Special Session: Machine Learning for Embedded System Design

Keyphrases

• Machine Learning 100%
• Levels of Abstraction 100%
• Embedded System Design 100%
• Machine Learning Techniques 66%
• Machine Learning Applications 66%
• Embedded Systems 66%
• System Optimization 66%
• Design Verification 66%
• High-level Synthesis 33%
• Integrated Circuits 33%
• System Modeling 33%
• Circuit Level 33%
• Design Optimization 33%
• Architectural Design 33%
• IP Blocks 33%
• Microarchitecture 33%
• Machine Learning-based Approach 33%
• Conventional Design 33%
• NP-hard 33%
• System Verification 33%
• Design Information 33%
• Design Automation 33%
• Reuse Strategy 33%
• Verification Problem 33%
• Verification Data 33%
• Computing Applications 33%
• Productivity Improvement 33%
• Design Productivity 33%
• Time Machine 33%
• System-level Optimization 33%
• Fundamental Limits 33%
• Design Optimization Problem 33%

Computer Science

• Embedded System Design 100%
• Machine Learning 100%
• Learning System 100%
• Embedded System 50%
• Design Optimization 50%
• Design Verification 50%
• High Level Synthesis 25%
• Machine Learning Technique 25%
• Microarchitecture 25%
• Machine Learning-Based Approach 25%
• Architecture Design 25%
• Design Productivity 25%
• Fundamental Limit 25%
• Integrated Circuit 25%
• Design Automation 25%