Search Results for author:
Found 8 papers, 2 papers with code
Filter Bubble or Homogenization? Disentangling the Long-Term Effects of Recommendations on User Consumption Patterns
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.
Spot Check Equivalence: an Interpretable Metric for Information Elicitation Mechanisms
However, different metrics lead to divergent and even contradictory results in various contexts.
Bayesian Persuasion in Sequential Trials
The non-determined experiments (signals) in the multi-phase trial are to be chosen by the sender in order to persuade the receiver best.
Survey Equivalence: A Procedure for Measuring Classifier Accuracy Against Human Labels
We refer to such tasks as survey settings because the ground truth is defined through a survey of one or more human raters.
Learning and Strongly Truthful Multi-Task Peer Prediction: A Variational Approach
2) We show how to turn a soft-predictor of an agent's signals (given the other agents' signals) into a mechanism.
Adaptive Greedy versus Non-adaptive Greedy for Influence Maximization
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
Water from Two Rocks: Maximizing the Mutual Information
In co-training/multiview learning, the goal is to aggregate two views of data into a prediction for a latent label.
Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality
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.
