Wenlin Wang | DeepAI

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Wei Liu
370 publications
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178 publications
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150 publications
Vaneet Aggarwal
117 publications
Zhe Gan
102 publications
Heng Huang
99 publications
Changyou Chen
87 publications
Dejing Dou
87 publications
Chunyuan Li
84 publications
Yizhe Zhang
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Yifan Sun
74 publications

∙ 06/03/2021

JIZHI: A Fast and Cost-Effective Model-As-A-Service System for Web-Scale Online Inference at Baidu

In modern internet industries, deep learning based recommender systems h...

0 Hao Liu, et al. ∙

∙ 10/12/2020

Improving Text Generation with Student-Forcing Optimal Transport

Neural language models are often trained with maximum likelihood estimat...

2 Guoyin Wang, et al. ∙

∙ 05/04/2020

Improving Adversarial Text Generation by Modeling the Distant Future

Auto-regressive text generation models usually focus on local fluency, a...

0 Ruiyi Zhang, et al. ∙

∙ 01/20/2020

Nested-Wasserstein Self-Imitation Learning for Sequence Generation

Reinforcement learning (RL) has been widely studied for improving sequen...

0 Ruiyi Zhang, et al. ∙

∙ 11/20/2019

Graph-Driven Generative Models for Heterogeneous Multi-Task Learning

We propose a novel graph-driven generative model, that unifies multiple ...

0 Wenlin Wang, et al. ∙

∙ 10/21/2019

Collaborative Filtering with A Synthetic Feedback Loop

We propose a novel learning framework for recommendation systems, assist...

0 Wenlin Wang, et al. ∙

∙ 10/20/2019

An Optimal Transport Framework for Zero-Shot Learning

We present an optimal transport (OT) framework for generalized zero-shot...

0 Wenlin Wang, et al. ∙

∙ 09/30/2019

Improving Textual Network Learning with Variational Homophilic Embeddings

The performance of many network learning applications crucially hinges o...

0 Wenlin Wang, et al. ∙

∙ 09/14/2019

Ouroboros: On Accelerating Training of Transformer-Based Language Models

Language models are essential for natural language processing (NLP) task...

0 Qian Yang, et al. ∙

∙ 06/05/2019

Improving Textual Network Embedding with Global Attention via Optimal Transport

Constituting highly informative network embeddings is an important tool ...

0 Liqun Chen, et al. ∙

∙ 05/15/2019

On Norm-Agnostic Robustness of Adversarial Training

Adversarial examples are carefully perturbed in-puts for fooling machine...

0 Bai Li, et al. ∙

∙ 03/17/2019

Topic-Guided Variational Autoencoders for Text Generation

We propose a topic-guided variational autoencoder (TGVAE) model for text...

0 Wenlin Wang, et al. ∙

∙ 11/02/2018

Sequence Generation with Guider Network

Sequence generation with reinforcement learning (RL) has received signif...

0 Ruiyi Zhang, et al. ∙

∙ 09/12/2018

Distilled Wasserstein Learning for Word Embedding and Topic Modeling

We propose a novel Wasserstein method with a distillation mechanism, yie...

0 Hongteng Xu, et al. ∙

∙ 09/10/2018

Second-Order Adversarial Attack and Certifiable Robustness

We propose a powerful second-order attack method that outperforms existi...

0 Bai Li, et al. ∙

∙ 05/29/2018

A Unified Particle-Optimization Framework for Scalable Bayesian Sampling

There has been recent interest in developing scalable Bayesian sampling ...

0 Changyou Chen, et al. ∙

∙ 05/24/2018

Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms

Many deep learning architectures have been proposed to model the composi...

0 Dinghan Shen, et al. ∙

∙ 05/14/2018

NASH: Toward End-to-End Neural Architecture for Generative Semantic Hashing

Semantic hashing has become a powerful paradigm for fast similarity sear...

0 Dinghan Shen, et al. ∙

∙ 05/10/2018

Joint Embedding of Words and Labels for Text Classification

Word embeddings are effective intermediate representations for capturing...

0 Guoyin Wang, et al. ∙

∙ 02/25/2018

Wide Compression: Tensor Ring Nets

Deep neural networks have demonstrated state-of-the-art performance in a...

0 Wenqi Wang, et al. ∙

∙ 12/28/2017

Topic Compositional Neural Language Model

We propose a Topic Compositional Neural Language Model (TCNLM), a novel ...

0 Wenlin Wang, et al. ∙

∙ 12/01/2017

InverseNet: Solving Inverse Problems with Splitting Networks

We propose a new method that uses deep learning techniques to solve the ...

0 Kai Fan, et al. ∙

∙ 11/15/2017

Zero-Shot Learning via Class-Conditioned Deep Generative Models

We present a deep generative model for learning to predict classes not s...

0 Wenlin Wang, et al. ∙

∙ 09/04/2017

A Convergence Analysis for A Class of Practical Variance-Reduction Stochastic Gradient MCMC

Stochastic gradient Markov Chain Monte Carlo (SG-MCMC) has been develope...

0 Changyou Chen, et al. ∙

∙ 09/04/2017

Continuous-Time Flows for Deep Generative Models

Normalizing flows have been developed recently as a method for drawing s...

0 Changyou Chen, et al. ∙

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