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Found 7 papers, 1 papers with code
SEGEN: SAMPLE-ENSEMBLE GENETIC EVOLUTIONARY NETWORK MODEL
Deep learning, a rebranding of deep neural network research works, has achieved a remarkable success in recent years.
EgoCoder: Intelligent Program Synthesis with Hierarchical Sequential Neural Network Model
To address the problem, a novel generative model, namely EgoCoder, will be introduced in this paper.
Reconciled Polynomial Machine: A Unified Representation of Shallow and Deep Learning Models
In this paper, we aim at introducing a new machine learning model, namely reconciled polynomial machine, which can provide a unified representation of existing shallow and deep machine learning models.
On Deep Ensemble Learning from a Function Approximation Perspective
In this paper, we propose to provide a general ensemble learning framework based on deep learning models.
GEN Model: An Alternative Approach to Deep Neural Network Models
In this paper, we introduce an alternative approach, namely GEN (Genetic Evolution Network) Model, to the deep learning models.
GADAM: Genetic-Evolutionary ADAM for Deep Neural Network Optimization
Deep neural network learning can be formulated as a non-convex optimization problem.
SEGEN: Sample-Ensemble Genetic Evolutional Network Model
Deep learning, a rebranding of deep neural network research works, has achieved a remarkable success in recent years.
