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» On the Complexity of Function Learning
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ICML
2004
IEEE
16 years 1 months ago
Apprenticeship learning via inverse reinforcement learning
We consider learning in a Markov decision process where we are not explicitly given a reward function, but where instead we can observe an expert demonstrating the task that we wa...
Pieter Abbeel, Andrew Y. Ng
199
Voted
ML
2011
ACM
308views Machine Learning» more  ML 2011»
14 years 7 months ago
Relational information gain
Abstract. Type Extension Trees (TET) have been recently introduced as an expressive representation language allowing to encode complex combinatorial features of relational entities...
Marco Lippi, Manfred Jaeger, Paolo Frasconi, Andre...
105
Voted
CORR
2010
Springer
101views Education» more  CORR 2010»
15 years 3 days ago
Online Learning: Random Averages, Combinatorial Parameters, and Learnability
We develop a theory of online learning by defining several complexity measures. Among them are analogues of Rademacher complexity, covering numbers and fatshattering dimension fro...
Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari
198
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Book
796views
16 years 11 months ago
Introduction to Machine Learning
This is an introductory book about machine learning. Notice that this is a draft book. It may contain typos, mistakes, etc. The book covers the following topics: Boolean Functio...
Nils J. Nilsson
TIT
2010
107views Education» more  TIT 2010»
14 years 7 months ago
Rate distortion and denoising of individual data using Kolmogorov complexity
We examine the structure of families of distortion balls from the perspective of Kolmogorov complexity. Special attention is paid to the canonical rate-distortion function of a so...
Nikolai K. Vereshchagin, Paul M. B. Vitányi