scholarly journals A Bayesian Optimization Framework for Neural Network Compression

2019 ◽  
Author(s):  
Xingchen Ma ◽  
Amal Rannen Triki ◽  
Maxim Berman ◽  
Christos Sagonas ◽  
Jacques Cali ◽  
...  
Keyword(s):  
Neural Network ◽  
Bayesian Optimization ◽  
Optimization Framework ◽  
Network Compression

scholarly journals Neural Network Based Country Wise Risk Prediction of COVID-19

2020 ◽  
Author(s):  
Ratnabali Pal ◽  
Arif Ahmed Sekh ◽  
Samarjit Kar ◽  
Dilip K. Prasad
Keyword(s):  
Neural Network ◽  
Short Term Memory ◽  
Bayesian Optimization ◽  
Weather Data ◽  
Risk Category ◽  
The Novel ◽  
Optimization Framework ◽  
Long Duration ◽  
Trend Data ◽  
Country Specific

The recent worldwide outbreak of the novel corona-virus (COVID-19) opened up new challenges to the research community. Artificial intelligence (AI) driven methods can be useful to predict the parameters, risks, and effects of such an epidemic. Such predictions can be helpful to control and prevent the spread of such diseases. The main challenges of applying AI is the small volume of data and the uncertain nature. Here, we propose a shallow Long short-term memory (LSTM) based neural network to predict the risk category of a country. We have used a Bayesian optimization framework to optimized and automatically design country-specific networks. We have combined the trend data and weather data together for the prediction. The results show that the proposed pipeline outperforms against state-of-the-art methods for 170 countries data and can be a useful tool for such risk categorization. The tool can be used to predict long-duration outbreak of such an epidemic such that we can take preventive steps earlier.

CrossEncoders: A complex neural network compression framework

2018 ◽  
Vol 2018 (2) ◽  
pp. 153-1-153-5
Author(s):  
Chirag Agarwal ◽  
Mehdi Sharifzadeh ◽  
Dan Schonfeld
Keyword(s):  
Neural Network ◽  
Network Compression

scholarly journals Multi-fidelity black-box optimization for time-optimal quadrotor maneuvers

2021 ◽  
pp. 027836492110333
Author(s):  
Gilhyun Ryou ◽  
Ezra Tal ◽  
Sertac Karaman
Keyword(s):  
Real World ◽  
High Speed ◽  
Analytical Approximation ◽  
Black Box ◽  
Bayesian Optimization ◽  
Optimization Framework ◽  
Quadrotor Aircraft ◽  
Time Optimal ◽  
Feasibility Constraints ◽  
Generation Problem

We consider the problem of generating a time-optimal quadrotor trajectory for highly maneuverable vehicles, such as quadrotor aircraft. The problem is challenging because the optimal trajectory is located on the boundary of the set of dynamically feasible trajectories. This boundary is hard to model as it involves limitations of the entire system, including complex aerodynamic and electromechanical phenomena, in agile high-speed flight. In this work, we propose a multi-fidelity Bayesian optimization framework that models the feasibility constraints based on analytical approximation, numerical simulation, and real-world flight experiments. By combining evaluations at different fidelities, trajectory time is optimized while the number of costly flight experiments is kept to a minimum. The algorithm is thoroughly evaluated for the trajectory generation problem in two different scenarios: (1) connecting predetermined waypoints; (2) planning in obstacle-rich environments. For each scenario, we conduct both simulation and real-world flight experiments at speeds up to 11 m/s. Resulting trajectories were found to be significantly faster than those obtained through minimum-snap trajectory planning.

scholarly journals On the Role of Structured Pruning for Neural Network Compression

2021 ◽  
Author(s):  
Andrea Bragagnolo ◽  
Enzo Tartaglione ◽  
Attilio Fiandrotti ◽  
Marco Grangetto
Keyword(s):  
Neural Network ◽  
Network Compression

scholarly journals Deep Neural Network Compression for Aircraft Collision Avoidance Systems

2019 ◽  
Vol 42 (3) ◽  
pp. 598-608 ◽  
Author(s):  
Kyle D. Julian ◽  
Mykel J. Kochenderfer ◽  
Michael P. Owen
Keyword(s):  
Neural Network ◽  
Collision Avoidance ◽  
Deep Neural Network ◽  
Network Compression
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