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06/17/2022
LIMO: Latent Inceptionism for Targeted Molecule Generation
Generation of drug-like molecules with high binding affinity to target p...
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06/01/2022
Privacy for Free: How does Dataset Condensation Help Privacy?
To prevent unintentional data leakage, research community has resorted t...
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05/23/2022
FaceMAE: Privacy-Preserving Face Recognition via Masked Autoencoders
Face recognition, as one of the most successful applications in artifici...
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05/21/2022
Symmetry Teleportation for Accelerated Optimization
Existing gradient-based optimization methods update the parameters local...
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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...
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04/15/2022
Synthesizing Informative Training Samples with GAN
Remarkable progress has been achieved in synthesizing photo-realistic im...
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03/03/2022
CAFE: Learning to Condense Dataset by Aligning Features
Dataset condensation aims at reducing the network training effort throug...
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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...
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12/13/2021
Makeup216: Logo Recognition with Adversarial Attention Representations
One of the challenges of logo recognition lies in the diversity of forms...
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12/09/2021
One-dimensional Deep Low-rank and Sparse Network for Accelerated MRI
Deep learning has shown astonishing performance in accelerated magnetic ...
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10/08/2021
Dataset Condensation with Distribution Matching
Computational cost to train state-of-the-art deep models in many learnin...
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07/19/2021
Feature-Filter: Detecting Adversarial Examples through Filtering off Recessive Features
Deep neural networks (DNNs) are under threat from adversarial example at...
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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...
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04/08/2021
One-bit Spectrum Sensing with the Eigenvalue Moment Ratio Approach
One-bit analog-to-digital converter (ADC), performing signal sampling as...
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03/18/2021
Concentric Spherical GNN for 3D Representation Learning
Learning 3D representations that generalize well to arbitrarily oriented...
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03/08/2021
Interpretable Attention Guided Network for Fine-grained Visual Classification
Fine-grained visual classification (FGVC) is challenging but more critic...
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02/16/2021
Dataset Condensation with Differentiable Siamese Augmentation
In many machine learning problems, large-scale datasets have become the ...
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12/31/2020
Multiple Plans are Better than One: Diverse Stochastic Planning
In planning problems, it is often challenging to fully model the desired...
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12/23/2020
Active Sampling for Accelerated MRI with Low-Rank Tensors
Magnetic resonance imaging (MRI) is a powerful imaging modality that rev...
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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...
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08/27/2020
Attribute-guided image generation from layout
Recent approaches have achieved great success in image generation from s...
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07/15/2020
Augmented Bi-path Network for Few-shot Learning
Few-shot Learning (FSL) which aims to learn from few labeled training da...
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07/07/2020
PinnerSage: Multi-Modal User Embedding Framework for Recommendations at Pinterest
Latent user representations are widely adopted in the tech industry for ...
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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...
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06/10/2020
Dataset Condensation with Gradient Matching
Efficient training of deep neural networks is an increasingly important ...
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06/08/2020
Continual Representation Learning for Biometric Identification
With the explosion of digital data in recent years, continuously learnin...
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01/08/2020
iDLG: Improved Deep Leakage from Gradients
It is widely believed that sharing gradients will not leak private train...
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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...
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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...
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11/28/2018
Image Generation from Layout
Despite significant recent progress on generative models, controlled gen...
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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...
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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...
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04/12/2018
A Large-scale Attribute Dataset for Zero-shot Learning
Zero-Shot Learning (ZSL) has attracted huge research attention over the ...
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04/10/2018
Modular Generative Adversarial Networks
Existing methods for multi-domain image-to-image translation (or generat...
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04/03/2018
Left-Right Comparative Recurrent Model for Stereo Matching
Leveraging the disparity information from both left and right views is c...
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11/20/2017
Zero-shot Learning via Shared-Reconstruction-Graph Pursuit
Zero-shot learning (ZSL) aims to recognize objects from novel unseen cla...
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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 ...
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07/21/2017
Neural Person Search Machines
We investigate the problem of person search in the wild in this work. In...
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04/17/2017
Multi-View Image Generation from a Single-View
This paper addresses a challenging problem -- how to generate multi-view...
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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...
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06/28/2016
Diversified Visual Attention Networks for Fine-Grained Object Classification
Fine-grained object classification is a challenging task due to the subt...
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09/22/2014
