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06/07/2023
Towards High-Performance Exploratory Data Analysis (EDA) Via Stable Equilibrium Point
Exploratory data analysis (EDA) is a vital procedure for data science pr...
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04/19/2023
Accelerate Support Vector Clustering via Spectrum-Preserving Data Compression
Support vector clustering is an important clustering method. However, it...
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07/20/2021
Follow Your Path: a Progressive Method for Knowledge Distillation
Deep neural networks often have a huge number of parameters, which posts...
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07/13/2020
Do You Have the Right Scissors? Tailoring Pre-trained Language Models via Monte-Carlo Methods
It has been a common approach to pre-train a language model on a large c...
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07/12/2020
Improving Maximum Likelihood Training for Text Generation with Density Ratio Estimation
Auto-regressive sequence generative models trained by Maximum Likelihood...
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04/05/2020
Discriminator Contrastive Divergence: Semi-Amortized Generative Modeling by Exploring Energy of the Discriminator
Generative Adversarial Networks (GANs) have shown great promise in model...
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04/03/2020
Infomax Neural Joint Source-Channel Coding via Adversarial Bit Flip
Although Shannon theory states that it is asymptotically optimal to sepa...
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11/21/2019
Improving Unsupervised Domain Adaptation with Variational Information Bottleneck
Domain adaptation aims to leverage the supervision signal of source doma...
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04/02/2019
Towards Efficient and Unbiased Implementation of Lipschitz Continuity in GANs
Lipschitz continuity recently becomes popular in generative adversarial ...
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02/15/2019
Lipschitz Generative Adversarial Nets
In this paper we study the convergence of generative adversarial network...
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11/15/2018
Guiding the One-to-one Mapping in CycleGAN via Optimal Transport
CycleGAN is capable of learning a one-to-one mapping between two data di...
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07/02/2018
Understanding the Effectiveness of Lipschitz Constraint in Training of GANs via Gradient Analysis
This paper aims to bring a new perspective for understanding GANs, by de...
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03/06/2017