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Found 25 papers, 4 papers with code
Modeling and Analysis of Crypto-Backed Over-Collateralized Stable Derivatives in DeFi
In decentralized finance (DeFi), stablecoins like DAI are designed to offer a stable value amidst the fluctuating nature of cryptocurrencies.
CAREForMe: Contextual Multi-Armed Bandit Recommendation Framework for Mental Health
The COVID-19 pandemic has intensified the urgency for effective and accessible mental health interventions in people's daily lives.
Forecasting Cryptocurrency Staking Rewards
This research explores a relatively unexplored area of predicting cryptocurrency staking rewards, offering potential insights to researchers and investors.
IoT in the Era of Generative AI: Vision and Challenges
Equipped with sensing, networking, and computing capabilities, Internet of Things (IoT) such as smartphones, wearables, smart speakers, and household robots have been seamlessly weaved into our daily lives.
Reinforcement Learning for Safe Occupancy Strategies in Educational Spaces during an Epidemic
Epidemic modeling, encompassing deterministic and stochastic approaches, is vital for understanding infectious diseases and informing public health strategies.
Testing learning-enabled cyber-physical systems with Large-Language Models: A Formal Approach
The integration of machine learning (ML) into cyber-physical systems (CPS) offers significant benefits, including enhanced efficiency, predictive capabilities, real-time responsiveness, and the enabling of autonomous operations.
Incentivizing Private Data Sharing in Vehicular Networks: A Game-Theoretic Approach
In the context of evolving smart cities and autonomous transportation systems, Vehicular Ad-hoc Networks (VANETs) and the Internet of Vehicles (IoV) are growing in significance.
Trip Planning for Autonomous Vehicles with Wireless Data Transfer Needs Using Reinforcement Learning
With recent advancements in the field of communications and the Internet of Things, vehicles are becoming more aware of their environment and are evolving towards full autonomy.
Holistic Survey of Privacy and Fairness in Machine Learning
Privacy and fairness are two crucial pillars of responsible Artificial Intelligence (AI) and trustworthy Machine Learning (ML).
SMILE: Robust Network Localization via Sparse and Low-Rank Matrix Decomposition
Motivated by collaborative localization in robotic sensor networks, we consider the problem of large-scale network localization where location estimates are derived from inter-node radio signals.
QLAMMP: A Q-Learning Agent for Optimizing Fees on Automated Market Making Protocols
In particular, we develop a Q-Learning Agent for Market Making Protocols (QLAMMP) that learns the optimal fee rates and leverage coefficients for a given AMM protocol and maximizes the expected fee collected under a range of different market conditions.
Multi-modal Misinformation Detection: Approaches, Challenges and Opportunities
As social media platforms are evolving from text-based forums into multi-modal environments, the nature of misinformation in social media is also transforming accordingly.
DEFER: Distributed Edge Inference for Deep Neural Networks
We find that for the ResNet50 model, the inference throughput of DEFER with 8 compute nodes is 53% higher and per node energy consumption is 63% lower than single device inference.
Federated Learning for Internet of Things: Applications, Challenges, and Opportunities
In this paper, we will discuss the opportunities and challenges of FL in IoT platforms, as well as how it can enable diverse IoT applications.
GCNScheduler: Scheduling Distributed Computing Applications using Graph Convolutional Networks
We consider the classical problem of scheduling task graphs corresponding to complex applications on distributed computing systems.
Dataset: Large-scale Urban IoT Activity Data for DDoS Attack Emulation
As IoT deployments grow in scale for applications such as smart cities, they face increasing cyber-security threats.
Reducing the Volatility of Cryptocurrencies -- A Survey of Stablecoins
In the wake of financial crises, stablecoins are gaining adoption among digital currencies.
Dynamic Curves for Decentralized Autonomous Cryptocurrency Exchanges
In particular, dramatic market price changes can result in low liquidity with respect to one or more of the assets and reduce the total value of the LP.
Inter-Mobile-Device Distance Estimation using Network Localization Algorithms for Digital Contact Logging Applications
Mobile applications are being developed for automated logging of contacts via Bluetooth to help scale up digital contact tracing efforts in the context of the ongoing COVID-19 pandemic.
ARREST: A RSSI Based Approach for Mobile Sensing and Tracking of a Moving Object
Our proposed tracking agent, which we refer to as the TrackBot, uses a single rotating, off-the-shelf, directional antenna, novel angle and relative speed estimation algorithms, and Kalman filtering to continually estimate the relative position of the Leader with decimeter level accuracy (which is comparable to a state-of-the-art multiple access point based RF-localization system) and the relative speed of the Leader with accuracy on the order of 1 m/s.
Online Learning for Wireless Distributed Computing
To the best of our knowledge, MABSTA is the first online algorithm in this domain of task assignment problems and provides provable performance guarantee.
Online Learning Schemes for Power Allocation in Energy Harvesting Communications
In this problem, the transmitter has to choose the transmit power based on the amount of stored energy in its battery with the goal of maximizing the average rate obtained over time.
Stochastic Contextual Bandits with Known Reward Functions
Motivated by networking applications, we analyze a setting where the reward is a known non-linear function of the context and the chosen arm's current state.
Combinatorial Network Optimization with Unknown Variables: Multi-Armed Bandits with Linear Rewards
Furthermore, these policies only require storage that grows linearly in the number of unknown parameters.
