activity
20152017
most citedFast, Warped Graph Embedding: Unifying Framework and One-Click Algorithm

24 citations · 47 across the 3 of their papers we have counts for

collaborators

6 papers

cs.LG201723 cited

Generalized Value Iteration Networks: Life Beyond Lattices

Sufeng Niu, Siheng Chen, Hanyu Guo +3

In this paper, we introduce a generalized value iteration network (GVIN), which is an end-to-end neural network planning module. GVIN emulates the value iteration algorithm by usin…

cs.SI201724 cited

Fast, Warped Graph Embedding: Unifying Framework and One-Click Algorithm

Siheng Chen, Sufeng Niu, Leman Akoglu +2

What is the best way to describe a user in a social network with just a few numbers? Mathematically, this is equivalent to assigning a vector representation to each node in a graph…

cs.CV2016

Rotation Invariant Angular Descriptor Via A Bandlimited Gaussian-like Kernel

Michael T. McCann, Matthew Fickus, Jelena Kovacevic

We present a new smooth, Gaussian-like kernel that allows the kernel density estimate for an angular distribution to be exactly represented by a finite number of its Fourier series…

cs.IT2015

Signal Recovery on Graphs: Random versus Experimentally Designed Sampling

Siheng Chen, Rohan Varma, Aarti Singh +1

We study signal recovery on graphs based on two sampling strategies: random sampling and experimentally designed sampling. We propose a new class of smooth graph signals, called ap…

cs.CV2015

Robust hyperspectral image classification with rejection fields

Filipe Condessa, Jose Bioucas-Dias, Jelena Kovacevic

In this paper we present a novel method for robust hyperspectral image classification using context and rejection. Hyperspectral image classification is generally an ill-posed imag…

cs.CV2015

SegSALSA-STR: A convex formulation to supervised hyperspectral image segmentation using hidden fields and structure tensor regularization

Filipe Condessa, Jose Bioucas-Dias, Jelena Kovacevic

We present a supervised hyperspectral image segmentation algorithm based on a convex formulation of a marginal maximum a posteriori segmentation with hidden fields and structure te…