Search Results for author: Mi Zhang

Found 25 papers, 10 papers with code

Convolution over Hierarchical Syntactic and Lexical Graphs for Aspect Level Sentiment Analysis

no code implementations EMNLP 2020 Mi Zhang, Tieyun Qian

Moreover, we build a concept hierarchy on both the syntactic and lexical graphs for differentiating various types of dependency relations or lexical word pairs.

Sentiment Analysis

Cracking White-box DNN Watermarks via Invariant Neuron Transforms

no code implementations30 Apr 2022 Yifan Yan, Xudong Pan, Yining Wang, Mi Zhang, Min Yang

On $9$ state-of-the-art white-box watermarking schemes and a broad set of industry-level DNN architectures, our attack for the first time reduces the embedded identity message in the protected models to be almost random.

Deep AutoAugment

1 code implementation11 Mar 2022 Yu Zheng, Zhi Zhang, Shen Yan, Mi Zhang

In this work, instead of fixing a set of hand-picked default augmentations alongside the searched data augmentations, we propose a fully automated approach for data augmentation search named Deep AutoAugment (DeepAA).

AutoML Data Augmentation +1

Automatically Generating Counterfactuals for Relation Classification

no code implementations22 Feb 2022 Mi Zhang, Tieyun Qian, Ting Zhang

In this paper, we formulate the problem of automatically generating CAD for RC tasks from an entity-centric viewpoint, and develop a novel approach to derive contextual counterfactuals for entities.

Classification Natural Language Processing +1

Multiview Transformers for Video Recognition

1 code implementation CVPR 2022 Shen Yan, Xuehan Xiong, Anurag Arnab, Zhichao Lu, Mi Zhang, Chen Sun, Cordelia Schmid

Video understanding requires reasoning at multiple spatiotemporal resolutions -- from short fine-grained motions to events taking place over longer durations.

 Ranked #1 on Action Classification on Kinetics-400 (using extra training data)

Action Classification Action Recognition +1

Federated Learning for Internet of Things: Applications, Challenges, and Opportunities

no code implementations15 Nov 2021 Tuo Zhang, Lei Gao, Chaoyang He, Mi Zhang, Bhaskar Krishnamachari, Salman Avestimehr

In this paper, we will discuss the opportunities and challenges of FL in IoT platforms, as well as how it can enable diverse IoT applications.

Federated Learning

FedTune: Automatic Tuning of Federated Learning Hyper-Parameters from System Perspective

1 code implementation6 Oct 2021 Huanle Zhang, Mi Zhang, Xin Liu, Prasant Mohapatra, Michael DeLucia

Federated learning (FL) hyper-parameters significantly affect the training overheads in terms of computation time, transmission time, computation load, and transmission load.

Federated Learning

Automatic Tuning of Federated Learning Hyper-Parameters from System Perspective

no code implementations29 Sep 2021 Huanle Zhang, Mi Zhang, Xin Liu, Prasant Mohapatra, Michael DeLucia

Federated Learning (FL) is a distributed model training paradigm that preserves clients' data privacy.

Federated Learning

Multi-Scale Feature and Metric Learning for Relation Extraction

no code implementations28 Jul 2021 Mi Zhang, Tieyun Qian

Specifically, we first develop a multi-scale convolutional neural network to aggregate the non-successive mainstays in the lexical sequence.

Metric Learning Relation Extraction

Exploring the Security Boundary of Data Reconstruction via Neuron Exclusivity Analysis

no code implementations26 Oct 2020 Xudong Pan, Mi Zhang, Yifan Yan, Jiaming Zhu, Min Yang

Among existing privacy attacks on the gradient of neural networks, \emph{data reconstruction attack}, which reverse engineers the training batch from the gradient, poses a severe threat on the private training data.

Face Recognition

Does Unsupervised Architecture Representation Learning Help Neural Architecture Search?

1 code implementation NeurIPS 2020 Shen Yan, Yu Zheng, Wei Ao, Xiao Zeng, Mi Zhang

Existing Neural Architecture Search (NAS) methods either encode neural architectures using discrete encodings that do not scale well, or adopt supervised learning-based methods to jointly learn architecture representations and optimize architecture search on such representations which incurs search bias.

Neural Architecture Search

Dance Revolution: Long-Term Dance Generation with Music via Curriculum Learning

1 code implementation ICLR 2021 Ruozi Huang, Huang Hu, Wei Wu, Kei Sawada, Mi Zhang, Daxin Jiang

In this paper, we formalize the music-conditioned dance generation as a sequence-to-sequence learning problem and devise a novel seq2seq architecture to efficiently process long sequences of music features and capture the fine-grained correspondence between music and dance.

motion synthesis

Transfer learning in large-scale ocean bottom seismic wavefield reconstruction

1 code implementation15 Apr 2020 Mi Zhang, Ali Siahkoohi, Felix J. Herrmann

Because different frequency slices share information, we propose the use the method of transfer training to make our approach computationally more efficient by warm starting the training with CNN weights obtained from a neighboring frequency slices.

Transfer Learning

MutualNet: Adaptive ConvNet via Mutual Learning from Network Width and Resolution

2 code implementations ECCV 2020 Taojiannan Yang, Sijie Zhu, Chen Chen, Shen Yan, Mi Zhang, Andrew Willis

We propose the width-resolution mutual learning method (MutualNet) to train a network that is executable at dynamic resource constraints to achieve adaptive accuracy-efficiency trade-offs at runtime.

Instance Segmentation object-detection +3

HM-NAS: Efficient Neural Architecture Search via Hierarchical Masking

no code implementations31 Aug 2019 Shen Yan, Biyi Fang, Faen Zhang, Yu Zheng, Xiao Zeng, Hui Xu, Mi Zhang

Without the constraint imposed by the hand-designed heuristics, our searched networks contain more flexible and meaningful architectures that existing weight sharing based NAS approaches are not able to discover.

Neural Architecture Search

How Sequence-to-Sequence Models Perceive Language Styles?

no code implementations16 Aug 2019 Ruozi Huang, Mi Zhang, Xudong Pan, Beina Sheng

Style is ubiquitous in our daily language uses, while what is language style to learning machines?

Informativeness Style Transfer +1

NestDNN: Resource-Aware Multi-Tenant On-Device Deep Learning for Continuous Mobile Vision

no code implementations23 Oct 2018 Biyi Fang, Xiao Zeng, Mi Zhang

These systems usually run multiple applications concurrently and their available resources at runtime are dynamic due to events such as starting new applications, closing existing applications, and application priority changes.

Theoretical Analysis of Image-to-Image Translation with Adversarial Learning

no code implementations ICML 2018 Xudong Pan, Mi Zhang, Daizong Ding

Recently, a unified model for image-to-image translation tasks within adversarial learning framework has aroused widespread research interests in computer vision practitioners.

Image-to-Image Translation Translation

Line-Based Multi-Label Energy Optimization for Fisheye Image Rectification and Calibration

no code implementations CVPR 2015 Mi Zhang, Jian Yao, Menghan Xia, Kai Li, Yi Zhang, Yaping Liu

Fisheye image rectification and estimation of intrinsic parameters for real scenes have been addressed in the literature by using line information on the distorted images.

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