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ECML
2004
Springer
15 years 12 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
CVPR
1998
IEEE
15 years 11 months ago
Minimax Entropy and Learning by Diffusion
1 A system of coupled differential equations is formulated which learns priors for modelling "preattentive" textures. It is derived from an energy functional consisting o...
Jayant Shah
ECAI
2008
Springer
15 years 8 months ago
Online Rule Learning via Weighted Model Counting
Online multiplicative weight-update learning algorithms, such as Winnow, have proven to behave remarkably for learning simple disjunctions with few relevant attributes. The aim of ...
Frédéric Koriche
NIPS
2008
15 years 8 months ago
Supervised Dictionary Learning
It is now well established that sparse signal models are well suited for restoration tasks and can be effectively learned from audio, image, and video data. Recent research has be...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
NIPS
2007
15 years 8 months ago
Learning to classify complex patterns using a VLSI network of spiking neurons
We propose a compact, low power VLSI network of spiking neurons which can learn to classify complex patterns of mean firing rates on–line and in real–time. The network of int...
Srinjoy Mitra, Giacomo Indiveri, Stefano Fusi