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Karl Krauth
Karl Krauth
Postdoc, Stanford
Verified email at stanford.edu - Homepage
Title
Cited by
Cited by
Year
Beyond the imitation game: Quantifying and extrapolating the capabilities of language models
A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ...
Transaction on Machine Learning Research, 2022
9992022
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
8372019
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
174*2020
The Effect of Natural Distribution Shift on Question Answering Models
J Miller, K Krauth, B Recht, L Schmidt
International Conference on Machine Learning, 2020
1592020
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
672016
Finite-time analysis of approximate policy iteration for the linear quadratic regulator
K Krauth, S Tu, B Recht
Advances in Neural Information Processing Systems, 2019
582019
Do offline metrics predict online performance in recommender systems?
K Krauth, S Dean, A Zhao, W Guo, M Curmei, B Recht, MI Jordan
NeurIPS Workshop on Consequential Decisions in Dynamic Environments, 2020
432020
Modeling content creator incentives on algorithm-curated platforms
J Hron, K Krauth, MI Jordan, N Kilbertus, S Dean
International Conference on Learning Representations, 2022
332022
On component interactions in two-stage recommender systems
J Hron, K Krauth, MI Jordan, N Kilbertus
Advances in Neural Information Processing Systems, 2021
332021
Generic inference in latent Gaussian process models
EV Bonilla, K Krauth, A Dezfouli
Journal of Machine Learning Research 20 (117), 1-63, 2019
282019
Breaking feedback loops in recommender systems with causal inference
K Krauth, Y Wang, MI Jordan
arXiv preprint arXiv:2207.01616, 2022
182022
The Stereotyping Problem in Collaboratively Filtered Recommender Systems
W Guo, K Krauth, MI Jordan, N Garg
ACM Conference on Equity and Access in Algorithms, Mechanisms, and …, 2021
172021
Recommendation systems with distribution-free reliability guarantees
AN Angelopoulos, K Krauth, S Bates, Y Wang, MI Jordan
Conformal and Probabilistic Prediction with Applications, 175-193, 2023
142023
Exploration in two-stage recommender systems
J Hron, K Krauth, MI Jordan, N Kilbertus
ACM RecSys Workshop on Bandit and Reinforcement Learning from User Interactions, 2020
112020
Design automation of microfluidic single and double emulsion droplets with machine learning
A Lashkaripour, DP McIntyre, SGK Calhoun, K Krauth, DM Densmore, ...
Nature Communications 15 (1), 83, 2024
62024
The Dynamics of Recommender Systems
KM Krauth
University of California, Berkeley, 2022
2022
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