output
20132022
most citedFine-Grained Visual Classification of Aircraft

1.2k citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

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Showing cs.LGShow all

7 papers · 1 filter

cs.LG2021★ 6 cited

Topic-aware latent models for representation learning on networks

Abdulkadir Çelikkanat, Fragkiskos D. Malliaros

Network representation learning (NRL) methods have received significant attention over the last years thanks to their success in several graph analysis problems, including node cla…

cs.LG2021★ 1 cited

Maximizing Influence with Graph Neural Networks

George Panagopoulos, Nikolaos Tziortziotis, Michalis Vazirgiannis +1

Finding the seed set that maximizes the influence spread over a network is a well-known NP-hard problem. Though a greedy algorithm can provide near-optimal solutions, the subproble…

cs.LG2020

NodeSig: Binary Node Embeddings via Random Walk Diffusion

Abdulkadir Çelikkanat, Fragkiskos D. Malliaros, Apostolos N. Papadopoulos

Graph Representation Learning (GRL) has become a key paradigm in network analysis, with a plethora of interdisciplinary applications. As the scale of networks increases, most of th…

cs.LG2018★ 4 cited

TNE: A Latent Model for Representation Learning on Networks

Abdulkadir Çelikkanat, Fragkiskos D. Malliaros

Network representation learning (NRL) methods aim to map each vertex into a low dimensional space by preserving the local and global structure of a given network, and in recent yea…

cs.LG2018★ 78 cited

Scattering Networks for Hybrid Representation Learning

Edouard Oyallon, Sergey Zagoruyko, Gabriel Huang +4

Scattering networks are a class of designed Convolutional Neural Networks (CNNs) with fixed weights. We argue they can serve as generic representations for modelling images. In par…

cs.LG2016★ 42 cited

Minding the Gaps for Block Frank-Wolfe Optimization of Structured SVMs

Anton Osokin, Jean-Baptiste Alayrac, Isabella Lukasewitz +2

In this paper, we propose several improvements on the block-coordinate Frank-Wolfe (BCFW) algorithm from Lacoste-Julien et al. (2013) recently used to optimize the structured suppo…

cs.LG2013★ 16 cited

B-tests: Low Variance Kernel Two-Sample Tests

Wojciech Zaremba, Arthur Gretton, Matthew Blaschko

A family of maximum mean discrepancy (MMD) kernel two-sample tests is introduced. Members of the test family are called Block-tests or B-tests, since the test statistic is an avera…