no code implementations • CCL 2021 • Chenlin Zhang, Mingwen Wang, Yiming Tan, Ming Yin, Xinyi Zhang
“本文主要以汉语委婉语作为研究对象, 基于大量人工标注, 借助机器学习有监督分类方法, 实现了较高精度的委婉语自动识别, 并基于此对1946年-2017年的《人民日报》中的委婉语历时变化发展情况进行量化统计分析。从大规模数据的角度探讨委婉语历时性发展变化、委婉语与社会之间的共变关系, 验证了语言的格雷什姆规律与更新规律。”
no code implementations • 31 Oct 2024 • Chenyu Wang, Sharut Gupta, Xinyi Zhang, Sana Tonekaboni, Stefanie Jegelka, Tommi Jaakkola, Caroline Uhler
Multimodal representation learning seeks to relate and decompose information inherent in multiple modalities.
no code implementations • 2 Oct 2024 • Xinyi Zhang, Manuel Günther
Face recognition in the wild has gained a lot of focus in the last few years, and many face recognition models are designed to verify faces in medium-quality images.
1 code implementation • 26 Sep 2024 • Qinpeng Cui, Yixuan Liu, Xinyi Zhang, Qiqi Bao, Zhongdao Wang, Qingmin Liao, Li Wang, Tian Lu, Emad Barsoum
In this paper, we present DoSSR, a Domain Shift diffusion-based SR model that capitalizes on the generative powers of pretrained diffusion models while significantly enhancing efficiency by initiating the diffusion process with low-resolution (LR) images.
no code implementations • 6 Aug 2024 • Xinyi Zhang, Qiqi Bao, Qinpeng Cui, Wenming Yang, Qingmin Liao
This architecture introduces local enhancement with GCN by capturing relationships between neighboring joints, thus producing new representations to complement Mamba's outputs.
no code implementations • 5 Aug 2024 • Yiyan Li, Haoyang Li, Zhao Pu, Jing Zhang, Xinyi Zhang, Tao Ji, Luming Sun, Cuiping Li, Hong Chen
Knob tuning plays a crucial role in optimizing databases by adjusting knobs to enhance database performance.
no code implementations • 3 Jun 2024 • Li Wang, Xiangzheng Fu, Jiahao Yang, Xinyi Zhang, Xiucai Ye, Yiping Liu, Tetsuya Sakurai, Xiangxiang Zeng
Deep learning holds a big promise for optimizing existing peptides with more desirable properties, a critical step towards accelerating new drug discovery.
no code implementations • 3 Jun 2024 • Sichun Luo, Wei Shao, Yuxuan Yao, Jian Xu, Mingyang Liu, Qintong Li, Bowei He, Maolin Wang, Guanzhi Deng, Hanxu Hou, Xinyi Zhang, Linqi Song
Nowadays, large language models (LLMs) have been integrated with conventional recommendation models to improve recommendation performance.
no code implementations • 28 May 2024 • Qilin Wang, Zhengkai Jiang, Chengming Xu, Jiangning Zhang, Yabiao Wang, Xinyi Zhang, Yun Cao, Weijian Cao, Chengjie Wang, Yanwei Fu
This enables accurate alignment of pose and shape in the generated videos, providing a robust framework capable of handling a wide range of body shapes and dynamic hand movements.
1 code implementation • 19 May 2024 • Jingyang Wu, Xinyi Zhang, Fangyixuan Huang, Haochen Zhou, Rohtiash Chandra
In this study, we review the literature about deep learning for cryptocurrency price forecasting and evaluate novel deep learning models for cryptocurrency stock price prediction.
1 code implementation • 21 Mar 2024 • Xinyi Zhang, Johanna Sophie Bieri, Manuel Günther
In this paper, we extend gradient-based CAM techniques to work with binary classifiers and visualize the active regions for binary facial attribute classifiers.
no code implementations • 25 Jan 2024 • Sichun Luo, Yuxuan Yao, Bowei He, Yinya Huang, Aojun Zhou, Xinyi Zhang, Yuanzhang Xiao, Mingjie Zhan, Linqi Song
Conventional recommendation methods have achieved notable advancements by harnessing collaborative or sequential information from user behavior.
no code implementations • 23 Nov 2023 • Mengling Hu, Chaochao Chen, Weiming Liu, Xinyi Zhang, Xinting Liao, Xiaolin Zheng
However, most existing graph clustering methods focus on node-level clustering, i. e., grouping nodes in a single graph into clusters.
1 code implementation • 12 Sep 2023 • Qinpeng Cui, Xinyi Zhang, Zongqing Lu, Qingmin Liao
In this work, we formulate the sampling process as an extended reverse-time SDE (ER SDE), unifying prior explorations into ODEs and SDEs.
no code implementations • 5 Sep 2023 • Yang Li, Huaijun Jiang, Yu Shen, Yide Fang, Xiaofeng Yang, Danqing Huang, Xinyi Zhang, Wentao Zhang, Ce Zhang, Peng Chen, Bin Cui
The distributed data analytic system -- Spark is a common choice for processing massive volumes of heterogeneous data, while it is challenging to tune its parameters to achieve high performance.
no code implementations • 11 May 2023 • Sichun Luo, Yuanzhang Xiao, Xinyi Zhang, Yang Liu, Wenbo Ding, Linqi Song
Each user learns a personalized model by combining the global federated model, the cluster-level federated model, and its own fine-tuned local model.
no code implementations • 10 Mar 2023 • Xinyi Zhang, Zhuo Chang, Hong Wu, Yang Li, Jia Chen, Jian Tan, Feifei Li, Bin Cui
To tune different components for DBMS, a coordinating mechanism is needed to make the multiple agents cognizant of each other.
no code implementations • 12 Feb 2023 • Tianyi Bai, Yang Li, Yu Shen, Xinyi Zhang, Wentao Zhang, Bin Cui
A wide spectrum of design and decision problems, including parameter tuning, A/B testing and drug design, intrinsically are instances of black-box optimization.
no code implementations • ICCV 2023 • Xinyi Zhang, Naiqi Li, Jiawei Li, Tao Dai, Yong Jiang, Shu-Tao Xia
Unsupervised surface anomaly detection aims at discovering and localizing anomalous patterns using only anomaly-free training samples.
no code implementations • 20 Aug 2022 • Sichun Luo, Xinyi Zhang, Yuanzhang Xiao, Linqi Song
For example, in a mobile game recommendation, contextual features like locations, battery, and storage levels of mobile devices are frequently drifting over time.
no code implementations • 8 Aug 2022 • Tiago de Freitas Pereira, Dominic Schmidli, Yu Linghu, Xinyi Zhang, Sébastien Marcel, Manuel Günther
With the popularity of deep learning and its capability to solve a huge variety of different problems, face recognition researchers have concentrated effort on creating better models under this paradigm.
no code implementations • 8 Aug 2022 • Jiawei Li, Chenxi Lan, Xinyi Zhang, Bolin Jiang, Yuqiu Xie, Naiqi Li, Yan Liu, Yaowei Li, Enze Huo, Bin Chen
To make a step forward, this paper outlines an automatic annotation system called SsaA, working in a self-supervised learning manner, for continuously making the online visual inspection in the manufacturing automation scenarios.
1 code implementation • 29 Apr 2022 • Xinyi Zhang, Cong Hao, Peipei Zhou, Alex Jones, Jingtong Hu
The heterogeneity in ML models comes from multi-sensor perceiving and multi-task learning, i. e., multi-modality multi-task (MMMT), resulting in diverse deep neural network (DNN) layers and computation patterns.
no code implementations • 18 Feb 2022 • Yue Tang, Xinyi Zhang, Peipei Zhou, Jingtong Hu
In this work, we design EF-Train, an efficient DNN training accelerator with a unified channel-level parallelism-based convolution kernel that can achieve end-to-end training on resource-limited low-power edge-level FPGAs.
no code implementations • CVPR 2022 • Feida Zhu, Junwei Zhu, Wenqing Chu, Xinyi Zhang, Xiaozhong Ji, Chengjie Wang, Ying Tai
Moreover, we introduce hybrid-level losses to jointly train the shape and generative priors together with other network parts such that these two priors better adapt to our blind face restoration task.
no code implementations • 1 Oct 2021 • Toshiko Shibano, Xinyi Zhang, Mia Taige Li, Haejin Cho, Peter Sullivan, Muhammad Abdul-Mageed
To address the performance gap of English ASR models on L2 English speakers, we evaluate fine-tuning of pretrained wav2vec 2. 0 models (Baevski et al., 2020; Xu et al., 2021) on L2-ARCTIC, a non-native English speech corpus (Zhao et al., 2018) under different training settings.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +3
no code implementations • CVPR 2021 • Xinyi Zhang, Hang Dong, Jinshan Pan, Chao Zhu, Ying Tai, Chengjie Wang, Jilin Li, Feiyue Huang, Fei Wang
On the other hand, the video dehazing algorithms, which can acquire more satisfying dehazing results by exploiting the temporal redundancy from neighborhood hazy frames, receive less attention due to the absence of the video dehazing datasets.
no code implementations • 13 Apr 2021 • Xinyi Zhang, Chengfang Fang, Jie Shi
We find the effectiveness of existing techniques significantly affected by the absence of pre-trained models.
1 code implementation • 6 Apr 2021 • Xinyi Zhang, Lihui Chen
To address this issue, a novel meta-path-based HIN representation learning framework named mSHINE is designed to simultaneously learn multiple node representations for different meta-paths.
1 code implementation • 23 Sep 2020 • Xinyi Zhang, Jiahao Xu, Charlie Soh, Lihui Chen
In this paper, we propose a Label-based Attention for Hierarchical Mutlti-label Text Classification Neural Network (LA-HCN), where the novel label-based attention module is designed to hierarchically extract important information from the text based on the labels from different hierarchy levels.
Multi Label Text Classification Multi-Label Text Classification +1
no code implementations • 24 Jul 2020 • Jing Chen, Chenhui Wang, Kejun Wang, Chaoqun Yin, Cong Zhao, Tao Xu, Xinyi Zhang, Ziqiang Huang, Meichen Liu, Tao Yang
Existing multimodal emotion databases in the real-world conditions are few and small, with a limited number of subjects and expressed in a single language.
1 code implementation • CVPR 2020 • Hang Dong, Jinshan Pan, Lei Xiang, Zhe Hu, Xinyi Zhang, Fei Wang, Ming-Hsuan Yang
To address the issue of preserving spatial information in the U-Net architecture, we design a dense feature fusion module using the back-projection feedback scheme.
Ranked #11 on Image Dehazing on Haze4k
1 code implementation • 2 Mar 2020 • Xinyi Zhang, Hang Dong, Zhe Hu, Wei-Sheng Lai, Fei Wang, Ming-Hsuan Yang
To address this problem, we propose a dual-branch convolutional neural network to extract base features and recovered features separately.
2 code implementations • 23 Apr 2019 • Linsen Dong, Guanyu Gao, Xinyi Zhang, Liang-Yu Chen, Yonggang Wen
Model-Based Reinforcement Learning (MBRL) is one category of Reinforcement Learning (RL) algorithms which can improve sampling efficiency by modeling and approximating system dynamics.
no code implementations • 31 Jan 2019 • Weiwen Jiang, Xinyi Zhang, Edwin H. -M. Sha, Lei Yang, Qingfeng Zhuge, Yiyu Shi, Jingtong Hu
In addition, with a performance abstraction model to analyze the latency of neural architectures without training, our framework can quickly prune architectures that do not satisfy the specification, leading to higher efficiency.
no code implementations • 1 Sep 2018 • Xiaowei Xu, Xinyi Zhang, Bei Yu, X. Sharon Hu, Christopher Rowen, Jingtong Hu, Yiyu Shi
The 55th Design Automation Conference (DAC) held its first System Design Contest (SDC) in 2018.
2 code implementations • 27 Jul 2018 • Xinyi Zhang, Hang Dong, Zhe Hu, Wei-Sheng Lai, Fei Wang, Ming-Hsuan Yang
Single-image super-resolution is a fundamental task for vision applications to enhance the image quality with respect to spatial resolution.