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09/12/2023
Backdoor Attacks and Countermeasures in Natural Language Processing Models: A Comprehensive Security Review
Deep Neural Networks (DNNs) have led to unprecedented progress in variou...
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05/25/2023
A Robust Classifier Under Missing-Not-At-Random Sample Selection Bias
The shift between the training and testing distributions is commonly due...
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05/16/2023
UOR: Universal Backdoor Attacks on Pre-trained Language Models
Backdoors implanted in pre-trained language models (PLMs) can be transfe...
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03/28/2023
A Universal Identity Backdoor Attack against Speaker Verification based on Siamese Network
Speaker verification has been widely used in many authentication scenari...
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12/17/2022
Enhancing Cyber Resilience of Networked Microgrids using Vertical Federated Reinforcement Learning
This paper presents a novel federated reinforcement learning (Fed-RL) me...
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11/29/2022
Compressing Cross-Lingual Multi-Task Models at Qualtrics
Experience management is an emerging business area where organizations f...
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09/21/2022
CryptoSolve: Towards a Tool for the Symbolic Analysis of Cryptographic Algorithms
Recently, interest has been emerging in the application of symbolic tech...
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08/25/2022
Reduce Communication Costs and Preserve Privacy: Prompt Tuning Method in Federated Learning
Federated learning (FL) has enabled global model training on decentraliz...
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07/22/2022
Towards Fairness-Aware Multi-Objective Optimization
Recent years have seen the rapid development of fairness-aware machine l...
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10/17/2021
Poisoning Attacks on Fair Machine Learning
Both fair machine learning and adversarial learning have been extensivel...
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10/08/2021
Fair Regression under Sample Selection Bias
Recent research on fair regression focused on developing new fairness no...
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05/24/2021
Robust Fairness-aware Learning Under Sample Selection Bias
The underlying assumption of many machine learning algorithms is that th...
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10/10/2020
Fairness-aware Agnostic Federated Learning
Federated learning is an emerging framework that builds centralized mach...
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05/24/2020
PoliteCamera: Respecting Strangers' Privacy in Mobile Photographing
Camera is a standard on-board sensor of modern mobile phones. It makes p...
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04/14/2020
Multi-Resolution A*
Heuristic search-based planning techniques are commonly used for motion ...
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03/08/2020
Removing Disparate Impact of Differentially Private Stochastic Gradient Descent on Model Accuracy
When we enforce differential privacy in machine learning, the utility-pr...
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02/06/2020
Transfer Heterogeneous Knowledge Among Peer-to-Peer Teammates: A Model Distillation Approach
Peer-to-peer knowledge transfer in distributed environments has emerged ...
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03/12/2019
Service Capacity Enhanced Task Offloading and Resource Allocation in Multi-Server Edge Computing Environment
An edge computing environment features multiple edge servers and multipl...
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10/04/2018
Privacy-Preserving Multiparty Learning For Logistic Regression
In recent years, machine learning techniques are widely used in numerous...
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10/02/2018
Privacy-Preserving Outsourcing of Large-Scale Nonlinear Programming to the Cloud
The increasing massive data generated by various sources has given birth...
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06/30/2017
Prepaid or Postpaid? That is the question. Novel Methods of Subscription Type Prediction in Mobile Phone Services
In this paper we investigate the behavioural differences between mobile ...
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02/01/2017
Robust Order Scheduling in the Fashion Industry: A Multi-Objective Optimization Approach
In the fashion industry, order scheduling focuses on the assignment of p...
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12/17/2015