23.6k citations
- Carnegie Mellon UniversityUS49 papers
- Google (United States)US37 papers
- California Institute of TechnologyUS33 papers
- Amazon (Germany)DE32 papers
- University of Illinois Urbana-ChampaignUS22 papers
- Microsoft (United States)US20 papers
- Stanford UniversityUS20 papers
- The University of Texas at AustinUS20 papers
- University of California, Los AngelesUS20 papers
- University of California, Santa BarbaraUS19 papers
- University of WashingtonUS19 papers
- Georgia Institute of TechnologyUS17 papers
4 papers · 2 filters
The N-Grammys: Accelerating Autoregressive Inference with Learning-Free Batched Speculation
Lawrence Stewart, Matthew Trager, Sujan Kumar Gonugondla +1
Speculative decoding aims to speed up autoregressive generation of a language model by verifying in parallel the tokens generated by a smaller draft model.In this work, we explore…
MixNet: Joining Force of Classical and Modern Approaches Toward the Comprehensive Pipeline in Motor Imagery EEG Classification
Phairot Autthasan, Rattanaphon Chaisaen, Huy Phan +2
Recent advances in deep learning (DL) have significantly impacted motor imagery (MI)-based brain-computer interface (BCI) systems, enhancing the decoding of electroencephalography…
Double Machine Learning at Scale to Predict Causal Impact of Customer Actions
Sushant More, Priya Kotwal, Sujith Chappidi +2
Causal Impact (CI) of customer actions are broadly used across the industry to inform both short- and long-term investment decisions of various types. In this paper, we apply the d…
Universal Model in Online Customer Service
Shu-Ting Pi, Cheng-Ping Hsieh, Qun Liu +1
Building machine learning models can be a time-consuming process that often takes several months to implement in typical business scenarios. To ensure consistent model performance…