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ICML
2000
IEEE
15 years 7 months ago
Using Knowledge to Speed Learning: A Comparison of Knowledge-based Cascade-correlation and Multi-task Learning
Cognitive modeling with neural networks unrealistically ignores the role of knowledge in learning by starting from random weights. It is likely that effective use of knowledge by ...
Thomas R. Shultz, François Rivest
105
Voted
FOCS
2005
IEEE
15 years 8 months ago
Mechanism Design via Machine Learning
We use techniques from sample-complexity in machine learning to reduce problems of incentive-compatible mechanism design to standard algorithmic questions, for a wide variety of r...
Maria-Florina Balcan, Avrim Blum, Jason D. Hartlin...
VLSID
2005
IEEE
105views VLSI» more  VLSID 2005»
15 years 8 months ago
Placement and Routing for 3D-FPGAs Using Reinforcement Learning and Support Vector Machines
The primary advantage of using 3D-FPGA over 2D-FPGA is that the vertical stacking of active layers reduce the Manhattan distance between the components in 3D-FPGA than when placed...
R. Manimegalai, E. Siva Soumya, V. Muralidharan, B...
CDC
2009
IEEE
159views Control Systems» more  CDC 2009»
15 years 7 months ago
A distributed machine learning framework
Abstract— A distributed online learning framework for support vector machines (SVMs) is presented and analyzed. First, the generic binary classification problem is decomposed in...
Tansu Alpcan, Christian Bauckhage
JMLR
2006
108views more  JMLR 2006»
15 years 2 months ago
The Interplay of Optimization and Machine Learning Research
The fields of machine learning and mathematical programming are increasingly intertwined. Optimization problems lie at the heart of most machine learning approaches. The Special T...
Kristin P. Bennett, Emilio Parrado-Hernánde...