Search Results for author: Yiming Chen

Found 22 papers, 8 papers with code

Analyzing and Evaluating Faithfulness in Dialogue Summarization

1 code implementation21 Oct 2022 Bin Wang, Chen Zhang, Yan Zhang, Yiming Chen, Haizhou Li

The factual correctness of summaries has the highest priority before practical applications.

Text Summarization

Revisiting Optimal Convergence Rate for Smooth and Non-convex Stochastic Decentralized Optimization

no code implementations14 Oct 2022 Kun Yuan, Xinmeng Huang, Yiming Chen, Xiaohan Zhang, Yingya Zhang, Pan Pan

While (Lu and Sa, 2021) have recently provided an optimal rate for non-convex stochastic decentralized optimization with weight matrices defined over linear graphs, the optimal rate with general weight matrices remains unclear.

Lower Bounds and Nearly Optimal Algorithms in Distributed Learning with Communication Compression

no code implementations8 Jun 2022 Xinmeng Huang, Yiming Chen, Wotao Yin, Kun Yuan

We establish a convergence lower bound for algorithms whether using unbiased or contractive compressors in unidirection or bidirection.

Distributed Optimization

BlueFog: Make Decentralized Algorithms Practical for Optimization and Deep Learning

2 code implementations8 Nov 2021 Bicheng Ying, Kun Yuan, Hanbin Hu, Yiming Chen, Wotao Yin

On mainstream DNN training tasks, BlueFog reaches a much higher throughput and achieves an overall $1. 2\times \sim 1. 8\times$ speedup over Horovod, a state-of-the-art distributed deep learning package based on Ring-Allreduce.

Exponential Graph is Provably Efficient for Decentralized Deep Training

2 code implementations NeurIPS 2021 Bicheng Ying, Kun Yuan, Yiming Chen, Hanbin Hu, Pan Pan, Wotao Yin

Experimental results on a variety of tasks and models demonstrate that decentralized (momentum) SGD over exponential graphs promises both fast and high-quality training.

Revisiting Self-Training for Few-Shot Learning of Language Model

1 code implementation EMNLP 2021 Yiming Chen, Yan Zhang, Chen Zhang, Grandee Lee, Ran Cheng, Haizhou Li

In this work, we revisit the self-training technique for language model fine-tuning and present a state-of-the-art prompt-based few-shot learner, SFLM.

Few-Shot Learning Language Modelling +3

Communicate Then Adapt: An Effective Decentralized Adaptive Method for Deep Training

no code implementations29 Sep 2021 Bicheng Ying, Kun Yuan, Yiming Chen, Hanbin Hu, Yingya Zhang, Pan Pan, Wotao Yin

Decentralized adaptive gradient methods, in which each node averages only with its neighbors, are critical to save communication and wall-clock training time in deep learning tasks.

Bias Loss for Mobile Neural Networks

2 code implementations ICCV 2021 Lusine Abrahamyan, Valentin Ziatchin, Yiming Chen, Nikos Deligiannis

In compact CNNs, due to the limited number of parameters, abundant features are unlikely to be obtained, and feature diversity becomes an essential characteristic.

Image Classification

DecentLaM: Decentralized Momentum SGD for Large-batch Deep Training

1 code implementation ICCV 2021 Kun Yuan, Yiming Chen, Xinmeng Huang, Yingya Zhang, Pan Pan, Yinghui Xu, Wotao Yin

Experimental results on a variety of computer vision tasks and models demonstrate that DecentLaM promises both efficient and high-quality training.

IMU Data Processing For Inertial Aided Navigation: A Recurrent Neural Network Based Approach

no code implementations26 Mar 2021 Ming Zhang, Mingming Zhang, Yiming Chen, Mingyang Li

In this work, we propose a novel method for performing inertial aided navigation, by using deep neural networks (DNNs).

Learned Gradient Compression for Distributed Deep Learning

no code implementations16 Mar 2021 Lusine Abrahamyan, Yiming Chen, Giannis Bekoulis, Nikos Deligiannis

In contrast, we advocate that the gradients across the nodes are correlated and propose methods to leverage this inter-node redundancy to improve compression efficiency.

Image Classification Quantization +1

Bra-ket wormholes in gravitationally prepared states

no code implementations31 Jul 2020 Yiming Chen, Victor Gorbenko, Juan Maldacena

The most promising one also leads to a divergent temperature but by making a projection onto low energy states we find that it has features that look similar to the previous Euclidean case.

High Energy Physics - Theory General Relativity and Quantum Cosmology

Visual-Inertial Localization for Skid-Steering Robots with Kinematic Constraints

no code implementations13 Nov 2019 Xingxing Zuo, Mingming Zhang, Yiming Chen, Yong liu, Guoquan Huang, Mingyang Li

While visual localization or SLAM has witnessed great progress in past decades, when deploying it on a mobile robot in practice, few works have explicitly considered the kinematic (or dynamic) constraints of the real robotic system when designing state estimators.

Visual Localization

Pose Estimation for Ground Robots: On Manifold Representation, Integration, Re-Parameterization, and Optimization

no code implementations8 Sep 2019 Mingming Zhang, Xingxing Zuo, Yiming Chen, Yong liu, Mingyang Li

In this paper, we focus on motion estimation dedicated for non-holonomic ground robots, by probabilistically fusing measurements from the wheel odometer and exteroceptive sensors.

6D Pose Estimation Motion Estimation

FoxNet: A Multi-face Alignment Method

no code implementations22 Apr 2019 Yuxiang Wu, Zehua Cheng, Bin Huang, Yiming Chen, Xinghui Zhu, Weiyang Wang

Multi-face alignment aims to identify geometry structures of multiple faces in an image, and its performance is essential for the many practical tasks, such as face recognition, face tracking, and face animation.

Face Alignment Face Recognition

Automated Generation and Ensemble-Learned Matching of X-ray Absorption Spectra

no code implementations6 Nov 2017 Chen Zheng, Kiran Mathew, Chi Chen, Yiming Chen, Hanmei Tang, Alan Dozier, Joshua J. Kas, Fernando D. Vila, John J. Rehr, Louis F. J. Piper, Kristin Persson, Shyue Ping Ong

We report the development of XASdb, a large database of computed reference X-ray absorption spectra (XAS), and a novel Ensemble-Learned Spectra IdEntification (ELSIE) algorithm for the matching of spectra.

Materials Science

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