Search Results for author: Yi Ding

Found 25 papers, 12 papers with code

SCOPE: Safe Exploration for Dynamic Computer Systems Optimization

no code implementations22 Apr 2022 Hyunji Kim, Ahsan Pervaiz, Henry Hoffmann, Michael Carbin, Yi Ding

Such solutions monitor past system executions to learn the system's behavior under different hardware resource allocations before dynamically tuning resources to optimize the application execution.

Safe Exploration

Cello: Efficient Computer Systems Optimization with Predictive Early Termination and Censored Regression

no code implementations11 Apr 2022 Yi Ding, Alex Renda, Ahsan Pervaiz, Michael Carbin, Henry Hoffmann

Our evaluation shows that compared to the state-of-the-art SEML approach in computer systems optimization, Cello improves latency by 1. 19X for minimizing latency under a power constraint, and improves energy by 1. 18X for minimizing energy under a latency constraint.

Continuous Emotion Recognition using Visual-audio-linguistic information: A Technical Report for ABAW3

1 code implementation24 Mar 2022 Su Zhang, Ruyi An, Yi Ding, Cuntai Guan

The visual encoding from the visual block is concatenated with the attention feature to emphasize the visual information.

Emotion Recognition

NURD: Negative-Unlabeled Learning for Online Datacenter Straggler Prediction

1 code implementation16 Mar 2022 Yi Ding, Avinash Rao, Hyebin Song, Rebecca Willett, Henry Hoffmann

To predict stragglers accurately and early without labeled positive examples or assumptions on latency distributions, this paper presents NURD, a novel Negative-Unlabeled learning approach with Reweighting and Distribution-compensation that only trains on negative and unlabeled streaming data.

Statistical Learning for Individualized Asset Allocation

no code implementations20 Jan 2022 Yi Ding, YingYing Li, Rui Song

We show that our proposed Discretization and Regression with generalized fOlded concaVe penalty on Effect discontinuity (DROVE) approach enjoys desirable theoretical properties and allows for statistical inference of the optimal value associated with optimal decision-making.

Decision Making

Programming with Neural Surrogates of Programs

1 code implementation12 Dec 2021 Alex Renda, Yi Ding, Michael Carbin

With surrogate adaptation, programmers develop a surrogate of a program then retrain that surrogate on a different task.

Sparse Fusion for Multimodal Transformers

no code implementations23 Nov 2021 Yi Ding, Alex Rich, Mason Wang, Noah Stier, Matthew Turk, Pradeep Sen, Tobias Höllerer

Multimodal classification is a core task in human-centric machine learning.

Continuous Emotion Recognition with Audio-visual Leader-follower Attentive Fusion

1 code implementation2 Jul 2021 Su Zhang, Yi Ding, Ziquan Wei, Cuntai Guan

We propose an audio-visual spatial-temporal deep neural network with: (1) a visual block containing a pretrained 2D-CNN followed by a temporal convolutional network (TCN); (2) an aural block containing several parallel TCNs; and (3) a leader-follower attentive fusion block combining the audio-visual information.

Emotion Recognition

LGGNet: Learning from Local-Global-Graph Representations for Brain-Computer Interface

1 code implementation5 May 2021 Yi Ding, Neethu Robinson, Qiuhao Zeng, Cuntai Guan

It captures temporal dynamics of EEG which then serves as input to the proposed local and global graph-filtering layers.

EEG EEG Emotion Recognition

TSception: Capturing Temporal Dynamics and Spatial Asymmetry from EEG for Emotion Recognition

2 code implementations7 Apr 2021 Yi Ding, Neethu Robinson, Su Zhang, Qiuhao Zeng, Cuntai Guan

TSception consists of dynamic temporal, asymmetric spatial, and high-level fusion layers, which learn discriminative representations in the time and channel dimensions simultaneously.

Emotion Recognition

Augmentation Strategies for Learning with Noisy Labels

1 code implementation CVPR 2021 Kento Nishi, Yi Ding, Alex Rich, Tobias Höllerer

In this paper, we evaluate different augmentation strategies for algorithms tackling the "learning with noisy labels" problem.

Ranked #4 on Image Classification on Clothing1M (using extra training data)

Learning with noisy labels pseudo label

Multiple Instance Segmentation in Brachial Plexus Ultrasound Image Using BPMSegNet

no code implementations22 Dec 2020 Yi Ding, Qiqi Yang, Guozheng Wu, Jian Zhang, Zhiguang Qin

In this paper, a network called Brachial Plexus Multi-instance Segmentation Network (BPMSegNet) is proposed to identify different tissues (nerves, arteries, veins, muscles) in ultrasound images.

Instance Segmentation Semantic Segmentation

DeepKeyGen: A Deep Learning-based Stream Cipher Generator for Medical Image Encryption and Decryption

no code implementations21 Dec 2020 Yi Ding, Fuyuan Tan, Zhen Qin, Mingsheng Cao, Kim-Kwang Raymond Choo, Zhiguang Qin

In this paper, a novel deep learning-based key generation network (DeepKeyGen) is proposed as a stream cipher generator to generate the private key, which can then be used for encrypting and decrypting of medical images.

A Multi-View Dynamic Fusion Framework: How to Improve the Multimodal Brain Tumor Segmentation from Multi-Views?

no code implementations21 Dec 2020 Yi Ding, Wei Zheng, Guozheng Wu, Ji Geng, Mingsheng Cao, Zhiguang Qin

Moreover, the multi-view fusion loss, which consists of the segmentation loss, the transition loss and the decision loss, is proposed to facilitate the training process of multi-view learning networks so as to keep the consistency of appearance and space, not only in the process of fusing segmentation results, but also in the process of training the learning network.

Brain Tumor Segmentation MULTI-VIEW LEARNING +1

Channel Pruning Guided by Spatial and Channel Attention for DNNs in Intelligent Edge Computing

no code implementations8 Nov 2020 Mengran Liu, Weiwei Fang, Xiaodong Ma, Wenyuan Xu, Naixue Xiong, Yi Ding

Guided by the scale values generated by SCA for measuring channel importance, we further propose a new channel pruning approach called Channel Pruning guided by Spatial and Channel Attention (CPSCA).



1 code implementation11 Aug 2020 Gang Chen, Yi Ding, Hugo Edwards, Chong Hin Chau, Sai Hou, Grace Johnson, Mohammed Sharukh Syed, Haoyuan Tang, Yue Wu, Ye Yan, Gil Tidhar, Nir Lipovetzky

Planimation is a modular and extensible open source framework to visualise sequential solutions of planning problems specified in PDDL.

A polynomial-time algorithm for learning nonparametric causal graphs

1 code implementation NeurIPS 2020 Ming Gao, Yi Ding, Bryon Aragam

We establish finite-sample guarantees for a polynomial-time algorithm for learning a nonlinear, nonparametric directed acyclic graphical (DAG) model from data.

DeepEDN: A Deep Learning-based Image Encryption and Decryption Network for Internet of Medical Things

no code implementations12 Apr 2020 Yi Ding, Guozheng Wu, Dajiang Chen, Ning Zhang, Linpeng Gong, Mingsheng Cao, Zhiguang Qin

Specifically, in DeepEDN, the Cycle-Generative Adversarial Network (Cycle-GAN) is employed as the main learning network to transfer the medical image from its original domain into the target domain.

TSception: A Deep Learning Framework for Emotion Detection Using EEG

1 code implementation2 Apr 2020 Yi Ding, Neethu Robinson, Qiuhao Zeng, Duo Chen, Aung Aung Phyo Wai, Tih-Shih Lee, Cuntai Guan

TSception consists of temporal and spatial convolutional layers, which learn discriminative representations in the time and channel domains simultaneously.

EEG General Classification

Dynamical systems theory for causal inference with application to synthetic control methods

1 code implementation27 Aug 2018 Yi Ding, Panos Toulis

In this setting, we propose to screen out control units that have a weak dynamical relationship to the single treated unit before the model is fit.


RUN:Residual U-Net for Computer-Aided Detection of Pulmonary Nodules without Candidate Selection

no code implementations30 May 2018 Tian Lan, Yuanyuan Li, Jonah Kimani Murugi, Yi Ding, Zhiguang Qin

The early detection and early diagnosis of lung cancer are crucial to improve the survival rate of lung cancer patients.

Multiresolution Kernel Approximation for Gaussian Process Regression

1 code implementation NeurIPS 2017 Yi Ding, Risi Kondor, Jonathan Eskreis-Winkler

Gaussian process regression generally does not scale to beyond a few thousands data points without applying some sort of kernel approximation method.

Adaptive Subgradient Methods for Online AUC Maximization

no code implementations1 Feb 2016 Yi Ding, Peilin Zhao, Steven C. H. Hoi, Yew-Soon Ong

Despite their encouraging results reported, the existing online AUC maximization algorithms often adopt simple online gradient descent approaches that fail to exploit the geometrical knowledge of the data observed during the online learning process, and thus could suffer from relatively larger regret.

online learning

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