no code implementations • 18 Jan 2023 • Penghang Liu, Rupam Acharyya, Robert E. Tillman, Shunya Kimura, Naoki Masuda, Ahmet Erdem Sarıyüce
For the Venmo network, we investigate the interplay between financial and social relations on three tasks: friendship prediction, vendor identification, and analysis of temporal cycles.
no code implementations • 31 May 2022 • Parisa Hassanzadeh, Robert E. Tillman
Deep generative models, such as Generative Adversarial Networks (GANs), synthesize diverse high-fidelity data samples by estimating the underlying distribution of high dimensional data.
no code implementations • 14 Apr 2020 • Chirag Nagpal, Robert E. Tillman, Prashant Reddy, Manuela Veloso
We consider the problem of aggregating predictions or measurements from a set of human forecasters, models, sensors or other instruments which may be subject to bias or miscalibration and random heteroscedastic noise.
no code implementations • 9 Apr 2020 • Robert E. Tillman, Vamsi K. Potluru, Jiahao Chen, Prashant Reddy, Manuela Veloso
Through experiments with simulated and real world scientific collaboration, transportation and global trade networks, we demonstrate that the proposed heuristics show increased performance with the richness of connection type correlation structure and significantly outperform their baseline heuristics for ordinary networks with a single connection type.
no code implementations • NeurIPS 2009 • Arthur Gretton, Peter Spirtes, Robert E. Tillman
This results in a more computationally efficient approach that is useful for arbitrary distributions even when additive noise models are invertible.
no code implementations • NeurIPS 2008 • David Danks, Clark Glymour, Robert E. Tillman
In many domains, data are distributed among datasets that share only some variables; other recorded variables may occur in only one dataset.