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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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