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Combining labeled and unlabeled data with co-training
- A. Blum, Tom. Mitchell
- Computer ScienceCOLT' 98
- 24 July 1998
TLDR
Variational Dropout and the Local Reparameterization Trick
- A. Blum, Nika Haghtalab, Ariel D. Procaccia
- Computer ScienceNIPS
- 2015
TLDR
Selection of Relevant Features and Examples in Machine Learning
- A. Blum, P. Langley
- Computer ScienceArtif. Intell.
- 1 December 1997
Practical privacy: the SuLQ framework
- A. Blum, C. Dwork, Frank McSherry, Kobbi Nissim
- Computer SciencePODS '05
- 13 June 2005
TLDR
A learning theory approach to non-interactive database privacy
- A. Blum, Katrina Ligett, Aaron Roth
- Computer Science, MathematicsSTOC
- 17 May 2008
TLDR
Learning from Labeled and Unlabeled Data using Graph Mincuts
- A. Blum, Shuchi Chawla
- Computer ScienceICML
- 28 June 2001
TLDR
Noise-tolerant learning, the parity problem, and the statistical query model
- A. Blum, A. Kalai, H. Wasserman
- Computer ScienceJACM
- 15 October 2000
TLDR
Clearing algorithms for barter exchange markets: enabling nationwide kidney exchanges
- David J. Abraham, A. Blum, T. Sandholm
- Computer ScienceEC '07
- 11 June 2007
TLDR
The minimum latency problem
- A. Blum, P. Chalasani, D. Coppersmith, W. Pulleyblank, P. Raghavan, M. Sudan
- Computer ScienceSTOC '94
- 23 May 1994
TLDR
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