b'Bo Zhao'

research

∙ 06/17/2022

LIMO: Latent Inceptionism for Targeted Molecule Generation

Generation of drug-like molecules with high binding affinity to target p...

19 Peter Eckmann, et al. ∙

research

∙ 06/01/2022

Privacy for Free: How does Dataset Condensation Help Privacy?

To prevent unintentional data leakage, research community has resorted t...

9 Tian Dong, et al. ∙

research

∙ 05/23/2022

FaceMAE: Privacy-Preserving Face Recognition via Masked Autoencoders

Face recognition, as one of the most successful applications in artifici...

16 Kai Wang, et al. ∙

research

∙ 05/21/2022

Symmetry Teleportation for Accelerated Optimization

Existing gradient-based optimization methods update the parameters local...

11 Bo Zhao, et al. ∙

research

∙ 04/18/2022

DeepCore: A Comprehensive Library for Coreset Selection in Deep Learning

Coreset selection, which aims to select a subset of the most informative...

21 Chengcheng Guo, et al. ∙

research

∙ 04/15/2022

Synthesizing Informative Training Samples with GAN

Remarkable progress has been achieved in synthesizing photo-realistic im...

7 Bo Zhao, et al. ∙

research

∙ 03/03/2022

CAFE: Learning to Condense Dataset by Aligning Features

Dataset condensation aims at reducing the network training effort throug...

23 Kai Wang, et al. ∙

research

∙ 01/04/2022

Towards Understanding and Harnessing the Effect of Image Transformation in Adversarial Detection

Deep neural networks (DNNs) are threatened by adversarial examples. Adve...

8 Hui Liu, et al. ∙

research

∙ 12/13/2021

Makeup216: Logo Recognition with Adversarial Attention Representations

One of the challenges of logo recognition lies in the diversity of forms...

10 Junjun Hu, et al. ∙

research

∙ 12/09/2021

One-dimensional Deep Low-rank and Sparse Network for Accelerated MRI

Deep learning has shown astonishing performance in accelerated magnetic ...

13 Zi Wang, et al. ∙

research

∙ 10/08/2021

Dataset Condensation with Distribution Matching

Computational cost to train state-of-the-art deep models in many learnin...

4 Bo Zhao, et al. ∙

research

∙ 07/19/2021

Feature-Filter: Detecting Adversarial Examples through Filtering off Recessive Features

Deep neural networks (DNNs) are under threat from adversarial example at...

14 Hui Liu, et al. ∙

research

∙ 04/16/2021

FedCom: A Byzantine-Robust Local Model Aggregation Rule Using Data Commitment for Federated Learning

Federated learning (FL) is a promising privacy-preserving distributed ma...

10 Bo Zhao, et al. ∙

research

∙ 04/08/2021

One-bit Spectrum Sensing with the Eigenvalue Moment Ratio Approach

One-bit analog-to-digital converter (ADC), performing signal sampling as...

0 Yuan Zhao, et al. ∙

research

∙ 03/18/2021

Concentric Spherical GNN for 3D Representation Learning

Learning 3D representations that generalize well to arbitrarily oriented...

5 James Fox, et al. ∙

research

∙ 03/08/2021

Interpretable Attention Guided Network for Fine-grained Visual Classification

Fine-grained visual classification (FGVC) is challenging but more critic...

5 Zhenhuan Huang, et al. ∙

research

∙ 02/16/2021

Dataset Condensation with Differentiable Siamese Augmentation

In many machine learning problems, large-scale datasets have become the ...

5 Bo Zhao, et al. ∙

research

∙ 12/31/2020

Multiple Plans are Better than One: Diverse Stochastic Planning

In planning problems, it is often challenging to fully model the desired...

23 Mahsa Ghasemi, et al. ∙

research

∙ 12/23/2020

Active Sampling for Accelerated MRI with Low-Rank Tensors

Magnetic resonance imaging (MRI) is a powerful imaging modality that rev...

7 Zichang He, et al. ∙

research

∙ 10/14/2020

GreedyFool: An Imperceptible Black-box Adversarial Example Attack against Neural Networks

Deep neural networks (DNNs) are inherently vulnerable to well-designed i...

11 Hui Liu, et al. ∙

research

∙ 08/27/2020

Attribute-guided image generation from layout

Recent approaches have achieved great success in image generation from s...

0 Ke Ma, et al. ∙

research

∙ 07/15/2020

Augmented Bi-path Network for Few-shot Learning

Few-shot Learning (FSL) which aims to learn from few labeled training da...

0 Baoming Yan, et al. ∙

research

∙ 07/07/2020

PinnerSage: Multi-Modal User Embedding Framework for Recommendations at Pinterest

Latent user representations are widely adopted in the tech industry for ...

7 Aditya Pal, et al. ∙

research

∙ 06/15/2020

Privacy-Preserving Technology to Help Millions of People: Federated Prediction Model for Stroke Prevention

prevention of stroke with its associated risk factors has been one of th...

0 Ce Ju, et al. ∙

research

∙ 06/10/2020

Dataset Condensation with Gradient Matching

Efficient training of deep neural networks is an increasingly important ...

0 Bo Zhao, et al. ∙

research

∙ 06/08/2020

Continual Representation Learning for Biometric Identification

With the explosion of digital data in recent years, continuously learnin...

0 Bo Zhao, et al. ∙

research

∙ 01/08/2020

iDLG: Improved Deep Leakage from Gradients

It is widely believed that sharing gradients will not leak private train...

0 Bo Zhao, et al. ∙

research

∙ 10/24/2019

LabPipe: an extensible informatics platform to streamline management of metabolomics data and metadata

Summary: Data management in clinical metabolomics studies is often inade...

0 Bo Zhao, et al. ∙

research

∙ 10/21/2019

DwNet: Dense warp-based network for pose-guided human video generation

Generation of realistic high-resolution videos of human subjects is a ch...

14 Polina Zablotskaia, et al. ∙

research

∙ 11/28/2018

Image Generation from Layout

Despite significant recent progress on generative models, controlled gen...

0 Bo Zhao, et al. ∙

research

∙ 10/01/2018

Where and When to Look? Spatio-temporal Attention for Action Recognition in Videos

Inspired by the observation that humans are able to process videos effic...

0 Lili Meng, et al. ∙

research

∙ 06/12/2018

MSplit LBI: Realizing Feature Selection and Dense Estimation Simultaneously in Few-shot and Zero-shot Learning

It is one typical and general topic of learning a good embedding model t...

0 Bo Zhao, et al. ∙

research

∙ 04/12/2018

A Large-scale Attribute Dataset for Zero-shot Learning

Zero-Shot Learning (ZSL) has attracted huge research attention over the ...

0 Bo Zhao, et al. ∙

research

∙ 04/10/2018

Modular Generative Adversarial Networks

Existing methods for multi-domain image-to-image translation (or generat...

0 Bo Zhao, et al. ∙

research

∙ 04/03/2018

Left-Right Comparative Recurrent Model for Stereo Matching

Leveraging the disparity information from both left and right views is c...

0 Zequn Jie, et al. ∙

research

∙ 11/20/2017

Zero-shot Learning via Shared-Reconstruction-Graph Pursuit

Zero-shot learning (ZSL) aims to recognize objects from novel unseen cla...

0 Bo Zhao, et al. ∙

research

∙ 11/17/2017

AI Challenger : A Large-scale Dataset for Going Deeper in Image Understanding

Significant progress has been achieved in Computer Vision by leveraging ...

0 Jiahong Wu, et al. ∙

research

∙ 07/21/2017

Neural Person Search Machines

We investigate the problem of person search in the wild in this work. In...

0 Hao Liu, et al. ∙

research

∙ 04/17/2017

Multi-View Image Generation from a Single-View

This paper addresses a challenging problem -- how to generate multi-view...

1 Bo Zhao, et al. ∙

research

∙ 12/02/2016

Zero-Shot Learning posed as a Missing Data Problem

This paper presents a method of zero-shot learning (ZSL) which poses ZSL...

0 Bo Zhao, et al. ∙

research

∙ 06/28/2016

Diversified Visual Attention Networks for Fine-Grained Object Classification

Fine-grained object classification is a challenging task due to the subt...

0 Bo Zhao, et al. ∙

research

∙ 09/22/2014

Fast Low-rank Representation based Spatial Pyramid Matching for Image Classification

Spatial Pyramid Matching (SPM) and its variants have achieved a lot of s...

0 Xi Peng, et al. ∙

Bo Zhao

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