Wang, Shaojun

22 publications

ICML 2024 DFlow: A Generative Model Combining Denoising AutoEncoder and Normalizing Flow for High Fidelity Waveform Generation Chenfeng Miao, Qingying Zhu, Minchuan Chen, Wei Hu, Zijian Li, Shaojun Wang, Jing Xiao

AISTATS 2021 Understanding Gradient Clipping in Incremental Gradient Methods Jiang Qian, Yuren Wu, Bojin Zhuang, Shaojun Wang, Jing Xiao

ICML 2021 EfficientTTS: An Efficient and High-Quality Text-to-Speech Architecture Chenfeng Miao, Liang Shuang, Zhengchen Liu, Chen Minchuan, Jun Ma, Shaojun Wang, Jing Xiao

AAAI 2020 An Iterative Polishing Framework Based on Quality Aware Masked Language Model for Chinese Poetry Generation Liming Deng, Jie Wang, Hang-Ming Liang, Hui Chen, Zhiqiang Xie, Bojin Zhuang, Shaojun Wang, Jing Xiao

IJCAI 2020 Generating Reasonable Legal Text Through the Combination of Language Modeling and Question Answering Weijing Huang, Xianfeng Liao, Zhiqiang Xie, Jiang Qian, Bojin Zhuang, Shaojun Wang, Jing Xiao

AISTATS 2019 Adversarial Discrete Sequence Generation Without Explicit NeuralNetworks as Discriminators Zhongliang Li, Tian Xia, Xingyu Lou, Kaihe Xu, Shaojun Wang, Jing Xiao

AAAI 2018 Slim Embedding Layers for Recurrent Neural Language Models Zhongliang Li, Raymond Kulhanek, Shaojun Wang, Yunxin Zhao, Shuang Wu

IJCAI 2015 A Direct Boosting Approach for Semi-Supervised Classification Shaodan Zhai, Tian Xia, Zhongliang Li, Shaojun Wang

NeurIPS 2013 Direct 0-1 Loss Minimization and Margin Maximization with Boosting Shaodan Zhai, Tian Xia, Ming Tan, Shaojun Wang

NeurIPS 2009 A Rate Distortion Approach for Semi-Supervised Conditional Random Fields Yang Wang, Gholamreza Haffari, Shaojun Wang, Greg Mori

ICML 2008 Boosting with Incomplete Information Gholamreza Haffari, Yang Wang, Shaojun Wang, Greg Mori, Feng Jiao

AAAI 2008 Constrained Classification on Structured Data Chi-Hoon Lee, Matthew R. G. Brown, Russell Greiner, Shaojun Wang, Albert Murtha

NeurIPS 2006 Implicit Online Learning with Kernels Li Cheng, Dale Schuurmans, Shaojun Wang, Terry Caelli, S.v.n. Vishwanathan

NeurIPS 2006 Learning to Model Spatial Dependency: Semi-Supervised Discriminative Random Fields Chi-hoon Lee, Shaojun Wang, Feng Jiao, Dale Schuurmans, Russell Greiner

ICML 2006 Using Query-Specific Variance Estimates to Combine Bayesian Classifiers Chi-Hoon Lee, Russell Greiner, Shaojun Wang

MLJ 2005 Combining Statistical Language Models via the Latent Maximum Entropy Principle Shaojun Wang, Dale Schuurmans, Fuchun Peng, Yunxin Zhao

ICML 2005 Exploiting Syntactic, Semantic and Lexical Regularities in Language Modeling via Directed Markov Random Fields Shaojun Wang, Shaomin Wang, Russell Greiner, Dale Schuurmans, Li Cheng

ICML 2005 Variational Bayesian Image Modelling Li Cheng, Feng Jiao, Dale Schuurmans, Shaojun Wang

UAI 2003 Boltzmann Machine Learning with the Latent Maximum Entropy Principle Shaojun Wang, Dale Schuurmans, Fuchun Peng, Yunxin Zhao

AISTATS 2003 Latent Maximum Entropy Approach for Semantic $n$-Gram Language Modeling Shaojun Wang, Dale Schuurmans, Fuchun Peng

ALT 2003 Learning Continuous Latent Variable Models with Bregman Divergences Shaojun Wang, Dale Schuurmans

ICML 2003 Learning Mixture Models with the Latent Maximum Entropy Principle Shaojun Wang, Dale Schuurmans, Fuchun Peng, Yunxin Zhao