60 citations · 61 across the 4 of their papers we have counts for
5 papers
Performance of Zero-Shot Time Series Foundation Models on Cloud Data
William Toner, Thomas L. Lee, Artjom Joosen +2
Time series foundation models (FMs) have emerged as a popular paradigm for zero-shot multi-domain forecasting. FMs are trained on numerous diverse datasets and claim to be effectiv…
Lightweight Online Adaption for Time Series Foundation Model Forecasts
Thomas L. Lee, William Toner, Rajkarn Singh +2
Foundation models (FMs) have emerged as a promising approach for time series forecasting. While effective, FMs typically remain fixed during deployment due to the high computationa…
Serverless Cold Starts and Where to Find Them
Artjom Joosen, Ahmed Hassan, Martin Asenov +5
This paper releases and analyzes a month-long trace of 85 billion user requests and 11.9 million cold starts from Huawei's serverless cloud platform. Our analysis spans workloads f…
DAM: Towards A Foundation Model for Time Series Forecasting
Luke Darlow, Qiwen Deng, Ahmed Hassan +5
It is challenging to scale time series forecasting models such that they forecast accurately for multiple distinct domains and datasets, all with potentially different underlying c…
How Does It Function? Characterizing Long-term Trends in Production Serverless Workloads
Artjom Joosen, Ahmed Hassan, Martin Asenov +4
This paper releases and analyzes two new Huawei cloud serverless traces. The traces span a period of over 7 months with over 1.4 trillion function invocations combined. The first t…