Shiftable Context: Addressing Training-Inference Context Mismatch in Simultaneous Speech Translation
Transformer models using segment-based processing have been an effective architecture for simultaneous speech translation. However, such models create a context mismatch between training and...
RAPID: Enabling Fast Online Policy Learning in Dynamic Public Cloud Environments
Resource sharing between multiple workloads has become a prominent practice among cloud service providers, motivated by demand for improved resource utilization and reduced cost of ownership....
PROMPT: Learning Dynamic Resource Allocation Policies for Network Applications
A growing number of service providers are exploring methods to improve server utilization and reduce power consumption by co-scheduling high-priority latency-critical workloads with best-effort...
Optimizing Routerless Network-on-Chip Designs: An Innovative Learning-Based Framework
Machine learning applied to architecture design presents a promising opportunity with broad applications. Recent deep reinforcement learning (DRL) techniques, in particular, enable efficient...