High Efficiency
High efficiency in various computational domains is a central research theme, aiming to minimize resource consumption (time, memory, energy) while maintaining or improving performance. Current efforts focus on developing novel algorithms and architectures, such as optimized Thompson sampling for reinforcement learning, sparse attention mechanisms for transformers, and efficient model compression techniques, to achieve this goal across diverse applications including natural language processing, computer vision, and robotics. These advancements are crucial for deploying complex AI models on resource-constrained devices and for accelerating scientific discovery in data-intensive fields.
Papers
Energy Efficiency Considerations for Popular AI Benchmarks
Raphael Fischer, Matthias Jakobs, Katharina Morik
Efficient and Effective Text Encoding for Chinese LLaMA and Alpaca
Yiming Cui, Ziqing Yang, Xin Yao
Memento: Facilitating Effortless, Efficient, and Reliable ML Experiments
Zac Pullar-Strecker, Xinglong Chang, Liam Brydon, Ioannis Ziogas, Katharina Dost, Jörg Wicker