Backpropagation, similar to most learning algorithms that can form complex decision surfaces, is prone to overfitting. This work presents classification-based objective functions, ...
: This paper addresses the inference of probabilistic classification models using weakly supervised learning. The main contribution of this work is the development of learning meth...
In this demo, we present a system called iRIN designed for performing image retrieval in image-rich information networks. We first introduce MoK-SimRank to significantly improve...
Xin Jin, Jiebo Luo, Jie Yu, Gang Wang, Dhiraj Josh...
This paper presents a model of neural network embodiment of intentions and planning mechanisms for autonomous agents. The model bridges the dichotomy of symbolic and non-symbolic ...
This paper describes an evolvable hardware (EHW) system for generalized neural network learning. We have developed an ASIC VLSI chip, which is a building block to configure a scal...