Feature hashing for large scale multitask learning

ACM International Conference Proceeding Series

Volumn 382, Issue , 2009, Pages

  Weinberger, Kilian ^a   Dasgupta, Anirban ^a   Langford, John ^a   Smola, Alex ^a   Attenberg, Josh ^a  

^a YAHOO RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DIMENSIONALITY REDUCTION; EMPIRICAL EVIDENCE; EXPONENTIAL TAIL; HIGH PROBABILITY; MULTITASK LEARNING; NON-PARAMETRIC ESTIMATIONS; RANDOM SUBSPACES;

ROBOT LEARNING;

EDUCATION;

EID: 70049083823     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1553374.1553516     Document Type: Conference Paper

References (12)

1. Achlioptas, D. (2003). Database-friendly random projections: Johnson-lindenstrauss with binary coins. Journal of Computer and System Sciences, 66, 671-687.
2. Bennett, J., & Lanning, S. (2007). The Netflix Prize. Proceedings of Conference on Knowledge Discovery and Data Mining Cup and Workshop 2007.
3. Bernstein, S. (1946). The theory of probabilities. Moscow: Gastehizdat Publishing House.
4. Daume, H. (2007). Frustratingly easy domain adaptation. Annual Meeting of the Association for Computational Linguistics (p. 256).
5. Ganchev, K., & Dredze, M. (2008). Small statistical models by random feature mixing. Workshop on Mobile Language Processing, Annual Meeting of the Association for Computational Linguistics.
6. Gionis, A., Indyk, P., & Motwani, R. (1999). Similarity search in high dimensions via hashing. Proceedings of the 25th VLDB Conference (pp. 518-529). Edinburgh, Scotland: Morgan Kaufmann.
7. Langford, J., Li, L., & Strehl, A. (2007). Vowpal wabbit online learning project (Technical Report). http://hunch.net/?p=309.
8. Ledoux, M. (2001). The concentration of measure phenomenon. Providence, RI: AMS.
9. Li, P., Church, K., & Hastie, T. (2007). Conditional random sampling: A sketch-based sampling technique for sparse data. In B. Schölkopf, J. Platt and T. Hoffman (Eds.), Advances in neural information processing systems 19, 873-880. Cambridge, MA: MIT Press.
10. Rahimi, A., & Recht, B. (2008). Random features for largescale kernel machines. In J. Platt, D. Koller, Y. Singer and S. Roweis (Eds.), Advances in neural information processing systems 20. Cambridge, MA: MIT Press.
11. Rahimi, A., & Recht, B. (2009). Randomized kitchen sinks. In L. Bottou, Y. Bengio, D. Schuurmans and D. Koller (Eds.), Advances in neural information processing systems 21. Cambridge, MA: MIT Press.
12. Shi, Q., Petterson, J., Dror, G., Langford, J., Smola, A., Strehl, A., & Vishwanathan, V. (2009). Hash kernels. Proc. Intl.Workshop on Artificial Intelligence and Statistics 12.