b'Yi Sun'

Preserve, Promote, or Attack? GNN Explanation via Topology Perturbation

Prior works on formalizing explanations of a graph neural network (GNN) ...
03/25/2021 ∙ by Yi Sun, et al. ∙ 10 ∙ share

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Data augmentation as stochastic optimization

We present a theoretical framework recasting data augmentation as stocha...
10/21/2020 ∙ by Boris Hanin, et al. ∙ 0 ∙ share

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Multi-Agent Deep Reinforcement Learning for HVAC Control in Commercial Buildings

In commercial buildings, about 40 is attributed to Heating, Ventilation,...
06/25/2020 ∙ by Liang Yu, et al. ∙ 0 ∙ share

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Likelihood landscape and maximum likelihood estimation for the discrete orbit recovery model

We study the non-convex optimization landscape for maximum likelihood es...
03/31/2020 ∙ by Zhou Fan, et al. ∙ 0 ∙ share

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Multi-objective Ranking via Constrained Optimization

In this paper, we introduce an Augmented Lagrangian based method to inco...
02/13/2020 ∙ by Michinari Momma, et al. ∙ 0 ∙ share

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Line as object: datasets and framework for semantic line segment detection

In this work, we propose a learning-based approach to the task of detect...
09/14/2019 ∙ by Yi Sun, et al. ∙ 10 ∙ share

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Testing Robustness Against Unforeseen Adversaries

Considerable work on adversarial defense has studied robustness to a fix...
08/21/2019 ∙ by Daniel Kang, et al. ∙ 1 ∙ share

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Learning Fair Classifiers in Online Stochastic Settings

In many real life situations, including job and loan applications, gatek...
08/19/2019 ∙ by Yi Sun, et al. ∙ 0 ∙ share

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Txilm: Lossy Block Compression with Salted Short Hashing

Current blockchains are restricted by the low throughput. Aimed at this ...
06/15/2019 ∙ by Donghui Ding, et al. ∙ 0 ∙ share

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Transfer of Adversarial Robustness Between Perturbation Types

We study the transfer of adversarial robustness of deep neural networks ...
05/03/2019 ∙ by Daniel Kang, et al. ∙ 12 ∙ share

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Principal components in linear mixed models with general bulk

We study the outlier eigenvalues and eigenvectors in variance components...
03/22/2019 ∙ by Zhou Fan, et al. ∙ 0 ∙ share

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An Active-Passive Measurement Study of TCP Performance over LTE on High-speed Rails

High-speed rail (HSR) systems potentially provide a more efficient way o...
12/12/2018 ∙ by Jing Wang, et al. ∙ 0 ∙ share

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Learning Vine Copula Models For Synthetic Data Generation

A vine copula model is a flexible high-dimensional dependence model whic...
12/04/2018 ∙ by Yi Sun, et al. ∙ 6 ∙ share

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Limited Gradient Descent: Learning With Noisy Labels

Label noise may handicap the generalization of classifiers, and it is an...
11/20/2018 ∙ by Yi Sun, et al. ∙ 14 ∙ share

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Spiked covariances and principal components analysis in high-dimensional random effects models

We study principal components analyses in multivariate random and mixed ...
06/25/2018 ∙ by Zhou Fan, et al. ∙ 0 ∙ share

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Development of a computer-aided design software for dental splint in orthognathic surgery

In the orthognathic surgery, dental splints are important and necessary ...
03/09/2017 ∙ by Xiaojun Chen, et al. ∙ 0 ∙ share

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Sparsifying Neural Network Connections for Face Recognition

This paper proposes to learn high-performance deep ConvNets with sparse ...
12/07/2015 ∙ by Yi Sun, et al. ∙ 0 ∙ share

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From random walks to distances on unweighted graphs

Large unweighted directed graphs are commonly used to capture relations ...
11/02/2015 ∙ by Tatsunori B. Hashimoto, et al. ∙ 0 ∙ share

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DeepID3: Face Recognition with Very Deep Neural Networks

The state-of-the-art of face recognition has been significantly advanced...
02/03/2015 ∙ by Yi Sun, et al. ∙ 0 ∙ share

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Deeply learned face representations are sparse, selective, and robust

This paper designs a high-performance deep convolutional network (DeepID...
12/03/2014 ∙ by Yi Sun, et al. ∙ 0 ∙ share

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Metric recovery from directed unweighted graphs

We analyze directed, unweighted graphs obtained from x_i∈R^d by connecti...
11/20/2014 ∙ by Tatsunori B. Hashimoto, et al. ∙ 0 ∙ share

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Deep Learning Face Representation by Joint Identification-Verification

The key challenge of face recognition is to develop effective feature re...
06/18/2014 ∙ by Yi Sun, et al. ∙ 0 ∙ share

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Efficient Natural Evolution Strategies

Efficient Natural Evolution Strategies (eNES) is a novel alternative to ...
09/26/2012 ∙ by Yi Sun, et al. ∙ 0 ∙ share

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On the Size of the Online Kernel Sparsification Dictionary

We analyze the size of the dictionary constructed from online kernel spa...
06/18/2012 ∙ by Yi Sun, et al. ∙ 0 ∙ share

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Natural Evolution Strategies

This paper presents Natural Evolution Strategies (NES), a recent family ...
06/22/2011 ∙ by Daan Wierstra, et al. ∙ 0 ∙ share

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A Linear Time Natural Evolution Strategy for Non-Separable Functions

We present a novel Natural Evolution Strategy (NES) variant, the Rank-On...
06/10/2011 ∙ by Yi Sun, et al. ∙ 0 ∙ share

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Planning to Be Surprised: Optimal Bayesian Exploration in Dynamic Environments

To maximize its success, an AGI typically needs to explore its initially...
03/29/2011 ∙ by Yi Sun, et al. ∙ 0 ∙ share

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Yi Sun

Featured Co-authors

Hao Wang

Xiaogang Wang

Tao Jiang

Sijia Liu

Xiaoou Tang

Jing Wang

Jürgen Schmidhuber

Yihong Wu

Jan Egger

Juergen Schmidhuber

Kai Sun

Preserve, Promote, or Attack? GNN Explanation via Topology Perturbation

Data augmentation as stochastic optimization

Multi-Agent Deep Reinforcement Learning for HVAC Control in Commercial Buildings

Likelihood landscape and maximum likelihood estimation for the discrete orbit recovery model

Multi-objective Ranking via Constrained Optimization

Line as object: datasets and framework for semantic line segment detection

Testing Robustness Against Unforeseen Adversaries

Learning Fair Classifiers in Online Stochastic Settings

Txilm: Lossy Block Compression with Salted Short Hashing

Transfer of Adversarial Robustness Between Perturbation Types

Principal components in linear mixed models with general bulk

An Active-Passive Measurement Study of TCP Performance over LTE on High-speed Rails

Learning Vine Copula Models For Synthetic Data Generation

Limited Gradient Descent: Learning With Noisy Labels

Spiked covariances and principal components analysis in high-dimensional random effects models

Development of a computer-aided design software for dental splint in orthognathic surgery

Sparsifying Neural Network Connections for Face Recognition

From random walks to distances on unweighted graphs

DeepID3: Face Recognition with Very Deep Neural Networks

Deeply learned face representations are sparse, selective, and robust

Metric recovery from directed unweighted graphs

Deep Learning Face Representation by Joint Identification-Verification

Efficient Natural Evolution Strategies

On the Size of the Online Kernel Sparsification Dictionary

Natural Evolution Strategies

A Linear Time Natural Evolution Strategy for Non-Separable Functions

Planning to Be Surprised: Optimal Bayesian Exploration in Dynamic Environments