Daniel Haas
Daniel Haas
Verified email at cs.berkeley.edu - Homepage
Title
Cited by
Cited by
Year
Automating model search for large scale machine learning
ER Sparks, A Talwalkar, D Haas, MJ Franklin, MI Jordan, T Kraska
Proceedings of the Sixth ACM Symposium on Cloud Computing, 368-380, 2015
1292015
Argonaut: Macrotask crowdsourcing for complex data processing
D Haas, J Ansel, L Gu, A Marcus
Proceedings of the VLDB Endowment 8 (12), 1642-1653, 2015
802015
Clamshell: Speeding up crowds for low-latency data labeling
D Haas, J Wang, E Wu, MJ Franklin
arXiv preprint arXiv:1509.05969, 2015
672015
Towards reliable interactive data cleaning: A user survey and recommendations
S Krishnan, D Haas, MJ Franklin, E Wu
Proceedings of the Workshop on Human-In-the-Loop Data Analytics, 1-5, 2016
492016
Detecting people in cubist art
S Ginosar, D Haas, T Brown, J Malik
European Conference on Computer Vision, 101-116, 2014
432014
Wisteria: Nurturing scalable data cleaning infrastructure
D Haas, S Krishnan, J Wang, MJ Franklin, E Wu
Proceedings of the VLDB Endowment 8 (12), 2004-2007, 2015
392015
The Power of Adaptivity in Identifying Statistical Alternatives.
KG Jamieson, D Haas, B Recht
NIPS, 775-783, 2016
152016
Workflow management for crowd worker tasks with fixed throughput and budgets
D Haas, J Ansel, Z Gu, A Marcus
US Patent App. 15/253,411, 2017
82017
System and method for management of processing workers
J Ansel, M Greenstein, D Haas, K Kamalov, A Marcus, M Olszewski, ...
US Patent App. 14/209,306, 2014
62014
Cioppino: Multi-tenant crowd management
D Haas, M Franklin
Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 5 (1), 2017
42017
Reducing error in context-sensitive crowdsourced tasks
D Haas, M Greenstein, K Kamalov, A Marcus, M Olszewski, M Piette
Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 1 (1), 2013
32013
App Store for EHRs and Patients Both.
T Franckle, D Haas, KD Mandl
AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits …, 2013
32013
On the detection of mixture distributions with applications to the most biased coin problem
K Jamieson, D Haas, B Recht
arXiv preprint arXiv:1603.08037, 2016
12016
Predictive model of task quality for crowd worker tasks
D Haas, J Ansel, Z Gu, A Marcus
US Patent App. 15/253,483, 2017
2017
Hierarchical review structure for crowd worker tasks
D Haas, J Ansel, Z Gu, A Marcus
US Patent App. 15/253,505, 2017
2017
High-Performance Systems for Crowdsourced Data Analysis
D Haas
UC Berkeley, 2017
2017
CarPhD
D Bruckner, D Haas, C Thompson
South Beach: A Model For the Healthy Consumption of Resources
D Haas, ER Sparks
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Articles 1–18