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Finite-sample analysis of interpolating linear classifiers in the overparameterized regime
We prove bounds on the population risk of the maximum margin algorithm for two-class
linear classification. For linearly separable training data, the maximum margin algorithm has …
linear classification. For linearly separable training data, the maximum margin algorithm has …
Equalized odds postprocessing under imperfect group information
Most approaches aiming to ensure a model's fairness with respect to a protected attribute
(such as gender or race) assume to know the true value of the attribute for every data point …
(such as gender or race) assume to know the true value of the attribute for every data point …
Strength from weakness: Fast learning using weak supervision
We study generalization properties of weakly supervised learning, that is, learning where
only a few" strong" labels (the actual target for prediction) are present but many more" weak" …
only a few" strong" labels (the actual target for prediction) are present but many more" weak" …
Adversarial crowdsourcing through robust rank-one matrix completion
We consider the problem of reconstructing a rank-one matrix from a revealed subset of its
entries when some of the revealed entries are corrupted with perturbations that are unknown …
entries when some of the revealed entries are corrupted with perturbations that are unknown …
Crowdsourced label aggregation using bilayer collaborative clustering
With online crowdsourcing platforms, labels can be acquired at relatively low costs from
massive nonexpert workers. To improve the quality of labels obtained from these imperfect …
massive nonexpert workers. To improve the quality of labels obtained from these imperfect …
Eliciting confidence for improving crowdsourced audio annotations
In this work we explore confidence elicitation methods for crowdsourcing" soft" labels, eg,
probability estimates, to reduce the annotation costs for domains with ambiguous data …
probability estimates, to reduce the annotation costs for domains with ambiguous data …
CONAN: A framework for detecting and handling collusion in crowdsourcing
In contrast to the traditional view that individuals should work independently to realize the
crowd wisdom, crowdsourcing workers often collaborate with each other in task processing …
crowd wisdom, crowdsourcing workers often collaborate with each other in task processing …
Ranking and combining latent structured predictive scores without labeled data
Combining multiple predictors obtained from distributed data sources to an accurate meta-
learner is promising to achieve enhanced performance in lots of prediction problems. As the …
learner is promising to achieve enhanced performance in lots of prediction problems. As the …
Online algorithm for unsupervised sensor selection
In many security and healthcare systems, the detection and diagnosis systems use a
sequence of sensors/tests. Each test outputs a prediction of the latent state and carries an …
sequence of sensors/tests. Each test outputs a prediction of the latent state and carries an …
Robust Decision Aggregation with Adversarial Experts
We consider a binary decision aggregation problem in the presence of both truthful and
adversarial experts. The truthful experts will report their private signals truthfully with proper …
adversarial experts. The truthful experts will report their private signals truthfully with proper …