Search Results for author: Pei Zhang

Found 36 papers, 9 papers with code

Alibaba Speech Translation Systems for IWSLT 2018

no code implementations IWSLT (EMNLP) 2018 Nguyen Bach, Hongjie Chen, Kai Fan, Cheung-Chi Leung, Bo Li, Chongjia Ni, Rong Tong, Pei Zhang, Boxing Chen, Bin Ma, Fei Huang

This work describes the En→De Alibaba speech translation system developed for the evaluation campaign of the International Workshop on Spoken Language Translation (IWSLT) 2018.

Sentence Translation

One-Step Late Fusion Multi-view Clustering with Compressed Subspace

no code implementations3 Jan 2024 Qiyuan Ou, Pei Zhang, Sihang Zhou, En Zhu

Late fusion multi-view clustering (LFMVC) has become a rapidly growing class of methods in the multi-view clustering (MVC) field, owing to its excellent computational speed and clustering performance.


Transferring a molecular foundation model for polymer property predictions

no code implementations25 Oct 2023 Pei Zhang, Logan Kearney, Debsindhu Bhowmik, Zachary Fox, Amit K. Naskar, John Gounley

Transformer-based large language models have remarkable potential to accelerate design optimization for applications such as drug development and materials discovery.

Data Augmentation Transfer Learning

Anchor-based Multi-view Subspace Clustering with Hierarchical Feature Descent

1 code implementation11 Oct 2023 Qiyuan Ou, Siwei Wang, Pei Zhang, Sihang Zhou, En Zhu

However, we propose Anchor-based Multi-view Subspace Clustering with Hierarchical Feature Descent(MVSC-HFD) to tackle the discrepancy among views through hierarchical feature descent and project to a common subspace( STAGE 1), which reveals dependency of different views.

Clustering Multi-view Subspace Clustering

DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies

no code implementations6 Oct 2023 Shuaiwen Leon Song, Bonnie Kruft, Minjia Zhang, Conglong Li, Shiyang Chen, Chengming Zhang, Masahiro Tanaka, Xiaoxia Wu, Jeff Rasley, Ammar Ahmad Awan, Connor Holmes, Martin Cai, Adam Ghanem, Zhongzhu Zhou, Yuxiong He, Pete Luferenko, Divya Kumar, Jonathan Weyn, Ruixiong Zhang, Sylwester Klocek, Volodymyr Vragov, Mohammed AlQuraishi, Gustaf Ahdritz, Christina Floristean, Cristina Negri, Rao Kotamarthi, Venkatram Vishwanath, Arvind Ramanathan, Sam Foreman, Kyle Hippe, Troy Arcomano, Romit Maulik, Maxim Zvyagin, Alexander Brace, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael Irvin, J. Gregory Pauloski, Logan Ward, Valerie Hayot, Murali Emani, Zhen Xie, Diangen Lin, Maulik Shukla, Ian Foster, James J. Davis, Michael E. Papka, Thomas Brettin, Prasanna Balaprakash, Gina Tourassi, John Gounley, Heidi Hanson, Thomas E Potok, Massimiliano Lupo Pasini, Kate Evans, Dan Lu, Dalton Lunga, Junqi Yin, Sajal Dash, Feiyi Wang, Mallikarjun Shankar, Isaac Lyngaas, Xiao Wang, Guojing Cong, Pei Zhang, Ming Fan, Siyan Liu, Adolfy Hoisie, Shinjae Yoo, Yihui Ren, William Tang, Kyle Felker, Alexey Svyatkovskiy, Hang Liu, Ashwin Aji, Angela Dalton, Michael Schulte, Karl Schulz, Yuntian Deng, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Anima Anandkumar, Rick Stevens

In the upcoming decade, deep learning may revolutionize the natural sciences, enhancing our capacity to model and predict natural occurrences.

Neuromorphic Imaging with Joint Image Deblurring and Event Denoising

no code implementations28 Sep 2023 Pei Zhang, Haosen Liu, Zhou Ge, Chutian Wang, Edmund Y. Lam

Neuromorphic imaging reacts to per-pixel brightness changes of a dynamic scene with high temporal precision and responds with asynchronous streaming events as a result.

Deblurring Denoising +1

Neuromorphic Imaging and Classification with Graph Learning

no code implementations27 Sep 2023 Pei Zhang, Chutian Wang, Edmund Y. Lam

Bio-inspired neuromorphic cameras asynchronously record pixel brightness changes and generate sparse event streams.

Classification Graph Learning

Normality Learning-based Graph Anomaly Detection via Multi-Scale Contrastive Learning

1 code implementation12 Sep 2023 Jingcan Duan, Pei Zhang, Siwei Wang, Jingtao Hu, Hu Jin, Jiaxin Zhang, Haifang Zhou, Xinwang Liu

Finally, the model is refined with the only input of reliable normal nodes and learns a more accurate estimate of normality so that anomalous nodes can be more easily distinguished.

Contrastive Learning Graph Anomaly Detection

Efficient Multi-View Graph Clustering with Local and Global Structure Preservation

1 code implementation31 Aug 2023 Yi Wen, Suyuan Liu, Xinhang Wan, Siwei Wang, Ke Liang, Xinwang Liu, Xihong Yang, Pei Zhang

Anchor-based multi-view graph clustering (AMVGC) has received abundant attention owing to its high efficiency and the capability to capture complementary structural information across multiple views.

Clustering Graph Clustering +1

Meta-Reasoning: Semantics-Symbol Deconstruction for Large Language Models

1 code implementation30 Jun 2023 Yiming Wang, Zhuosheng Zhang, Pei Zhang, Baosong Yang, Rui Wang

Neural-symbolic methods have demonstrated efficiency in enhancing the reasoning abilities of large language models (LLMs).

Domain Generalization In-Context Learning +1

Event Encryption: Rethinking Privacy Exposure for Neuromorphic Imaging

no code implementations6 Jun 2023 Pei Zhang, Shuo Zhu, Edmund Y. Lam

Bio-inspired neuromorphic cameras sense illumination changes on a per-pixel basis and generate spatiotemporal streaming events within microseconds in response, offering visual information with high temporal resolution over a high dynamic range.

Privacy Preserving

Characterization and Generation of 3D Realistic Geological Particles with Metaball Descriptor based on X-Ray Computed Tomography

no code implementations5 Feb 2023 Yifeng Zhao, Xiangbo Gao, Pei Zhang, Liang Lei, S. A. Galindo-Torres, Stan Z. Li

This algorithm can capture the main contour of parental particles with a series of non-overlapping spheres and refine surface-texture details through gradient search.

PigV$^2$: Monitoring Pig Vital Signs through Ground Vibrations Induced by Heartbeat and Respiration

no code implementations7 Dec 2022 Yiwen Dong, Jesse R Codling, Gary Rohrer, Jeremy Miles, Sudhendu Sharma, Tami Brown-Brandl, Pei Zhang, Hae Young Noh

In this paper, we introduce PigV$^2$, the first system to monitor pig heart rate and respiratory rate through ground vibrations.

Graph Anomaly Detection via Multi-Scale Contrastive Learning Networks with Augmented View

no code implementations1 Dec 2022 Jingcan Duan, Siwei Wang, Pei Zhang, En Zhu, Jingtao Hu, Hu Jin, Yue Liu, Zhibin Dong

However, they neglect the subgraph-subgraph comparison information which the normal and abnormal subgraph pairs behave differently in terms of embeddings and structures in GAD, resulting in sub-optimal task performance.

Contrastive Learning Graph Anomaly Detection

Scalable training of graph convolutional neural networks for fast and accurate predictions of HOMO-LUMO gap in molecules

no code implementations22 Jul 2022 Jong Youl Choi, Pei Zhang, Kshitij Mehta, Andrew Blanchard, Massimiliano Lupo Pasini

Graph Convolutional Neural Network (GCNN) is a popular class of deep learning (DL) models in material science to predict material properties from the graph representation of molecular structures.

Distributed Computing Management

Multi-task graph neural networks for simultaneous prediction of global and atomic properties in ferromagnetic systems

1 code implementation4 Feb 2022 Massimiliano Lupo Pasini, Pei Zhang, Samuel Temple Reeve, Jong Youl Choi

We train HydraGNN on an open-source ab initio density functional theory (DFT) dataset for iron-platinum (FePt) with a fixed body centered tetragonal (BCT) lattice structure and fixed volume to simultaneously predict the mixing enthalpy (a global feature of the system), the atomic charge transfer, and the atomic magnetic moment across configurations that span the entire compositional range.

Multi-Task Learning

Sharp Attention for Sequence to Sequence Learning

no code implementations29 Sep 2021 Pei Zhang, Hua Liu

Attention mechanism has been widely applied to tasks that output some sequence from an input image.

Hard Attention Scene Text Recognition

PI3NN: Out-of-distribution-aware prediction intervals from three neural networks

1 code implementation ICLR 2022 Siyan Liu, Pei Zhang, Dan Lu, Guannan Zhang

First, existing PI methods require retraining of neural networks (NNs) for every given confidence level and suffer from the crossing issue in calculating multiple PIs.

Prediction Intervals Uncertainty Quantification

A Data-driven feature selection and machine-learning model benchmark for the prediction of longitudinal dispersion coefficient

no code implementations16 Jul 2021 Yifeng Zhao, Pei Zhang, S. A. Galindo-Torres, Stan Z. Li

Then, a global optimal feature set (the channel width, the flow velocity, the channel slope and the cross sectional area) was proposed through numerical comparison of the distilled local optimums in performance with representative ML models.

Ensemble Learning feature selection

Context-Interactive Pre-Training for Document Machine Translation

no code implementations NAACL 2021 Pengcheng Yang, Pei Zhang, Boxing Chen, Jun Xie, Weihua Luo

Document machine translation aims to translate the source sentence into the target language in the presence of additional contextual information.

Machine Translation Sentence +1

Multi-view Clustering with Deep Matrix Factorization and Global Graph Refinement

no code implementations1 May 2021 Chen Zhang, Siwei Wang, Wenxuan Tu, Pei Zhang, Xinwang Liu, Changwang Zhang, Bo Yuan

Multi-view clustering is an important yet challenging task in machine learning and data mining community.


Retrieving High-Dimensional Quantum Steering From a Noisy Environment with N Measurement Settings

no code implementations12 Jan 2021 Rui Qu, Yunlong Wang, Min An, Feiran Wang, Hongrong Li, Hong Gao, Fuli Li, Pei Zhang

One of the most often implied benefits of high-dimensional (HD) quantum systems is to lead to stronger forms of correlations, featuring increased robustness to noise.

Quantum Physics

Long-Short Term Masking Transformer: A Simple but Effective Baseline for Document-level Neural Machine Translation

no code implementations EMNLP 2020 Pei Zhang, Boxing Chen, Niyu Ge, Kai Fan

In this paper, we research extensively the pros and cons of the standard transformer in document-level translation, and find that the auto-regressive property can simultaneously bring both the advantage of the consistency and the disadvantage of error accumulation.

Machine Translation NMT +1

Extending Label Smoothing Regularization with Self-Knowledge Distillation

no code implementations11 Sep 2020 Ji-Yue Wang, Pei Zhang, Wen-feng Pang, Jie Li

The experiment results confirm that the TC can help LsrKD and MrKD to boost training, especially on the networks they are failed.

Self-Knowledge Distillation

Learning Contextualized Sentence Representations for Document-Level Neural Machine Translation

no code implementations30 Mar 2020 Pei Zhang, Xu Zhang, Wei Chen, Jian Yu, Yan-Feng Wang, Deyi Xiong

In this paper, we propose a new framework to model cross-sentence dependencies by training neural machine translation (NMT) to predict both the target translation and surrounding sentences of a source sentence.

Document Level Machine Translation Machine Translation +4

Visual Agreement Regularized Training for Multi-Modal Machine Translation

no code implementations27 Dec 2019 Pengcheng Yang, Boxing Chen, Pei Zhang, Xu sun

Further analysis demonstrates that the proposed regularized training can effectively improve the agreement of attention on the image, leading to better use of visual information.

Machine Translation Sentence +1

Lattice Transformer for Speech Translation

no code implementations ACL 2019 Pei Zhang, Boxing Chen, Niyu Ge, Kai Fan

Recent advances in sequence modeling have highlighted the strengths of the transformer architecture, especially in achieving state-of-the-art machine translation results.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +3

PSA: A novel optimization algorithm based on survival rules of porcellio scaber

no code implementations28 Sep 2017 Yinyan Zhang, Pei Zhang, Shuai Li

Bio-inspired algorithms such as neural network algorithms and genetic algorithms have received a significant amount of attention in both academic and engineering societies.

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