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» Machine Learning by Function Decomposition
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ALT
2004
Springer
15 years 8 months ago
On Kernels, Margins, and Low-Dimensional Mappings
Kernel functions are typically viewed as providing an implicit mapping of points into a high-dimensional space, with the ability to gain much of the power of that space without inc...
Maria-Florina Balcan, Avrim Blum, Santosh Vempala
COLT
2004
Springer
15 years 5 months ago
Graphical Economics
: We introduce a graph-theoretic generalization of classical Arrow-Debreu economics, in which an undirected graph specifies which consumers or economies are permitted to engage in...
Sham Kakade, Michael J. Kearns, Luis E. Ortiz
TPHOL
1999
IEEE
15 years 4 months ago
Three Tactic Theorem Proving
Abstract. We describe the key features of the proof description language of Declare, an experimental theorem prover for higher order logic. We take a somewhat radical approach to p...
Don Syme
ICALP
2011
Springer
14 years 3 months ago
New Algorithms for Learning in Presence of Errors
We give new algorithms for a variety of randomly-generated instances of computational problems using a linearization technique that reduces to solving a system of linear equations...
Sanjeev Arora, Rong Ge
ICML
2005
IEEE
16 years 20 days ago
Optimal assignment kernels for attributed molecular graphs
We propose a new kernel function for attributed molecular graphs, which is based on the idea of computing an optimal assignment from the atoms of one molecule to those of another ...
Andreas Zell, Florian Sieker, Holger Fröhlich...