Ninh Pham
Ninh Pham
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Fast and scalable polynomial kernels via explicit feature maps
N Pham, R Pagh
Proceedings of the 19th ACM SIGKDD international conference on Knowledge …, 2013
A near-linear time approximation algorithm for angle-based outlier detection in high-dimensional data
N Pham, R Pagh
Proceedings of the 18th ACM SIGKDD international conference on Knowledge …, 2012
Efficient estimation for high similarities using odd sketches
M Mitzenmacher, R Pagh, N Pham
Proceedings of the 23rd international conference on World wide web, 109-118, 2014
Online discovery of top-k similar motifs in time series data
HT Lam, ND Pham, T Calders
Proceedings of the 2011 SIAM International Conference on Data Mining, 1004-1015, 2011
Two novel adaptive symbolic representations for similarity search in time series databases
ND Pham, QL Le, TK Dang
2010 12th International Asia-Pacific Web Conference, 181-187, 2010
I/O-efficient similarity join
R Pagh, N Pham, F Silvestri, M Stöckel
Algorithmica 78 (4), 1263-1283, 2017
HOT aSAX: A novel adaptive symbolic representation for time series discords discovery
ND Pham, QL Le, TK Dang
Asian Conference on Intelligent Information and Database Systems, 113-121, 2010
Scalability and total recall with fast CoveringLSH
N Pham, R Pagh
Proceedings of the 25th ACM International on Conference on Information and …, 2016
Hybrid LSH: faster near neighbors reporting in high-dimensional space
N Pham
arXiv preprint arXiv:1607.06179, 2016
L1-depth revisited: A robust angle-based outlier factor in high-dimensional space
N Pham
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2018
On predicting student performance using low-rank matrix factorization techniques
S Lorenzen, N Pham, S Alstrup
European Conference on e-Learning, 326-334, 2017
Revisiting Wedge Sampling for Budgeted Maximum Inner Product Search
SS Lorenzen, N Pham
arXiv preprint arXiv:1908.08656, 2019
DABAI: A data driven project for e-Learning in Denmark
S Alstrup, C Hansen, C Hansen, N Hjuler, S Lorenzen, N Pham
European Conference on e-Learning, 18-24, 2017
Sublinear Maximum Inner Product Search using Concomitants of Extreme Order Statistics
N Pham
arXiv preprint arXiv:2012.11098, 2020
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