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» Learning Approximate Consistencies
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FOCS
1992
IEEE
15 years 7 months ago
Proof Verification and Hardness of Approximation Problems
The class PCP(f(n), g(n)) consists of all languages L for which there exists a polynomial-time probabilistic oracle machine that uses O(f(n)) random bits, queries O(g(n)) bits of ...
Sanjeev Arora, Carsten Lund, Rajeev Motwani, Madhu...
ECML
2004
Springer
15 years 9 months ago
Convergence and Divergence in Standard and Averaging Reinforcement Learning
Although tabular reinforcement learning (RL) methods have been proved to converge to an optimal policy, the combination of particular conventional reinforcement learning techniques...
Marco Wiering
ICML
2005
IEEE
16 years 5 months ago
A model for handling approximate, noisy or incomplete labeling in text classification
We introduce a Bayesian model, BayesANIL, that is capable of estimating uncertainties associated with the labeling process. Given a labeled or partially labeled training corpus of...
Ganesh Ramakrishnan, Krishna Prasad Chitrapura, Ra...
124
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AAAI
2008
15 years 6 months ago
Adaptive Importance Sampling with Automatic Model Selection in Value Function Approximation
Off-policy reinforcement learning is aimed at efficiently reusing data samples gathered in the past, which is an essential problem for physically grounded AI as experiments are us...
Hirotaka Hachiya, Takayuki Akiyama, Masashi Sugiya...
COMBINATORICA
2010
14 years 11 months ago
Approximation algorithms via contraction decomposition
We prove that the edges of every graph of bounded (Euler) genus can be partitioned into any prescribed number k of pieces such that contracting any piece results in a graph of bou...
Erik D. Demaine, MohammadTaghi Hajiaghayi, Bojan M...