Karl Krauth
Karl Krauth
PhD student, UC Berkeley
Verified email at berkeley.edu - Homepage
Cited by
Cited by
Cloud programming simplified: A berkeley view on serverless computing
E Jonas, J Schleier-Smith, V Sreekanti, CC Tsai, A Khandelwal, Q Pu, ...
arXiv preprint arXiv:1902.03383, 2019
AutoGP: Exploring the capabilities and limitations of Gaussian process models
K Krauth, EV Bonilla, K Cutajar, M Filippone
Conference for Uncertainty in Artificial intelligence (UAI), 2016
Serverless linear algebra
V Shankar, K Krauth, K Vodrahalli, Q Pu, B Recht, I Stoica, ...
Proceedings of the 11th ACM Symposium on Cloud Computing, 281-295, 2020
Finite-time analysis of approximate policy iteration for the linear quadratic regulator
K Krauth, S Tu, B Recht
arXiv preprint arXiv:1905.12842, 2019
Generic Inference in Latent Gaussian Process Models.
EV Bonilla, K Krauth, A Dezfouli
Journal of Machine Learning Research 20 (117), 1-63, 2019
The Effect of Natural Distribution Shift on Question Answering Models
J Miller, K Krauth, B Recht, L Schmidt
International Conference on Machine Learning, 2020
Exploration in two-stage recommender systems
J Hron, K Krauth, MI Jordan, N Kilbertus
arXiv preprint arXiv:2009.08956, 2020
Do Offline Metrics Predict Online Performance in Recommender Systems?
K Krauth, S Dean, A Zhao, W Guo, M Curmei, B Recht, MI Jordan
arXiv preprint arXiv:2011.07931, 2020
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