Kai Wei
Kai Wei
Graduate student of Electrical Engineering, University of Washington
Verifierad e-postadress på uw.edu - Startsida
TitelCiteras avÅr
Submodularity in Data Subset Selection and Active Learning
K Wei, R Iyer, J Bilmes
International Conference on Machine Learning, 1954–1963, 2015
1032015
Submodular subset selection for large-scale speech training data
K Wei, Y Liu, K Kirchhoff, C Bartels, J Bilmes
2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014
672014
Fast multi-stage submodular maximization
K Wei, R Iyer, J Bilmes
International conference on machine learning, 1494-1502, 2014
592014
Using document summarization techniques for speech data subset selection
K Wei, Y Liu, K Kirchhoff, J Bilmes
Proceedings of the 2013 Conference of the North American Chapter of the …, 2013
532013
Submodular feature selection for high-dimensional acoustic score spaces
Y Liu, K Wei, K Kirchhoff, Y Song, J Bilmes
2013 IEEE International Conference on Acoustics, Speech and Signal …, 2013
512013
Unsupervised submodular subset selection for speech data
K Wei, Y Liu, K Kirchhoff, J Bilmes
2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014
292014
Unsupervised submodular subset selection for speech data
K Wei, Y Liu, K Kirchhoff, J Bilmes
2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014
292014
Mixed robust/average submodular partitioning: Fast algorithms, guarantees, and applications
K Wei, RK Iyer, S Wang, W Bai, JA Bilmes
Advances in Neural Information Processing Systems, 2233-2241, 2015
152015
Algorithms for optimizing the ratio of submodular functions
W Bai, R Iyer, K Wei, J Bilmes
International Conference on Machine Learning, 2751-2759, 2016
102016
Jensen: An easily-extensible c++ toolkit for production-level machine learning and convex optimization
R Iyer, JT Halloran, K Wei
arXiv preprint arXiv:1807.06574, 2018
42018
How to intelligently distribute training data to multiple compute nodes: Distributed machine learning via submodular partitioning
K Wei, R Iyer, S Wang, W Bai, J Bilmes
Neural Information Processing Society (NIPS) Workshop, Montreal, Canada, 2015
42015
Choosing panels of genomics assays using submodular optimization
K Wei, MW Libbrecht, JA Bilmes, WS Noble
Genome biology 17 (1), 229, 2016
32016
Choosing panels of genomics assays using submodular optimization
K Wei, M Libbrecht, J Bilmes, W Noble
Genome Biology 17, 229, 2016
32016
A submodularity framework for data subset selection
K Kirchhoff, J Bilmes, K Wei, Y Liu, A Mandal, C Bartels
WASHINGTON UNIV SEATTLE DEPT OF ELECTRICAL ENGINEERING, 2013
32013
Modeling and Simultaneously Removing Bias via Adversarial Neural Networks
J Moore, J Pfeiffer, K Wei, R Iyer, D Charles, R Gilad-Bachrach, L Boyles, ...
arXiv preprint arXiv:1804.06909, 2018
12018
Submodular Optimization and Data Processing
K Wei
12016
Mixed Robust/Average Submodular Partitioning: Fast Algorithms, Guarantees, and Applications to Parallel Machine Learning and Multi-Label Image Segmentation
K Wei, R Iyer, S Wang, W Bai, J Bilmes
arXiv preprint arXiv:1510.08865, 2015
2015
Mixed Robust/Average Submodular Partitioning: Fast Algorithms, Guarantees, and Applications: NIPS 2015 Extended Supplementary
K Wei, R Iyer, S Wang, W Bai, J Bilmes
arXiv preprint arXiv:1510.08865, 2015
2015
Fast Multi-Stage Submodular Maximization: Extended version
K Wei, W EDU, R Iyer, J Bilmes
2014
Submodularity in Data Subset Selection and Active Learning: Extended Version
K Wei, W EDU, R Iyer, J Bilmes
Systemet kan inte utföra åtgärden just nu. Försök igen senare.
Artiklar 1–20