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» On the Complexity of Function Learning
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NIPS
2008
15 years 6 months ago
Deep Learning with Kernel Regularization for Visual Recognition
In this paper we aim to train deep neural networks for rapid visual recognition. The task is highly challenging, largely due to the lack of a meaningful regularizer on the functio...
Kai Yu, Wei Xu, Yihong Gong
167
Voted
NIPS
2004
15 years 6 months ago
Semi-supervised Learning on Directed Graphs
Given a directed graph in which some of the nodes are labeled, we investigate the question of how to exploit the link structure of the graph to infer the labels of the remaining u...
Dengyong Zhou, Bernhard Schölkopf, Thomas Hof...
ICML
1999
IEEE
16 years 5 months ago
Least-Squares Temporal Difference Learning
Excerpted from: Boyan, Justin. Learning Evaluation Functions for Global Optimization. Ph.D. thesis, Carnegie Mellon University, August 1998. (Available as Technical Report CMU-CS-...
Justin A. Boyan
139
Voted
EUROSYS
2007
ACM
16 years 2 months ago
Melange: creating a "functional" internet
Most implementations of critical Internet protocols are written in type-unsafe languages such as C or C++ and are regularly vulnerable to serious security and reliability problems...
Anil Madhavapeddy, Alex Ho, Tim Deegan, David Scot...
173
Voted
COCO
1994
Springer
140views Algorithms» more  COCO 1994»
15 years 9 months ago
Random Debaters and the Hardness of Approximating Stochastic Functions
A probabilistically checkable debate system (PCDS) for a language L consists of a probabilisticpolynomial-time veri er V and a debate between Player 1, who claims that the input x ...
Anne Condon, Joan Feigenbaum, Carsten Lund, Peter ...