP Tasks via Collective Weight Factorization on BERT
We test our proposed method on finetuning multiple natural language understanding tasks by employing BERT-Large as an instantiation of the Transformer and the GLUE as the evaluation benchmark.
A Gradient Free Neural Network Framework Based on Universal Approximation Theorem
The proposed algorithm adheres to the underlying theory, is highly fast, and results in remarkably low errors when applied for regression and classification of complex data-sets, such as the Griewank function of multiple variables $\mathbf{x} \in \mathbb{R}^{100}$ with random noise addition, and MNIST database for handwritten digits recognition, with $7\times10^4$ images.
3DFaceGAN: Adversarial Nets for 3D Face Representation, Generation, and Translation
As a result, linear methods such as Principal Component Analysis (PCA) have been mainly utilized towards 3D shape analysis, despite being unable to capture non-linearities and high frequency details of the 3D face - such as eyelid and lip variations.
Multi-Attribute Robust Component Analysis for Facial UV Maps
In this paper, we propose a novel component analysis technique that is suitable for facial UV maps containing a considerable amount of missing information and outliers, while additionally, incorporates knowledge from various attributes (such as age and identity).
