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» On-line Algorithms in Machine Learning
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94
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ICAI
2004
15 years 4 months ago
Task Oriented Machine-Learning and Review
We propose an optimization algorithm to execute a previously unlearned task-oriented command in an intelligent machine. We show that a well-defined, physically bounded, task-orien...
Pierre Abdelmalek, Howard E. Michel
145
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ICDE
2011
IEEE
258views Database» more  ICDE 2011»
14 years 6 months ago
SystemML: Declarative machine learning on MapReduce
Abstract—MapReduce is emerging as a generic parallel programming paradigm for large clusters of machines. This trend combined with the growing need to run machine learning (ML) a...
Amol Ghoting, Rajasekar Krishnamurthy, Edwin P. D....
133
Voted
ACL
2012
13 years 5 months ago
Learning Translation Consensus with Structured Label Propagation
In this paper, we address the issue for learning better translation consensus in machine translation (MT) research, and explore the search of translation consensus from similar, r...
Shujie Liu, Chi-Ho Li, Mu Li, Ming Zhou
148
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JMLR
2010
143views more  JMLR 2010»
15 years 1 months ago
A Quasi-Newton Approach to Nonsmooth Convex Optimization Problems in Machine Learning
We extend the well-known BFGS quasi-Newton method and its memory-limited variant LBFGS to the optimization of nonsmooth convex objectives. This is done in a rigorous fashion by ge...
Jin Yu, S. V. N. Vishwanathan, Simon Günter, ...
85
Voted
ICML
2007
IEEE
16 years 3 months ago
Intractability and clustering with constraints
Clustering with constraints is a developing area of machine learning. Various papers have used constraints to enforce particular clusterings, seed clustering algorithms and even l...
Ian Davidson, S. S. Ravi