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Competitive Information Disclosure with Multiple Receivers
This paper analyzes a model of competition in Bayesian persuasion in whi...
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FlashP: An Analytical Pipeline for Real-time Forecasting of Time-Series Relational Data
Interactive response time is important in analytical pipelines for users...
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A Pluggable Learned Index Method via Sampling and Gap Insertion
Database indexes facilitate data retrieval and benefit broad application...
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Contrastive Pre-training for Sequential Recommendation
Sequential recommendation methods play a crucial role in modern recommen...
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Intertwining Order Preserving Encryption and Differential Privacy
Ciphertexts of an order-preserving encryption (OPE) scheme preserve the ...
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Interactive Feature Generation via Learning Adjacency Tensor of Feature Graph
To automate the generation of interactive features, recent methods are p...
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Simple and Deep Graph Convolutional Networks
Graph convolutional networks (GCNs) are a powerful deep learning approac...
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Sequential Recommendation with Self-Attentive Multi-Adversarial Network
Recently, deep learning has made significant progress in the task of seq...
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Practical Data Poisoning Attack against Next-Item Recommendation
Online recommendation systems make use of a variety of information sourc...
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AdaBERT: Task-Adaptive BERT Compression with Differentiable Neural Architecture Search
Large pre-trained language models such as BERT have shown their effectiv...
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Automated Relational Meta-learning
In order to efficiently learn with small amount of data on new tasks, me...
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Design of Algorithms under Policy-Aware Local Differential Privacy: Utility-Privacy Trade-offs
Local differential privacy (LDP) enables private data sharing and analyt...
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MURS: Practical and Robust Privacy Amplification with Multi-Party Differential Privacy
When collecting information, local differential privacy (LDP) alleviates...
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Practical and Robust Privacy Amplification with Multi-Party Differential Privacy
When collecting information, local differential privacy (LDP) alleviates...
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Continuous Integration of Machine Learning Models with ease.ml/ci: Towards a Rigorous Yet Practical Treatment
Continuous integration is an indispensable step of modern software engin...
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Efficient Identification of Approximate Best Configuration of Training in Large Datasets
A configuration of training refers to the combinations of feature engine...
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Towards Differentially Private Truth Discovery for Crowd Sensing Systems
Nowadays, crowd sensing becomes increasingly more popular due to the ubi...
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An Algorithmic Framework For Differentially Private Data Analysis on Trusted Processors
Differential privacy has emerged as the main definition for private data...
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Comparing Population Means under Local Differential Privacy: with Significance and Power
A statistical hypothesis test determines whether a hypothesis should be ...
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Collecting Telemetry Data Privately
The collection and analysis of telemetry data from users' devices is rou...
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Learn-Memorize-Recall-Reduce A Robotic Cloud Computing Paradigm
The rise of robotic applications has led to the generation of a huge vol...
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