conftrace_

distribution learning

75 papers

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Co-occurring keywords

sample complexity (1169) generative adversarial network (1944) differential privacy (1016) discrete distribution (49) probability distribution (265) learning theory (519) wasserstein distance (417) generative model (2892) loss function (462) total variation distance (52)

Papers

SURF: A Simple, Universal, Robust, Fast Distribution Learning Algorithm NIPS 2020
Lower Bounds for Learning Distributions under Communication Constraints via Fisher Information JMLR 2020
Optimal Robust Learning of Discrete Distributions from Batches ICML 2020
Learning Structured Distributions From Untrusted Batches: Faster and Simpler NIPS 2020
Private Hypothesis Selection NIPS 2019
Toward a Characterization of Loss Functions for Distribution Learning NIPS 2019
Inference under Information Constraints: Lower Bounds from Chi-Square Contraction COLT 2019
Learning to Sample Hard Instances for Graph Algorithms ACML 2019
Distribution Learning of a Random Spatial Field with a Location-Unaware Mobile Sensor NIPS 2019
Two Generator Game: Learning to Sample via Linear Goodness-of-Fit Test NIPS 2019
Learning Distributions Generated by One-Layer ReLU Networks NIPS 2019
How Large Are Lions? Inducing Distributions over Quantitative Attributes ACL 2019
Communication-Constrained Inference and the Role of Shared Randomness ICML 2019
Nearly tight sample complexity bounds for learning mixtures of Gaussians via sample compression schemes NIPS 2018
Text Emotion Distribution Learning via Multi-Task Convolutional Neural Network IJCAI 2018
Mean-Variance Loss for Deep Age Estimation From a Face CVPR 2018
Learning Populations of Parameters NIPS 2017
Predicting with Distributions COLT 2017
Communication-Efficient Distributed Learning of Discrete Distributions NIPS 2017
Optimal Learning via the Fourier Transform for Sums of Independent Integer Random Variables COLT 2016
The Hedge Algorithm on a Continuum ICML 2015
On Learning Distributions from their Samples COLT 2015
Differentially Private Learning of Structured Discrete Distributions NIPS 2015
Tight Bounds on Profile Redundancy and Distinguishability NIPS 2012
Learning from Distributions via Support Measure Machines NIPS 2012