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06/15/2023
ArchGym: An Open-Source Gymnasium for Machine Learning Assisted Architecture Design
Machine learning is a prevalent approach to tame the complexity of desig...
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11/29/2022
Multi-Agent Reinforcement Learning for Microprocessor Design Space Exploration
Microprocessor architects are increasingly resorting to domain-specific ...
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05/11/2022
Tiny Robot Learning: Challenges and Directions for Machine Learning in Resource-Constrained Robots
Machine learning (ML) has become a pervasive tool across computing syste...
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06/07/2021
Widening Access to Applied Machine Learning with TinyML
Broadening access to both computational and educational resources is cri...
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02/08/2021
RL-Scope: Cross-Stack Profiling for Deep Reinforcement Learning Workloads
Deep reinforcement learning (RL) has made groundbreaking advancements in...
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02/05/2021
Machine Learning-Based Automated Design Space Exploration for Autonomous Aerial Robots
Building domain-specific architectures for autonomous aerial robots is c...
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10/02/2019
Quantized Reinforcement Learning (QUARL)
Recent work has shown that quantization can help reduce the memory, comp...
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09/25/2019
Learning to Seek: Autonomous Source Seeking with Deep Reinforcement Learning Onboard a Nano Drone Microcontroller
Fully autonomous navigation using nano drones has numerous application i...
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06/24/2019
The Role of Compute in Autonomous Aerial Vehicles
Autonomous-mobile cyber-physical machines are part of our future. Specif...
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06/02/2019
Air Learning: An AI Research Platform for Algorithm-Hardware Benchmarking of Autonomous Aerial Robots
We introduce Air Learning, an AI research platform for benchmarking algo...
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05/15/2019
