Yuxuan Song | DeepAI

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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...

0 Yuxuan Song, et al. ∙

∙ 04/19/2023

Accelerate Support Vector Clustering via Spectrum-Preserving Data Compression

Support vector clustering is an important clustering method. However, it...

0 Yuxuan Song, et al. ∙

∙ 07/20/2021

Follow Your Path: a Progressive Method for Knowledge Distillation

Deep neural networks often have a huge number of parameters, which posts...

0 Wenxian Shi, et al. ∙

∙ 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...

0 Ning Miao, et al. ∙

∙ 07/12/2020

Improving Maximum Likelihood Training for Text Generation with Density Ratio Estimation

Auto-regressive sequence generative models trained by Maximum Likelihood...

4 Yuxuan Song, et al. ∙

∙ 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...

0 Yuxuan Song, et al. ∙

∙ 04/03/2020

Infomax Neural Joint Source-Channel Coding via Adversarial Bit Flip

Although Shannon theory states that it is asymptotically optimal to sepa...

0 Yuxuan Song, et al. ∙

∙ 11/21/2019

Improving Unsupervised Domain Adaptation with Variational Information Bottleneck

Domain adaptation aims to leverage the supervision signal of source doma...

0 Yuxuan Song, et al. ∙

∙ 04/02/2019

Towards Efficient and Unbiased Implementation of Lipschitz Continuity in GANs

Lipschitz continuity recently becomes popular in generative adversarial ...

0 Zhiming Zhou, et al. ∙

∙ 02/15/2019

Lipschitz Generative Adversarial Nets

In this paper we study the convergence of generative adversarial network...

0 Zhiming Zhou, et al. ∙

∙ 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...

0 Guansong Lu, et al. ∙

∙ 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...

4 Zhiming Zhou, et al. ∙

∙ 03/06/2017

Activation Maximization Generative Adversarial Nets

Class label information has been empirically proven to be very useful in...

0 Zhiming Zhou, et al. ∙

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