Lecture Notes in Computer Science - Algorithmic Learning Theory
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Published By Springer Berlin Heidelberg

9783540752240, 9783540752257

Latest Documents Most Cited Documents Contributed Authors Related Sources Related Keywords

Simple Algorithmic Principles of Discovery, Subjective Beauty, Selective Attention, Curiosity and Creativity

Lecture Notes in Computer Science - Algorithmic Learning Theory ◽

10.1007/978-3-540-75225-7_6 ◽

2007 ◽

pp. 32-33 ◽

Cited By ~ 3

Author(s):

Jürgen Schmidhuber

Keyword(s):

Selective Attention

Learning in Friedberg Numberings

Lecture Notes in Computer Science - Algorithmic Learning Theory ◽

10.1007/978-3-540-75225-7_10 ◽

2007 ◽

pp. 79-93 ◽

Cited By ~ 3

Author(s):

Sanjay Jain ◽

Frank Stephan

Polynomial Time Algorithms for Learning k-Reversible Languages and Pattern Languages with Correction Queries

Lecture Notes in Computer Science - Algorithmic Learning Theory ◽

10.1007/978-3-540-75225-7_23 ◽

2007 ◽

pp. 272-284 ◽

Cited By ~ 3

Author(s):

Cristina Tîrnăucă ◽

Timo Knuutila

Keyword(s):

Polynomial Time ◽

Pattern Languages ◽

Polynomial Time Algorithms

Continuity of Performance Metrics for Thin Feature Maps

Lecture Notes in Computer Science - Algorithmic Learning Theory ◽

10.1007/978-3-540-75225-7_28 ◽

2007 ◽

pp. 343-357

Author(s):

Adam Kowalczyk

Keyword(s):

Performance Metrics ◽

Feature Maps

Multiple Pass Streaming Algorithms for Learning Mixtures of Distributions in ${\mathbb R}^d$

Lecture Notes in Computer Science - Algorithmic Learning Theory ◽

10.1007/978-3-540-75225-7_19 ◽

2007 ◽

pp. 211-226 ◽

Cited By ~ 1

Author(s):

Kevin L. Chang

Keyword(s):

Streaming Algorithms ◽

Mixtures Of Distributions ◽

Multiple Pass

Following the Perturbed Leader to Gamble at Multi-armed Bandits

Lecture Notes in Computer Science - Algorithmic Learning Theory ◽

10.1007/978-3-540-75225-7_16 ◽

2007 ◽

pp. 166-180 ◽

Cited By ~ 3

Author(s):

Jussi Kujala ◽

Tapio Elomaa

Feasible Iteration of Feasible Learning Functionals

Lecture Notes in Computer Science - Algorithmic Learning Theory ◽

10.1007/978-3-540-75225-7_7 ◽

2007 ◽

pp. 34-48 ◽

Cited By ~ 4

Author(s):

John Case ◽

Timo Kötzing ◽

Todd Paddock

Pseudometrics for State Aggregation in Average Reward Markov Decision Processes

Lecture Notes in Computer Science - Algorithmic Learning Theory ◽

10.1007/978-3-540-75225-7_30 ◽

2007 ◽

pp. 373-387 ◽

Cited By ~ 11

Author(s):

Ronald Ortner

Keyword(s):

Markov Decision Processes ◽

Decision Processes ◽

Average Reward ◽

State Aggregation ◽

Markov Decision

Vapnik-Chervonenkis Dimension of Parallel Arithmetic Computations

Lecture Notes in Computer Science - Algorithmic Learning Theory ◽

10.1007/978-3-540-75225-7_12 ◽

2007 ◽

pp. 107-119 ◽

Cited By ~ 1

Author(s):

César L. Alonso ◽

José Luis Montaña

Keyword(s):

Parallel Arithmetic

One-Shot Learners Using Negative Counterexamples and Nearest Positive Examples

Lecture Notes in Computer Science - Algorithmic Learning Theory ◽

10.1007/978-3-540-75225-7_22 ◽

2007 ◽

pp. 257-271 ◽

Cited By ~ 4

Author(s):

Sanjay Jain ◽

Efim Kinber

Lecture Notes in Computer Science - Algorithmic Learning TheoryLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer Berlin Heidelberg

Simple Algorithmic Principles of Discovery, Subjective Beauty, Selective Attention, Curiosity and Creativity

Learning in Friedberg Numberings

Polynomial Time Algorithms for Learning k-Reversible Languages and Pattern Languages with Correction Queries

Continuity of Performance Metrics for Thin Feature Maps

Multiple Pass Streaming Algorithms for Learning Mixtures of Distributions in ${\mathbb R}^d$

Following the Perturbed Leader to Gamble at Multi-armed Bandits

Feasible Iteration of Feasible Learning Functionals

Pseudometrics for State Aggregation in Average Reward Markov Decision Processes

Vapnik-Chervonenkis Dimension of Parallel Arithmetic Computations

One-Shot Learners Using Negative Counterexamples and Nearest Positive Examples

Lecture Notes in Computer Science - Algorithmic Learning Theory
Latest Publications