no code implementations • 22 Feb 2024 • Md Sanzeed Anwar, Grant Schoenebeck, Paramveer S. Dhillon
However, because of this assumption of a tradeoff between these two effects, prior work cannot develop a more nuanced view of how recommendation systems may independently impact homogenization and filter bubble effects.
no code implementations • 21 Feb 2024 • Shengwei Xu, Yichi Zhang, Paul Resnick, Grant Schoenebeck
However, different metrics lead to divergent and even contradictory results in various contexts.
no code implementations • 18 Oct 2021 • Shih-Tang Su, Vijay G. Subramanian, Grant Schoenebeck
The non-determined experiments (signals) in the multi-phase trial are to be chosen by the sender in order to persuade the receiver best.
1 code implementation • 2 Jun 2021 • Paul Resnick, Yuqing Kong, Grant Schoenebeck, Tim Weninger
We refer to such tasks as survey settings because the ground truth is defined through a survey of one or more human raters.
no code implementations • 30 Sep 2020 • Grant Schoenebeck, Fang-Yi Yu
2) We show how to turn a soft-predictor of an agent's signals (given the other agents' signals) into a mechanism.
no code implementations • 19 Nov 2019 • Wei Chen, Binghui Peng, Grant Schoenebeck, Biaoshuai Tao
On the other side, we prove that in any submodular cascade, the adaptive greedy algorithm always outputs a $(1-1/e)$-approximation to the expected number of adoptions in the optimal non-adaptive seed choice.
Social and Information Networks
no code implementations • 24 Feb 2018 • Yuqing Kong, Grant Schoenebeck
In co-training/multiview learning, the goal is to aggregate two views of data into a prediction for a latent label.
1 code implementation • ICLR 2018 • Xingjun Ma, Bo Li, Yisen Wang, Sarah M. Erfani, Sudanthi Wijewickrema, Grant Schoenebeck, Dawn Song, Michael E. Houle, James Bailey
Deep Neural Networks (DNNs) have recently been shown to be vulnerable against adversarial examples, which are carefully crafted instances that can mislead DNNs to make errors during prediction.