Search Results for author: Huan Li

Found 14 papers, 1 papers with code

Accelerated Gradient Tracking over Time-varying Graphs for Decentralized Optimization

no code implementations6 Apr 2021 Huan Li, Zhouchen Lin

We prove the $O((\frac{\gamma}{1-\sigma_{\gamma}})^2\sqrt{\frac{L}{\epsilon}})$ and $O((\frac{\gamma}{1-\sigma_{\gamma}})^{1. 5}\sqrt{\frac{L}{\mu}}\log\frac{1}{\epsilon})$ complexities for the practical single loop accelerated gradient tracking over time-varying graphs when the problems are nonstrongly convex and strongly convex, respectively, where $\gamma$ and $\sigma_{\gamma}$ are two common constants charactering the network connectivity, $\epsilon$ is the desired precision, and $L$ and $\mu$ are the smoothness and strong convexity constants, respectively.

Federated Learning

An Experimental Analysis of Indoor Spatial Queries: Modeling, Indexing, and Processing

1 code implementation8 Oct 2020 Tiantian Liu, Huan Li, Hua Lu, Muhammad Aamir Cheema, Lidan Shou

Indoor location-based services (LBS), such as POI search and routing, are often built on top of typical indoor spatial queries.

Databases Data Structures and Algorithms

Variance Reduced EXTRA and DIGing and Their Optimal Acceleration for Strongly Convex Decentralized Optimization

no code implementations9 Sep 2020 Huan Li, Zhouchen Lin, Yongchun Fang

Our stochastic gradient computation complexities are the same as the ones of single-machine VR methods, such as SAG, SAGA, and SVRG, and our communication complexities keep the same as those of EXTRA and DIGing, respectively.

Revisiting EXTRA for Smooth Distributed Optimization

no code implementations24 Feb 2020 Huan Li, Zhouchen Lin

EXTRA is a popular method for dencentralized distributed optimization and has broad applications.

Distributed Optimization

AIBench: An Industry Standard Internet Service AI Benchmark Suite

no code implementations13 Aug 2019 Wanling Gao, Fei Tang, Lei Wang, Jianfeng Zhan, Chunxin Lan, Chunjie Luo, Yunyou Huang, Chen Zheng, Jiahui Dai, Zheng Cao, Daoyi Zheng, Haoning Tang, Kunlin Zhan, Biao Wang, Defei Kong, Tong Wu, Minghe Yu, Chongkang Tan, Huan Li, Xinhui Tian, Yatao Li, Junchao Shao, Zhenyu Wang, Xiaoyu Wang, Hainan Ye

On the basis of the AIBench framework, abstracting the real-world data sets and workloads from one of the top e-commerce providers, we design and implement the first end-to-end Internet service AI benchmark, which contains the primary modules in the critical paths of an industry scale application and is scalable to deploy on different cluster scales.

Learning-To-Rank

Hermitian matrices for clustering directed graphs: insights and applications

no code implementations6 Aug 2019 Mihai Cucuringu, Huan Li, He Sun, Luca Zanetti

Graph clustering is a basic technique in machine learning, and has widespread applications in different domains.

Graph Clustering Stochastic Block Model

Optimization Algorithm Inspired Deep Neural Network Structure Design

no code implementations3 Oct 2018 Huan Li, Yibo Yang, Dongmin Chen, Zhouchen Lin

In this paper, we propose the hypothesis that the neural network structure design can be inspired by optimization algorithms and a faster optimization algorithm may lead to a better neural network structure.

Strategies for Searching Video Content with Text Queries or Video Examples

no code implementations17 Jun 2016 Shoou-I Yu, Yi Yang, Zhongwen Xu, Shicheng Xu, Deyu Meng, Zexi Mao, Zhigang Ma, Ming Lin, Xuanchong Li, Huan Li, Zhenzhong Lan, Lu Jiang, Alexander G. Hauptmann, Chuang Gan, Xingzhong Du, Xiaojun Chang

The large number of user-generated videos uploaded on to the Internet everyday has led to many commercial video search engines, which mainly rely on text metadata for search.

Event Detection Video Retrieval

Accelerated Proximal Gradient Methods for Nonconvex Programming

no code implementations NeurIPS 2015 Huan Li, Zhouchen Lin

However, it is still unknown whether the usual APG can ensure the convergence to a critical point in nonconvex programming.

Fast Proximal Linearized Alternating Direction Method of Multiplier with Parallel Splitting

no code implementations14 Nov 2015 Canyi Lu, Huan Li, Zhouchen Lin, Shuicheng Yan

The Augmented Lagragian Method (ALM) and Alternating Direction Method of Multiplier (ADMM) have been powerful optimization methods for general convex programming subject to linear constraint.

Optimized Projections for Compressed Sensing via Direct Mutual Coherence Minimization

no code implementations13 Aug 2015 Canyi Lu, Huan Li, Zhouchen Lin

To the best of our knowledge, this is the first work which directly minimizes the mutual coherence of the projected dictionary with a convergence guarantee.

Linearized Alternating Direction Method with Parallel Splitting and Adaptive Penalty for Separable Convex Programs in Machine Learning

no code implementations18 Oct 2013 Zhouchen Lin, Risheng Liu, Huan Li

However, the traditional alternating direction method (ADM) and its linearized version (LADM, obtained by linearizing the quadratic penalty term) are for the two-block case and cannot be naively generalized to solve the multi-block case.

Distributed Computing

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