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» Superset Learning Based on Generalized Loss Minimization
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TCBB
2008
120views more  TCBB 2008»
14 years 10 months ago
Learning Scoring Schemes for Sequence Alignment from Partial Examples
When aligning biological sequences, the choice of scoring scheme is critical. Even small changes in gap penalties, for example, can yield radically different alignments. A rigorous...
Eagu Kim, John D. Kececioglu
SIAMJO
2010
127views more  SIAMJO 2010»
14 years 4 months ago
Trace Norm Regularization: Reformulations, Algorithms, and Multi-Task Learning
We consider a recently proposed optimization formulation of multi-task learning based on trace norm regularized least squares. While this problem may be formulated as a semidefini...
Ting Kei Pong, Paul Tseng, Shuiwang Ji, Jieping Ye
EMNLP
2011
13 years 9 months ago
Watermarking the Outputs of Structured Prediction with an application in Statistical Machine Translation
We propose a general method to watermark and probabilistically identify the structured outputs of machine learning algorithms. Our method is robust to local editing operations and...
Ashish Venugopal, Jakob Uszkoreit, David Talbot, F...
ICS
2010
Tsinghua U.
15 years 7 months ago
Beyond Equilibria: Mechanisms for Repeated Combinatorial Auctions
: We study the design of mechanisms in combinatorial auction domains. We focus on settings where the auction is repeated, motivated by auctions for licenses or advertising space. W...
Brendan Lucier
EH
1999
IEEE
351views Hardware» more  EH 1999»
15 years 2 months ago
Evolvable Hardware or Learning Hardware? Induction of State Machines from Temporal Logic Constraints
Here we advocate an approach to learning hardware based on induction of finite state machines from temporal logic constraints. The method involves training on examples, constraint...
Marek A. Perkowski, Alan Mishchenko, Anatoli N. Ch...