1.9k citations · 16k across the 151 of their papers we have counts for
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GCN-WP -- Semi-Supervised Graph Convolutional Networks for Win Prediction in Esports
Alexander J. Bisberg, Emilio Ferrara
Win prediction is crucial to understanding skill modeling, teamwork and matchmaking in esports. In this paper we propose GCN-WP, a semi-supervised win prediction model for esports…
Zero-shot meta-learning for small-scale data from human subjects
Julie Jiang, Kristina Lerman, Emilio Ferrara
While developments in machine learning led to impressive performance gains on big data, many human subjects data are, in actuality, small and sparsely labeled. Existing methods app…
FairFed: Enabling Group Fairness in Federated Learning
Yahya H. Ezzeldin, Shen Yan, Chaoyang He +2
Training ML models which are fair across different demographic groups is of critical importance due to the increased integration of ML in crucial decision-making scenarios such as…
Graph Signal Recovery Using Restricted Boltzmann Machines
Ankith Mohan, Aiichiro Nakano, Emilio Ferrara
We propose a model-agnostic pipeline to recover graph signals from an expert system by exploiting the content addressable memory property of restricted Boltzmann machine and the re…
Detecting multi-timescale consumption patterns from receipt data: A non-negative tensor factorization approach
Akira Matsui, Teruyoshi Kobayashi, Daisuke Moriwaki +1
Understanding consumer behavior is an important task, not only for developing marketing strategies but also for the management of economic policies. Detecting consumption patterns,…
Learning Behavioral Representations from Wearable Sensors
Nazgol Tavabi, Homa Hosseinmardi, Jennifer L. Villatte +4
Continuous collection of physiological data from wearable sensors enables temporal characterization of individual behaviors. Understanding the relation between an individual's beha…