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150
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ISAMI
2010
15 years 1 months ago
Employing Compact Intra-genomic Language Models to Predict Genomic Sequences and Characterize Their Entropy
Probabilistic models of languages are fundamental to understand and learn the profile of the subjacent code in order to estimate its entropy, enabling the verification and predicti...
Sérgio A. D. Deusdado, Paulo Carvalho
124
Voted
ICML
2008
IEEE
16 years 4 months ago
Semi-supervised learning of compact document representations with deep networks
Finding good representations of text documents is crucial in information retrieval and classification systems. Today the most popular document representation is based on a vector ...
Marc'Aurelio Ranzato, Martin Szummer
116
Voted
ICML
2002
IEEE
16 years 4 months ago
Learning from Scarce Experience
Searching the space of policies directly for the optimal policy has been one popular method for solving partially observable reinforcement learning problems. Typically, with each ...
Leonid Peshkin, Christian R. Shelton
108
Voted
AIED
2009
Springer
15 years 10 months ago
Toward Scenario Adaptation for Learning
Abstract. This paper presents a methodology for automatically customizing a scenario to suit a learner’s abilities, needs, or goals. Training scenarios are often utilized to give...
James Niehaus, Mark Riedl
130
Voted
AAAI
2010
15 years 5 months ago
Reinforcement Learning via AIXI Approximation
This paper introduces a principled approach for the design of a scalable general reinforcement learning agent. This approach is based on a direct approximation of AIXI, a Bayesian...
Joel Veness, Kee Siong Ng, Marcus Hutter, David Si...