Daniel Crankshaw
Daniel Crankshaw
Graduate Student, UC Berkeley
Bestätigte E-Mail-Adresse bei cs.berkeley.edu
Titel
Zitiert von
Zitiert von
Jahr
Graphx: Graph processing in a distributed dataflow framework
JE Gonzalez, RS Xin, A Dave, D Crankshaw, MJ Franklin, I Stoica
11th {USENIX} Symposium on Operating Systems Design and Implementation …, 2014
10592014
Clipper: A low-latency online prediction serving system
D Crankshaw, X Wang, G Zhou, MJ Franklin, JE Gonzalez, I Stoica
14th {USENIX} Symposium on Networked Systems Design and Implementation …, 2017
2352017
Graphx: Unifying data-parallel and graph-parallel analytics
RS Xin, D Crankshaw, A Dave, JE Gonzalez, MJ Franklin, I Stoica
arXiv preprint arXiv:1402.2394, 2014
1022014
The missing piece in complex analytics: Low latency, scalable model management and serving with velox
D Crankshaw, P Bailis, JE Gonzalez, H Li, Z Zhang, MJ Franklin, A Ghodsi, ...
arXiv preprint arXiv:1409.3809, 2014
922014
Idk cascades: Fast deep learning by learning not to overthink
X Wang, Y Luo, D Crankshaw, A Tumanov, F Yu, JE Gonzalez
arXiv preprint arXiv:1706.00885, 2017
392017
Inferline: ML inference pipeline composition framework
D Crankshaw, GE Sela, C Zumar, X Mo, JE Gonzalez, I Stoica, ...
arXiv preprint arXiv:1812.01776, 2018
212018
Composing meta-policies for autonomous driving using hierarchical deep reinforcement learning
R Liaw, S Krishnan, A Garg, D Crankshaw, JE Gonzalez, K Goldberg
arXiv preprint arXiv:1711.01503, 2017
112017
Context: The missing piece in the machine learning lifecycle
R Garcia, V Sreekanti, N Yadwadkar, D Crankshaw, JE Gonzalez, ...
KDD CMI Workshop 114, 2018
92018
Scalable training and serving of personalized models
D Crankshaw, X Wang, JE Gonzalez, MJ Franklin
NIPS 2015 Workshop on Machine Learning Systems (LearningSys), 2015
72015
Inverted indices for particle tracking in petascale cosmological simulations
D Crankshaw, R Burns, B Falck, T Budavári, AS Szalay, J Wang
Proceedings of the 25th International Conference on Scientific and …, 2013
42013
GraphX: graph processing in a distributed dataflow framework Mark
JE Gonzalez, RS Xin, A Dave, D Crankshaw, MJ Franklin, I Stoica
22014
The missing piece in complex analytics: Low latency, scalable model management and serving with velox. CIDR, 2015. Supplementary Material A Example algorithm implementation …
D Crankshaw, P Bailis, JE Gonzalez, H Li, Z Zhang, MJ Franklin, A Ghodsi, ...
22014
InferLine: latency-aware provisioning and scaling for prediction serving pipelines
D Crankshaw, GE Sela, X Mo, C Zumar, I Stoica, J Gonzalez, A Tumanov
Proceedings of the 11th ACM Symposium on Cloud Computing, 477-491, 2020
12020
The Indra Simulation Database
B Falck, T Budavari, S Cole, D Crankshaw, L Dobos, G Lemson, ...
American Astronomical Society Meeting Abstracts# 218 218, 131.04, 2011
12011
The Design and Implementation of Low-Latency Prediction Serving Systems
D Crankshaw
UC Berkeley, 2019
2019
InferLine: ML Prediction Pipeline Provisioning and Management for Tight Latency Objectives
D Crankshaw, GE Sela, C Zumar, X Mo, JE Gonzalez, I Stoica, ...
arXiv preprint arXiv:1812.01776, 2018
2018
Database Architecture for the Indra Cosmological Simulations
DS Crankshaw, B Falck, T Budavari, L Dobos, G Lemson, M Neyrinck, ...
American Astronomical Society Meeting Abstracts# 219 219, 145.13, 2012
2012
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