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06/02/2023
Mixture Proportion Estimation Beyond Irreducibility
The task of mixture proportion estimation (MPE) is to estimate the weigh...
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05/31/2023
Label Embedding by Johnson-Lindenstrauss Matrices
We present a simple and scalable framework for extreme multiclass classi...
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03/04/2022
Learning from Label Proportions by Learning with Label Noise
Learning from label proportions (LLP) is a weakly supervised classificat...
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11/10/2020
Supervised PCA: A Multiobjective Approach
Methods for supervised principal component analysis (SPCA) aim to incorp...
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06/12/2020
Consistent Estimation of Identifiable Nonparametric Mixture Models from Grouped Observations
Recent research has established sufficient conditions for finite mixture...
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06/12/2020
Learning from Label Proportions: A Mutual Contamination Framework
Learning from label proportions (LLP) is a weakly supervised setting for...
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05/28/2020
Calibrated Surrogate Losses for Adversarially Robust Classification
Adversarially robust classification seeks a classifier that is insensiti...
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10/10/2019
Learning from Multiple Corrupted Sources, with Application to Learning from Label Proportions
We study binary classification in the setting where the learner is prese...
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09/23/2019
PAC Reinforcement Learning without Real-World Feedback
This work studies reinforcement learning in the Sim-to-Real setting, in ...
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05/24/2019
A Generalization Error Bound for Multi-class Domain Generalization
Domain generalization is the problem of assigning labels to an unlabeled...
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11/30/2018
Local inversion-free estimation of spatial Gaussian processes
Maximizing the likelihood has been widely used for estimating the unknow...
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10/17/2018
Simple Regret Minimization for Contextual Bandits
There are two variants of the classical multi-armed bandit (MAB) problem...
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10/03/2018
A Generalized Neyman-Pearson Criterion for Optimal Domain Adaptation
In the problem domain adaptation for binary classification, the learner ...
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11/21/2017
Domain Generalization by Marginal Transfer Learning
Domain generalization is the problem of assigning class labels to an unl...
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10/06/2017
Dictionary-Free MRI PERK: Parameter Estimation via Regression with Kernels
This paper introduces a fast, general method for dictionary-free paramet...
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09/30/2017
Decontamination of Mutual Contamination Models
Many machine learning problems can be characterized by mutual contaminat...
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05/24/2017
Consistent Kernel Density Estimation with Non-Vanishing Bandwidth
Consistency of the kernel density estimator requires that the kernel ban...
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05/24/2017
Nonparametric Preference Completion
We consider the task of collaborative preference completion: given a poo...
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05/24/2017
Multi-Task Learning for Contextual Bandits
Contextual bandits are a form of multi-armed bandit in which the agent h...
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01/05/2017
Adaptive Questionnaires for Direct Identification of Optimal Product Design
We consider the problem of identifying the most profitable product desig...
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03/08/2016
Mixture Proportion Estimation via Kernel Embedding of Distributions
Mixture proportion estimation (MPE) is the problem of estimating the wei...
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02/19/2016
A Mutual Contamination Analysis of Mixed Membership and Partial Label Models
Many machine learning problems can be characterized by mutual contaminat...
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01/15/2016
On the consistency of inversion-free parameter estimation for Gaussian random fields
Gaussian random fields are a powerful tool for modeling environmental pr...
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06/03/2015
Optimal change point detection in Gaussian processes
We study the problem of detecting a change in the mean of one-dimensiona...
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06/21/2013
Class Proportion Estimation with Application to Multiclass Anomaly Rejection
This work addresses two classification problems that fall under the head...
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03/05/2013
Classification with Asymmetric Label Noise: Consistency and Maximal Denoising
In many real-world classification problems, the labels of training examp...
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02/14/2012
Active Diagnosis via AUC Maximization: An Efficient Approach for Multiple Fault Identification in Large Scale, Noisy Networks
The problem of active diagnosis arises in several applications such as d...
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09/14/2010
Calibrated Surrogate Losses for Classification with Label-Dependent Costs
We present surrogate regret bounds for arbitrary surrogate losses in the...
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11/24/2009