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08/19/2023
Finding emergence in data: causal emergence inspired dynamics learning
Modelling complex dynamical systems in a data-driven manner is challengi...
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06/14/2023
System Information Decomposition
In order to characterize complex higher-order interactions among variabl...
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02/20/2023
Dynamic Graph Neural Network with Adaptive Edge Attributes for Air Quality Predictions
Air quality prediction is a typical spatio-temporal modeling problem, wh...
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10/14/2022
No Video Left Behind: A Utility-Preserving Obfuscation Approach for YouTube Recommendations
Online content platforms optimize engagement by providing personalized r...
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09/01/2022
Expectation-Maximizing Network Reconstruction and MostApplicable Network Types Based on Binary Time Series Data
Based on the binary time series data of social infection dynamics, we pr...
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08/03/2022
How Much Privacy Does Federated Learning with Secure Aggregation Guarantee?
Federated learning (FL) has attracted growing interest for enabling priv...
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04/25/2022
Graph Auto-Encoders for Network Completion
Completing a graph means inferring the missing nodes and edges from a pa...
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01/25/2022
Neural Information Squeezer for Causal Emergence
The classic studies of causal emergence have revealed that in some Marko...
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01/13/2022
Privacy-Utility Trades in Crowdsourced Signal Map Obfuscation
Cellular providers and data aggregating companies crowdsource celluar si...
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12/07/2021
Location Leakage in Federated Signal Maps
We consider the problem of predicting cellular network performance (sign...
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11/09/2021
HARPO: Learning to Subvert Online Behavioral Advertising
Online behavioral advertising, and the associated tracking paraphernalia...
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06/24/2021
Tensor networks for unsupervised machine learning
Modeling the joint distribution of high-dimensional data is a central ta...
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11/22/2020
Fairness-guided SMT-based Rectification of Decision Trees and Random Forests
Data-driven decision making is gaining prominence with the popularity of...
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04/14/2020
Gumbel-softmax-based Optimization: A Simple General Framework for Optimization Problems on Graphs
In computer science, there exist a large number of optimization problems...
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01/18/2020
Inference for Network Structure and Dynamics from Time Series Data via Graph Neural Network
Network structures in various backgrounds play important roles in social...
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10/10/2019
Link Prediction via Deep Learning
Link prediction aims to infer the missing links or predicting future one...
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09/16/2019
Gumbel-softmax Optimization: A Simple General Framework for Combinatorial Optimization Problems on Graphs
Many problems in real life can be converted to combinatorial optimizatio...
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12/30/2018
A General Deep Learning Framework for Structure and Dynamics Reconstruction from Time Series Data
In this work, we present Gumbel Graph Network, a model-free deep learnin...
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12/08/2018
Crowdsensing Game with Demand Uncertainties: A Deep Reinforcement Learning Approach
Currently, explosive increase of smartphones with powerful built-in sens...
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11/23/2018
A Novel Learning-based Global Path Planning Algorithm for Planetary Rovers
Autonomous path planning algorithms are significant to planetary explora...
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08/25/2018
A Novel Deep Neural Network Architecture for Mars Visual Navigation
In this paper, emerging deep learning techniques are leveraged to deal w...
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02/02/2018
