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Found 9 papers, 0 papers with code
Fairness with Overlapping Groups; a Probabilistic Perspective
In algorithmically fair prediction problems, a standard goal is to ensure the equality of fairness metrics across multiple overlapping groups simultaneously.
Multiclass Performance Metric Elicitation
Metric Elicitation is a principled framework for selecting the performance metric that best reflects implicit user preferences.
Faster Distributed Synchronous SGD with Weak Synchronization
Distributed training of deep learning is widely conducted with large neural networks and large datasets.
Generalized Correspondence-LDA Models (GC-LDA) for Identifying Functional Regions in the Brain
This paper presents Generalized Correspondence-LDA (GC-LDA), a generalization of the Correspondence-LDA model that allows for variable spatial representations to be associated with topics, and increased flexibility in terms of the strength of the correspondence between data types induced by the model.
Examples are not enough, learn to criticize! Criticism for Interpretability
Example-based explanations are widely used in the effort to improve the interpretability of highly complex distributions.
Consistent Multilabel Classification
In particular, we show that for multilabel metrics constructed as instance-, micro- and macro-averages, the population optimal classifier can be decomposed into binary classifiers based on the marginal instance-conditional distribution of each label, with a weak association between labels via the threshold.
On Prior Distributions and Approximate Inference for Structured Variables
In cases where this projection is intractable, we propose a family of parameterized approximations indexed by subsets of the domain.
Sparse Bayesian structure learning with “dependent relevance determination” priors
Classical sparse regression methods, such as the lasso and automatic relevance determination (ARD), model parameters as independent a priori, and therefore do not exploit such dependencies.
Consistent Binary Classification with Generalized Performance Metrics
We consider a fairly large family of performance metrics given by ratios of linear combinations of the four fundamental population quantities.
