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NIPS
2004
13 years 11 months ago
Co-Training and Expansion: Towards Bridging Theory and Practice
Co-training is a method for combining labeled and unlabeled data when examples can be thought of as containing two distinct sets of features. It has had a number of practical succ...
Maria-Florina Balcan, Avrim Blum, Ke Yang
EMNLP
2009
13 years 7 months ago
Sinuhe - Statistical Machine Translation using a Globally Trained Conditional Exponential Family Translation Model
We present a new phrase-based conditional exponential family translation model for statistical machine translation. The model operates on a feature representation in which sentenc...
Matti Kääriäinen
AAAI
2007
14 years 12 days ago
Combining Multiple Heuristics Online
We present black-box techniques for learning how to interleave the execution of multiple heuristics in order to improve average-case performance. In our model, a user is given a s...
Matthew J. Streeter, Daniel Golovin, Stephen F. Sm...
AUSAI
2003
Springer
14 years 3 months ago
Guided Operators for a Hyper-Heuristic Genetic Algorithm
We have recently introduced a hyper-heuristic genetic algorithm (hyper-GA) with an adaptive length chromosome which aims to evolve an ordering of low-level heuristics so as to find...
Limin Han, Graham Kendall
PLDI
2004
ACM
14 years 3 months ago
Inducing heuristics to decide whether to schedule
Instruction scheduling is a compiler optimization that can improve program speed, sometimes by 10% or more—but it can also be expensive. Furthermore, time spent optimizing is mo...
John Cavazos, J. Eliot B. Moss