AIMC Topic: Learning

Clear Filters Showing 1341 to 1350 of 1476 articles

Extracting Low-Dimensional Psychological Representations from Convolutional Neural Networks.

Cognitive science
Convolutional neural networks (CNNs) are increasingly widely used in psychology and neuroscience to predict how human minds and brains respond to visual images. Typically, CNNs represent these images using thousands of features that are learned throu...

Progressive Interpretation Synthesis: Interpreting Task Solving by Quantifying Previously Used and Unused Information.

Neural computation
A deep neural network is a good task solver, but it is difficult to make sense of its operation. People have different ideas about how to interpret its operation. We look at this problem from a new perspective where the interpretation of task solving...

Recurrent Neural-Linear Posterior Sampling for Nonstationary Contextual Bandits.

Neural computation
An agent in a nonstationary contextual bandit problem should balance between exploration and the exploitation of (periodic or structured) patterns present in its previous experiences. Handcrafting an appropriate historical context is an attractive al...

multi-type neighbors enhanced global topology and pairwise attribute learning for drug-protein interaction prediction.

Briefings in bioinformatics
MOTIVATION: Accurate identification of proteins interacted with drugs helps reduce the time and cost of drug development. Most of previous methods focused on integrating multisource data about drugs and proteins for predicting drug-target interaction...

Provenance of life: Chemical autonomous agents surviving through associative learning.

Physical review. E
We present a benchmark study of autonomous, chemical agents exhibiting associative learning of an environmental feature. Associative learning systems have been widely studied in cognitive science and artificial intelligence but are most commonly impl...

CED-Net: A more effective DenseNet model with channel enhancement.

Mathematical biosciences and engineering : MBE
In recent years, deep convolutional neural network (CNN) has been applied more and more increasingly used in computer vision, natural language processing and other fields. At the same time, low-power platforms have more and more significant requireme...

A survey of adaptive optimal control theory.

Mathematical biosciences and engineering : MBE
This paper makes a survey about the recent development of optimal control based on adaptive dynamic programming (ADP). First of all, based on DP algorithm and reinforcement learning (RL) algorithm, the origin and development of the optimization idea ...

Braitenberg Vehicles as Developmental Neurosimulation.

Artificial life
Connecting brain and behavior is a longstanding issue in the areas of behavioral science, artificial intelligence, and neurobiology. As is standard among models of artificial and biological neural networks, an analogue of the fully mature brain is pr...

Learning Dynamic Patient-Robot Task Assignment and Scheduling for A Robotic Rehabilitation Gym.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings]
A robotic rehabilitation gym is a setup that allows multiple patients to exercise together using multiple robots. The effectiveness of training in such a group setting could be increased by dynamically assigning patients to specific robots. In this s...