13 citations · 33 across the 20 of their papers we have counts for
4 papers · 1 filter
Predicting Team Performance with Spatial Temporal Graph Convolutional Networks
Shengnan Hu, Gita Sukthankar
This paper presents a new approach for predicting team performance from the behavioral traces of a set of agents. This spatiotemporal forecasting problem is very relevant to sports…
Leveraging Transformers for StarCraft Macromanagement Prediction
Muhammad Junaid Khan, Shah Hassan, Gita Sukthankar
Inspired by the recent success of transformers in natural language processing and computer vision applications, we introduce a transformer-based neural architecture for two key Sta…
Leveraging the Variance of Return Sequences for Exploration Policy
Zerong Xi, Gita Sukthankar
This paper introduces a method for constructing an upper bound for exploration policy using either the weighted variance of return sequences or the weighted temporal difference (TD…
An Active Learning Approach for Jointly Estimating Worker Performance and Annotation Reliability with Crowdsourced Data
Liyue Zhao, Yu Zhang, Gita Sukthankar
Crowdsourcing platforms offer a practical solution to the problem of affordably annotating large datasets for training supervised classifiers. Unfortunately, poor worker performanc…