Search Results for author: Yang Cao

Found 42 papers, 17 papers with code

Background Activation Suppression for Weakly Supervised Object Localization

1 code implementation1 Dec 2021 Pingyu Wu, Wei Zhai, Yang Cao

Existing FPM-based methods use cross-entropy (CE) to evaluate the foreground prediction map and to guide the learning of generator.

Weakly-Supervised Object Localization

Do What Nature Did To Us: Evolving Plastic Recurrent Neural Networks For Task Generalization

1 code implementation8 Sep 2021 Fan Wang, Hao Tian, Haoyi Xiong, Hua Wu, Yang Cao, Yu Kang, Haifeng Wang

While artificial neural networks (ANNs) have been widely adopted in machine learning, researchers are increasingly obsessed by the gaps between ANNs and biological neural networks (BNNs).


Learning Visual Affordance Grounding from Demonstration Videos

no code implementations12 Aug 2021 Hongchen Luo, Wei Zhai, Jing Zhang, Yang Cao, DaCheng Tao

For the object branch, we introduce a semantic enhancement module (SEM) to make the network focus on different parts of the object according to the action classes and utilize a distillation loss to align the output features of the object branch with that of the video branch and transfer the knowledge in the video branch to the object branch.

Action Recognition

One-Shot Object Affordance Detection in the Wild

1 code implementation8 Aug 2021 Wei Zhai, Hongchen Luo, Jing Zhang, Yang Cao, DaCheng Tao

To empower robots with this ability in unseen scenarios, we first study the challenging one-shot affordance detection problem in this paper, i. e., given a support image that depicts the action purpose, all objects in a scene with the common affordance should be detected.

Action Recognition Affordance Detection +1

One-Shot Affordance Detection

1 code implementation28 Jun 2021 Hongchen Luo, Wei Zhai, Jing Zhang, Yang Cao, DaCheng Tao

To empower robots with this ability in unseen scenarios, we consider the challenging one-shot affordance detection problem in this paper, i. e., given a support image that depicts the action purpose, all objects in a scene with the common affordance should be detected.

Affordance Detection

Understanding the Interplay between Privacy and Robustness in Federated Learning

no code implementations13 Jun 2021 Yaowei Han, Yang Cao, Masatoshi Yoshikawa

Federated Learning (FL) is emerging as a promising paradigm of privacy-preserving machine learning, which trains an algorithm across multiple clients without exchanging their data samples.

Adversarial Robustness Federated Learning

FL-Market: Trading Private Models in Federated Learning

1 code implementation8 Jun 2021 Shuyuan Zheng, Yang Cao, Masatoshi Yoshikawa, Huizhong Li, Qiang Yan

In this work, we address the two problems simultaneously with FL-Market, which incentivizes data owners' participation by providing appropriate payments and privacy protection.

Federated Learning

FakeMix Augmentation Improves Transparent Object Detection

1 code implementation24 Mar 2021 Yang Cao, Zhengqiang Zhang, Enze Xie, Qibin Hou, Kai Zhao, Xiangui Luo, Jian Tuo

However, these methods usually encounter boundary-related imbalance problem, leading to limited generation capability.

Data Augmentation Object Detection +1

FedGNN: Federated Graph Neural Network for Privacy-Preserving Recommendation

no code implementations9 Feb 2021 Chuhan Wu, Fangzhao Wu, Yang Cao, Yongfeng Huang, Xing Xie

To incorporate high-order user-item interactions, we propose a user-item graph expansion method that can find neighboring users with co-interacted items and exchange their embeddings for expanding the local user-item graphs in a privacy-preserving way.

Transparent Contribution Evaluation for Secure Federated Learning on Blockchain

no code implementations26 Jan 2021 Shuaicheng Ma, Yang Cao, Li Xiong

In this work, we propose a blockchain-based federated learning framework and a protocol to transparently evaluate each participant's contribution.

Federated Learning

Quantifying the Privacy-Utility Trade-offs in COVID-19 Contact Tracing Apps

no code implementations24 Dec 2020 Patrick Ocheja, Yang Cao, Shiyao Ding, Masatoshi Yoshikawa

How to contain the spread of the COVID-19 virus is a major concern for most countries.

Computers and Society Cryptography and Security 68P27 H.3.4

PCT-TEE: Trajectory-based Private Contact Tracing System with Trusted Execution Environment

1 code implementation7 Dec 2020 Fumiyuki Kato, Yang Cao, Yoshikawa Masatoshi

To this end, we design a TEE-based system with flexible trajectory data encoding algorithms.

Cryptography and Security Computers and Society

FLAME: Differentially Private Federated Learning in the Shuffle Model

1 code implementation17 Sep 2020 Ruixuan Liu, Yang Cao, Hong Chen, Ruoyang Guo, Masatoshi Yoshikawa

In this work, by leveraging the \textit{privacy amplification} effect in the recently proposed shuffle model of differential privacy, we achieve the best of two worlds, i. e., accuracy in the curator model and strong privacy without relying on any trusted party.

Federated Learning

Finding Acceptable Parameter Regions of Stochastic Hill functions for Multisite Phosphorylation Mechanism

no code implementations14 Sep 2020 Minghan Chen, Mansooreh Ahmadian, Layne Watson, Yang Cao

To reduce model complexity, this work aims to simplify the multisite phosphorylation mechanism by a stochastic Hill function model.

Stochastic Optimization

Nighttime Dehazing with a Synthetic Benchmark

1 code implementation10 Aug 2020 Jing Zhang, Yang Cao, Zheng-Jun Zha, DaCheng Tao

To address this issue, we propose a novel synthetic method called 3R to simulate nighttime hazy images from daytime clear images, which first reconstructs the scene geometry, then simulates the light rays and object reflectance, and finally renders the haze effects.

P3GM: Private High-Dimensional Data Release via Privacy Preserving Phased Generative Model

1 code implementation22 Jun 2020 Shun Takagi, Tsubasa Takahashi, Yang Cao, Masatoshi Yoshikawa

The state-of-the-art approach for this problem is to build a generative model under differential privacy, which offers a rigorous privacy guarantee.

PGLP: Customizable and Rigorous Location Privacy through Policy Graph

3 code implementations4 May 2020 Yang Cao, Yonghui Xiao, Shun Takagi, Li Xiong, Masatoshi Yoshikawa, Yilin Shen, Jinfei Liu, Hongxia Jin, Xiaofeng Xu

Third, we design a private location trace release framework that pipelines the detection of location exposure, policy graph repair, and private trajectory release with customizable and rigorous location privacy.

Cryptography and Security Computers and Society

PANDA: Policy-aware Location Privacy for Epidemic Surveillance

3 code implementations1 May 2020 Yang Cao, Shun Takagi, Yonghui Xiao, Li Xiong, Masatoshi Yoshikawa

Our system has three primary functions for epidemic surveillance: location monitoring, epidemic analysis, and contact tracing.

Databases Cryptography and Security

Self-Supervised Tuning for Few-Shot Segmentation

no code implementations12 Apr 2020 Kai Zhu, Wei Zhai, Zheng-Jun Zha, Yang Cao

Few-shot segmentation aims at assigning a category label to each image pixel with few annotated samples.


FedSel: Federated SGD under Local Differential Privacy with Top-k Dimension Selection

no code implementations24 Mar 2020 Ruixuan Liu, Yang Cao, Masatoshi Yoshikawa, Hong Chen

To prevent privacy leakages from gradients that are calculated on users' sensitive data, local differential privacy (LDP) has been considered as a privacy guarantee in federated SGD recently.

Federated Learning

Sensor-Augmented Neural Adaptive Bitrate Video Streaming on UAVs

no code implementations23 Sep 2019 Xuedou Xiao, Wei Wang, Taobin Chen, Yang Cao, Tao Jiang, Qian Zhang

In this paper, we present SA-ABR, a new sensor-augmented system that generates ABR video streaming algorithms with the assistance of various kinds of inherent sensor data that are used to pilot UAVs.

EGNet:Edge Guidance Network for Salient Object Detection

no code implementations22 Aug 2019 Jia-Xing Zhao, Jiang-Jiang Liu, Den-Ping Fan, Yang Cao, Jufeng Yang, Ming-Ming Cheng

In the second step, we integrate the local edge information and global location information to obtain the salient edge features.

RGB Salient Object Detection Salient Object Detection

One-Shot Texture Retrieval with Global Context Metric

no code implementations16 May 2019 Kai Zhu, Wei Zhai, Zheng-Jun Zha, Yang Cao

In this paper, we tackle one-shot texture retrieval: given an example of a new reference texture, detect and segment all the pixels of the same texture category within an arbitrary image.

Reinforcement Learning for Optimal Load Distribution Sequencing in Resource-Sharing System

no code implementations5 Feb 2019 Fei Wu, Yang Cao, Thomas Robertazzi

Divisible Load Theory (DLT) is a powerful tool for modeling divisible load problems in data-intensive systems.

Deep Time-Frequency Representation and Progressive Decision Fusion for ECG Classification

no code implementations19 Jan 2019 Jing Zhang, Jing Tian, Yang Cao, Yuxiang Yang, Xiaobin Xu

Early recognition of abnormal rhythms in ECG signals is crucial for monitoring and diagnosing patients' cardiac conditions, increasing the success rate of the treatment.

ECG Classification General Classification

Enhanced-alignment Measure for Binary Foreground Map Evaluation

2 code implementations26 May 2018 Deng-Ping Fan, Cheng Gong, Yang Cao, Bo Ren, Ming-Ming Cheng, Ali Borji

The existing binary foreground map (FM) measures to address various types of errors in either pixel-wise or structural ways.

Nearly Optimal Adaptive Procedure with Change Detection for Piecewise-Stationary Bandit

no code implementations11 Feb 2018 Yang Cao, Zheng Wen, Branislav Kveton, Yao Xie

Multi-armed bandit (MAB) is a class of online learning problems where a learning agent aims to maximize its expected cumulative reward while repeatedly selecting to pull arms with unknown reward distributions.

Change Detection

Fully Point-wise Convolutional Neural Network for Modeling Statistical Regularities in Natural Images

no code implementations19 Jan 2018 Jing Zhang, Yang Cao, Yang Wang, Chenglin Wen, Chang Wen Chen

Specifically, we propose to randomly shuffle the pixels in the origin images and leverage the shuffled image as input to make CNN more concerned with the statistical properties.

Color Constancy Image Dehazing

Quantifying Differential Privacy in Continuous Data Release under Temporal Correlations

2 code implementations29 Nov 2017 Yang Cao, Masatoshi Yoshikawa, Yonghui Xiao, Li Xiong

Our analysis reveals that, the event-level privacy loss of a DP mechanism may \textit{increase over time}.


Fast Haze Removal for Nighttime Image Using Maximum Reflectance Prior

no code implementations CVPR 2017 Jing Zhang, Yang Cao, Shuai Fang, Yu Kang, Chang Wen Chen

Then, we propose a simple but effective image prior, maximum reflectance prior, to estimate the varying ambient illumination.

Nearly second-order asymptotic optimality of sequential change-point detection with one-sample updates

no code implementations19 May 2017 Yang Cao, Liyan Xie, Yao Xie, Huan Xu

Our proof is achieved by making a connection between sequential change-point and online convex optimization and leveraging the logarithmic regret bound property of online mirror descent algorithm.

Change Point Detection

Quantifying Differential Privacy under Temporal Correlations

2 code implementations24 Oct 2016 Yang Cao, Masatoshi Yoshikawa, Yonghui Xiao, Li Xiong

Our analysis reveals that the privacy leakage of a DP mechanism may accumulate and increase over time.

Databases Cryptography and Security

Nighttime Haze Removal with Illumination Correction

no code implementations5 Jun 2016 Jing Zhang, Yang Cao, Zengfu Wang

ii) Then it achieves a color-balance result by performing a color correction step after estimating the color characteristics of the incident light.

Multi-Sensor Slope Change Detection

no code implementations1 Sep 2015 Yang Cao, Yao Xie, Nagi Gebraeel

Observations are assumed to be initially normal random variables with known constant means and variances.

Change Detection

Categorical Matrix Completion

no code implementations2 Jul 2015 Yang Cao, Yao Xie

We recover a low-rank matrix $X$ by maximizing the likelihood ratio with a constraint on the nuclear norm of $X$, and the observations are mapped from entries of $X$ through multiple link functions.

Matrix Completion

Sketching for Sequential Change-Point Detection

no code implementations25 May 2015 Yang Cao, Andrew Thompson, Meng Wang, Yao Xie

We study sequential change-point detection procedures based on linear sketches of high-dimensional signal vectors using generalized likelihood ratio (GLR) statistics.

Change Point Detection

Poisson Matrix Recovery and Completion

no code implementations20 Apr 2015 Yang Cao, Yao Xie

We extend the theory of low-rank matrix recovery and completion to the case when Poisson observations for a linear combination or a subset of the entries of a matrix are available, which arises in various applications with count data.

Matrix Completion

Poisson Matrix Completion

no code implementations26 Jan 2015 Yang Cao, Yao Xie

We extend the theory of matrix completion to the case where we make Poisson observations for a subset of entries of a low-rank matrix.

Matrix Completion

Fast Algorithm for Low-rank matrix recovery in Poisson noise

no code implementations2 Jul 2014 Yang Cao, Yao Xie

This paper describes a fast algorithm for recovering low-rank matrices from their linear measurements contaminated with Poisson noise: the Poisson noise Maximum Likelihood Singular Value thresholding (PMLSV) algorithm.

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