PhD Seminar • Data Systems — Dynamic Early Exiting for Accelerating BERT Inference
Ji Xin, PhD candidate
David R. Cheriton School of Computer Science
Ji Xin, PhD candidate
David R. Cheriton School of Computer Science
Marcus Brubaker
Department of Electrical Engineering and Computer Science, York University
Research Director, Borealis AI
Modelling and synthesizing image noise is an important aspect in many computer vision applications. The long-standing additive white Gaussian and heteroscedastic (signal-dependent) noise models widely used in the literature provide only a coarse approximation of real sensor noise.
Dmitrii Pasechnik, Department of Computer Science
University of Oxford
Daniel Gibney, Department of Computer Science
University of Central Florida
James Jacobs, Co-founder and CEO
Ziva Dynamics
Richard Peng, School of Computer Science
Georgia Institute of Technology
Vedat Levi Alev, PhD candidate
David R. Cheriton School of Computer Science
Aravind Machiry, Department of Computer Science
University of California, Santa Barbara
Mathieu Nancel
Loki Research Group
Inria Lille, France
Aastha Mehta, Max Planck Institute for Software Systems
Saarbrücken, Germany