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09/04/2023
Safe and Robust Watermark Injection with a Single OoD Image
Training a high-performance deep neural network requires large amounts o...
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06/04/2023
Revisiting Data-Free Knowledge Distillation with Poisoned Teachers
Data-free knowledge distillation (KD) helps transfer knowledge from a pr...
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05/24/2023
WeiAvg: Federated Learning Model Aggregation Promoting Data Diversity
Federated learning provides a promising privacy-preserving way for utili...
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05/10/2023
Patchwork Learning: A Paradigm Towards Integrative Analysis across Diverse Biomedical Data Sources
Machine learning (ML) in healthcare presents numerous opportunities for ...
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03/18/2023
Discovering Predictable Latent Factors for Time Series Forecasting
Modern time series forecasting methods, such as Transformer and its vari...
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03/15/2023
FactReranker: Fact-guided Reranker for Faithful Radiology Report Summarization
Automatic radiology report summarization is a crucial clinical task, who...
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10/23/2022
Outsourcing Training without Uploading Data via Efficient Collaborative Open-Source Sampling
As deep learning blooms with growing demand for computation and data res...
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10/12/2022
Trap and Replace: Defending Backdoor Attacks by Trapping Them into an Easy-to-Replace Subnetwork
Deep neural networks (DNNs) are vulnerable to backdoor attacks. Previous...
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07/11/2022
RUSH: Robust Contrastive Learning via Randomized Smoothing
Recently, adversarial training has been incorporated in self-supervised ...
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07/04/2022
How Robust is Your Fairness? Evaluating and Sustaining Fairness under Unseen Distribution Shifts
Increasing concerns have been raised on deep learning fairness in recent...
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03/18/2022
Efficient Split-Mix Federated Learning for On-Demand and In-Situ Customization
Federated learning (FL) provides a distributed learning framework for mu...
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10/25/2021
Persona Authentication through Generative Dialogue
In this paper we define and investigate the problem of persona authentic...
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06/18/2021
Federated Robustness Propagation: Sharing Adversarial Robustness in Federated Learning
Federated learning (FL) emerges as a popular distributed learning schema...
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05/20/2021
Data-Free Knowledge Distillation for Heterogeneous Federated Learning
Federated Learning (FL) is a decentralized machine-learning paradigm, in...
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05/10/2021
MTNet: A Multi-Task Neural Network for On-Field Calibration of Low-Cost Air Monitoring Sensors
The advances of sensor technology enable people to monitor air quality t...
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04/07/2021
FedFace: Collaborative Learning of Face Recognition Model
DNN-based face recognition models require large centrally aggregated fac...
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02/25/2021
Off-Policy Imitation Learning from Observations
Learning from Observations (LfO) is a practical reinforcement learning s...
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02/12/2021
Learning Deep Neural Networks under Agnostic Corrupted Supervision
Training deep neural models in the presence of corrupted supervision is ...
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01/19/2021
On Dynamic Noise Influence in Differentially Private Learning
Protecting privacy in learning while maintaining the model performance h...
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09/16/2020
Transfer Learning in Deep Reinforcement Learning: A Survey
This paper surveys the field of transfer learning in the problem setting...
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07/11/2020
Federated Learning's Blessing: FedAvg has Linear Speedup
Federated learning (FL) learns a model jointly from a set of participati...
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05/15/2020
Alternate Distributed Beamforming for Buffer-Aided Multi-Antenna Relay Systems
In this paper, link selection is investigated in half-duplex (HD) dual-h...
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05/15/2020
Mimicking Full-Duplex Secure Communications for Buffer-Aided Multi-Relay Systems
This paper considers secure communication in buffer-aided cooperative wi...
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04/01/2020
Learning Sparse Rewarded Tasks from Sub-Optimal Demonstrations
Model-free deep reinforcement learning (RL) has demonstrated its superio...
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10/09/2019
Alternate Distributed Beamforming for Decode-and-Forward Multi-Relay Systems Using Buffers
In this paper, link selection for half-duplex buffer-aided relay systems...
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06/24/2019
Ranking Policy Gradient
Sample inefficiency is a long-lasting problem in reinforcement learning ...
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05/08/2019
MetaPred: Meta-Learning for Clinical Risk Prediction with Limited Patient Electronic Health Records
In recent years, increasingly augmentation of health data, such as patie...
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05/01/2019
Inferring the Importance of Product Appearance: A Step Towards the Screenless Revolution
Nowadays, almost all the online orders were placed through screened devi...
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04/22/2019
Feature-based factorized Bilinear Similarity Model for Cold-Start Top-n Item Recommendation
Recommending new items to existing users has remained a challenging prob...
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11/03/2018
Boosted Sparse and Low-Rank Tensor Regression
We propose a sparse and low-rank tensor regression model to relate a uni...
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09/18/2018
Model-Protected Multi-Task Learning
Multi-task learning (MTL) refers to the paradigm of learning multiple re...
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05/22/2018
Multi-View Graph Convolutional Network and Its Applications on Neuroimage Analysis for Parkinson's Disease
Parkinson's Disease (PD) is one of the most prevalent neurodegenerative ...
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04/28/2018
Drug Similarity Integration Through Attentive Multi-view Graph Auto-Encoders
Drug similarity has been studied to support downstream clinical tasks su...
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03/15/2018
Distributed Data Vending on Blockchain
Recent advances in blockchain technologies have provided exciting opport...
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02/19/2018
Differentially Private Generative Adversarial Network
Generative Adversarial Network (GAN) and its variants have recently attr...
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02/19/2018
Subspace Network: Deep Multi-Task Censored Regression for Modeling Neurodegenerative Diseases
Over the past decade a wide spectrum of machine learning models have bee...
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02/18/2018
Efficient Large-Scale Fleet Management via Multi-Agent Deep Reinforcement Learning
Large-scale online ride-sharing platforms have substantially transformed...
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02/18/2018
Improving Mild Cognitive Impairment Prediction via Reinforcement Learning and Dialogue Simulation
Mild cognitive impairment (MCI) is a prodromal phase in the progression ...
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02/13/2018
Identify Susceptible Locations in Medical Records via Adversarial Attacks on Deep Predictive Models
The surging availability of electronic medical records (EHR) leads to in...
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01/12/2018
EdgeChain: Blockchain-based Multi-vendor Mobile Edge Application Placement
The state-of-the-art mobile edge applications are generating intense tra...
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09/01/2015
Learning A Task-Specific Deep Architecture For Clustering
While sparse coding-based clustering methods have shown to be successful...
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07/16/2013
