Search Results for author:
Found 12 papers, 3 papers with code
On Solving Close Enough Orienteering Problem with Overlapped Neighborhoods
To tackle CEOP and CEOP-N, we develop a new approach featuring a Randomized Steiner Zone Discretization (RSZD) scheme coupled with a hybrid algorithm based on Particle Swarm Optimization (PSO) and Ant Colony System (ACS), CRaSZe-AntS.
Safe Reinforcement Learning as Wasserstein Variational Inference: Formal Methods for Interpretability
Reinforcement learning can provide effective reasoning for sequential decision-making problems with variable dynamics.
Multi-Agent Reinforcement Learning with Action Masking for UAV-enabled Mobile Communications
Simulation results confirm that: 1) training a shared DQN outperforms a conventional DQN in terms of maximum system throughput (+20%) and training time (-10%); 2) it can converge for agents with different action spaces, yielding a 9% increase in throughput compared to mutual learning algorithms; and 3) combining NOMA with an SDQN architecture enables the network to achieve a better sum rate compared with existing baseline schemes.
Trustworthy Reinforcement Learning for Quadrotor UAV Tracking Control Systems
We propose a novel, interpretable trajectory tracker integrating a Distributional Reinforcement Learning disturbance estimator for unknown aerodynamic effects with a Stochastic Model Predictive Controller (SMPC).
Distributional Reinforcement Learning
reinforcement-learning
+1
Interpretable Stochastic Model Predictive Control using Distributional Reinforced Estimation for Quadrotor Tracking Systems
The proposed framework integrates a distributional Reinforcement Learning (RL) estimator for unknown aerodynamic effects into a Stochastic Model Predictive Controller (SMPC) for trajectory tracking.
Distributional Reinforcement Learning
Model Predictive Control
+1
Towards Battery-Free Machine Learning and Inference in Underwater Environments
This paper is motivated by a simple question: Can we design and build battery-free devices capable of machine learning and inference in underwater environments?
Configurable Privacy-Preserving Automatic Speech Recognition
We show that overlapping speech inputs to ASR systems present further privacy concerns, and how these may be mitigated using speech separation and optimization techniques.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
OnionBot: A System for Collaborative Computational Cooking
An unsolved challenge in cooking automation is designing for shared kitchen workspaces.
Human-Computer Interaction Robotics
Paralinguistic Privacy Protection at the Edge
One approach to mitigate the risk of paralinguistic-based privacy breaches is to exploit a combination of cloud-based processing with privacy-preserving, on-device paralinguistic information learning and filtering before transmitting voice data.
Privacy-preserving Voice Analysis via Disentangled Representations
Our experimental evaluation over five datasets shows that the proposed framework can effectively defend against attribute inference attacks by reducing their success rates to approximately that of guessing at random, while maintaining accuracy in excess of 99% for the tasks of interest.
Emotionless: Privacy-Preserving Speech Analysis for Voice Assistants
The voice signal is a rich resource that discloses several possible states of a speaker, such as emotional state, confidence and stress levels, physical condition, age, gender, and personal traits.
A new approach for pedestrian density estimation using moving sensors and computer vision
However, such methods do not scale to the size of a city and a new approach to fill this gap is here proposed.
