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AAAI
2008
15 years 8 months ago
Constrained Classification on Structured Data
Most standard learning algorithms, such as Logistic Regression (LR) and the Support Vector Machine (SVM), are designed to deal with i.i.d. (independent and identically distributed...
Chi-Hoon Lee, Matthew R. G. Brown, Russell Greiner...
STOC
2006
ACM
116views Algorithms» more  STOC 2006»
16 years 6 months ago
Linear degree extractors and the inapproximability of max clique and chromatic number
: We derandomize results of H?astad (1999) and Feige and Kilian (1998) and show that for all > 0, approximating MAX CLIQUE and CHROMATIC NUMBER to within n1are NP-hard. We furt...
David Zuckerman
KBSE
2007
IEEE
16 years 24 days ago
Nighthawk: a two-level genetic-random unit test data generator
Randomized testing has been shown to be an effective method for testing software units. However, the thoroughness of randomized unit testing varies widely according to the settin...
James H. Andrews, Felix Chun Hang Li, Tim Menzies
CORR
2010
Springer
136views Education» more  CORR 2010»
15 years 3 months ago
Comparing Prediction Market Structures, With an Application to Market Making
Ensuring sufficient liquidity is one of the key challenges for designers of prediction markets. Various market making algorithms have been proposed in the literature and deployed ...
Aseem Brahma, Sanmay Das, Malik Magdon-Ismail
ASIACRYPT
2011
Springer
14 years 6 months ago
Short Signatures from Weaker Assumptions
We provide constructions of (m, 1)-programmable hash functions (PHFs) for m ≥ 2. Mimicking certain programmability properties of random oracles, PHFs can, e.g., be plugged into ...
Dennis Hofheinz, Tibor Jager, Eike Kiltz