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Latent Correlation-Based Multiview Learning and Self-Supervision: A Unifying Perspective


Jun 17, 2021
Qi Lyu, Xiao Fu, Weiran Wang, Songtao Lu

* fixed some typos in the proofs 

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Signal Transformer: Complex-valued Attention and Meta-Learning for Signal Recognition


Jun 12, 2021
Yihong Dong, Ying Peng, Muqiao Yang, Songtao Lu, Qingjiang Shi


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An Efficient Learning Framework For Federated XGBoost Using Secret Sharing And Distributed Optimization


May 12, 2021
Lunchen Xie, Jiaqi Liu, Songtao Lu, Tsung-hui Chang, Qingjiang Shi

* 24 pages, Special issue of ACM Transactions on Intelligent Systems and Technology 

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ScaleCom: Scalable Sparsified Gradient Compression for Communication-Efficient Distributed Training


Apr 21, 2021
Chia-Yu Chen, Jiamin Ni, Songtao Lu, Xiaodong Cui, Pin-Yu Chen, Xiao Sun, Naigang Wang, Swagath Venkataramani, Vijayalakshmi Srinivasan, Wei Zhang, Kailash Gopalakrishnan

* NeurIPS2020 accepted https://proceedings.neurips.cc/paper/2020/hash/9d58963592071dbf38a0fa114269959c-Abstract.html 

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Adversarial Examples for Unsupervised Machine Learning Models


Mar 02, 2021
Chia-Yi Hsu, Pin-Yu Chen, Songtao Lu, Sijia Lu, Chia-Mu Yu


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Federated Acoustic Modeling For Automatic Speech Recognition


Feb 08, 2021
Xiaodong Cui, Songtao Lu, Brian Kingsbury

* Accepted by ICASSP 2021 

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Learned Fine-Tuner for Incongruous Few-Shot Learning


Oct 20, 2020
Pu Zhao, Sijia Liu, Parikshit Ram, Songtao Lu, Djallel Bouneffouf, Xue Lin


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Randomized Bregman Coordinate Descent Methods for Non-Lipschitz Optimization


Jan 15, 2020
Tianxiang Gao, Songtao Lu, Jia Liu, Chris Chu

* First draft 

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Distributed Learning in the Non-Convex World: From Batch to Streaming Data, and Beyond


Jan 14, 2020
Tsung-Hui Chang, Mingyi Hong, Hoi-To Wai, Xinwei Zhang, Songtao Lu

* Submitted to IEEE Signal Processing Magazine Special Issue on Distributed, Streaming Machine Learning; THC, MH, HTW contributed equally 

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Leveraging Two Reference Functions in Block Bregman Proximal Gradient Descent for Non-convex and Non-Lipschitz Problems


Dec 16, 2019
Tianxiang Gao, Songtao Lu, Jia Liu, Chris Chu

* Submit to TSP 

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Learn Electronic Health Records by Fully Decentralized Federated Learning


Dec 10, 2019
Songtao Lu, Yawen Zhang, Yunlong Wang, Christina Mack


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Online Meta-Learning on Non-convex Setting


Oct 22, 2019
Zhenxun Zhuang, Yunlong Wang, Kezi Yu, Songtao Lu


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Improving the Sample and Communication Complexity for Decentralized Non-Convex Optimization: A Joint Gradient Estimation and Tracking Approach


Oct 13, 2019
Haoran Sun, Songtao Lu, Mingyi Hong


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Min-Max Optimization without Gradients: Convergence and Applications to Adversarial ML


Sep 30, 2019
Sijia Liu, Songtao Lu, Xiangyi Chen, Yao Feng, Kaidi Xu, Abdullah Al-Dujaili, Minyi Hong, Una-May Obelilly


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SNAP: Finding Approximate Second-Order Stationary Solutions Efficiently for Non-convex Linearly Constrained Problems


Jul 09, 2019
Songtao Lu, Meisam Razaviyayn, Bo Yang, Kejun Huang, Mingyi Hong


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Signal Demodulation with Machine Learning Methods for Physical Layer Visible Light Communications: Prototype Platform, Open Dataset and Algorithms


Mar 13, 2019
Shuai Ma, Jiahui Dai, Songtao Lu, Hang Li, Han Zhang, Chun Du, Shiyin Li


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Deep Learning for Signal Demodulation in Physical Layer Wireless Communications: Prototype Platform, Open Dataset, and Analytics


Mar 08, 2019
Hongmei Wang, Zhenzhen Wu, Shuai Ma, Songtao Lu, Han Zhang, Guoru Ding, Shiyin Li


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Hybrid Block Successive Approximation for One-Sided Non-Convex Min-Max Problems: Algorithms and Applications


Feb 21, 2019
Songtao Lu, Ioannis Tsaknakis, Mingyi Hong, Yongxin Chen


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Power Market Price Forecasting via Deep Learning


Oct 23, 2018
Yongli Zhu, Songtao Lu, Renchang Dai, Guangyi Liu, Zhiwei Wang

* This manuscript has been accepted by the incoming conference IECON 2018 at Washington DC, USA, Oct. 21-23, 2018 

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On the Sublinear Convergence of Randomly Perturbed Alternating Gradient Descent to Second Order Stationary Solutions


Feb 28, 2018
Songtao Lu, Mingyi Hong, Zhengdao Wang


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A Nonconvex Splitting Method for Symmetric Nonnegative Matrix Factorization: Convergence Analysis and Optimality


Mar 24, 2017
Songtao Lu, Mingyi Hong, Zhengdao Wang

* IEEE Transactions on Signal Processing (to appear) 

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