69 citations · 208 across the 40 of their papers we have counts for
9 papers · 1 filter
Volterra Neural Networks (VNNs)
Siddharth Roheda, Hamid Krim
The importance of inference in Machine Learning (ML) has led to an explosive number of different proposals in ML, and particularly in Deep Learning. In an attempt to reduce the com…
Deep Adversarial Belief Networks
Yuming Huang, Ashkan Panahi, Hamid Krim +2
We present a novel adversarial framework for training deep belief networks (DBNs), which includes replacing the generator network in the methodology of generative adversarial netwo…
Community Detection and Improved Detectability in Multiplex Networks
Yuming Huang, Ashkan Panahi, Hamid Krim +1
We investigate the widely encountered problem of detecting communities in multiplex networks, such as social networks, with an unknown arbitrary heterogeneous structure. To improve…
Sparse Generative Adversarial Network
Shahin Mahdizadehaghdam, Ashkan Panahi, Hamid Krim
We propose a new approach to Generative Adversarial Networks (GANs) to achieve an improved performance with additional robustness to its so-called and well recognized mode collapse…
Joint Concept Matching based Learning for Zero-Shot Recognition
Wen Tang, Ashkan Panahi, Hamid Krim
Zero-shot learning (ZSL) which aims to recognize unseen object classes by only training on seen object classes, has increasingly been of great interest in Machine Learning, and has…
Robust Multi-Modal Sensor Fusion: An Adversarial Approach
Siddharth Roheda, Hamid Krim, Benjamin S. Riggan
In recent years, multi-modal fusion has attracted a lot of research interest, both in academia, and in industry. Multimodal fusion entails the combination of information from a set…