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Search All 2021 Events
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Algorithms
Algorithms; Algorithms
Algorithms -> Bandit Algorithms; Reinforcement Learning and Planning
Algorithms -> Bandit Algorithms; Theory
Algorithms -> Classification; Algorithms -> Meta-Learning; Applications
Algorithms -> Classification; Applications -> Computational Biology and Bioinformatics; Applications
Algorithms -> Classification; Deep Learning -> CNN Architectures; Reinforcement Learning and Planning
Algorithms -> Classification; Deep Learning -> Predictive Models; Neuroscience and Cognitive Science
Algorithms -> Clustering; Theory
Algorithms -> Large Scale Learning; Algorithms -> Sparsity and Compressed Sensing; Algorithms
Algorithms -> Large Scale Learning; Optimization -> Convex Optimization; Optimization
Algorithms -> Missing Data; Algorithms
Algorithms -> Online Learning; Optimization
Algorithms, Optimization and Computation Methods
Algorithms -> Regression; Algorithms -> Uncertainty Estimation; Probabilistic Methods; Probabilistic Methods
Algorithms -> Regression; Optimization -> Convex Optimization; Theory -> Learning Theory; Theory
Algorithms -> Regression; Probabilistic Methods; Probabilistic Methods
Algorithms -> Representation Learning; Applications -> Computer Vision; Applications
Algorithms -> Semi-Supervised Learning; Applications -> Computer Vision; Applications
Algorithms -> Semi-Supervised Learning; Deep Learning -> Optimization for Deep Networks; Optimization
Algorithms -> Unsupervised Learning; Applications -> Computational Photography; Deep Learning
Algorithms -> Unsupervised Learning; Applications -> Computer Vision; Deep Learning
Applications
Applications -> Computer Vision; Applications -> Object Recognition; Deep Learning
Applications -> Computer Vision; Deep Learning -> CNN Architectures; Deep Learning -> Deep Autoencoders; Deep Learning
Applications -> Denoising; Applications -> Signal Processing; Deep Learning
Applications -> Denoising; Theory
Data, Challenges, Implementations, and Software
Deep Learning
Deep Learning -> CNN Architectures; Deep Learning
Ethics and Safety
Learning Theory and Statistics
Models and Methods
Neuroscience and Cognitive Science
Neuroscience and Cognitive Science -> Human or Animal Learning; Probabilistic Methods
Optimization
Probabilistic Methods
Reinforcement Learning and Planning
Theory
Results
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Poster
Wed 12:45
Learning Prediction Intervals for Regression: Generalization and Calibration
Haoxian Chen · Ziyi Huang · Henry Lam · Huajie Qian · Haofeng Zhang
Poster
Tue 14:00
Right Decisions from Wrong Predictions: A Mechanism Design Alternative to Individual Calibration
Shengjia Zhao · Stefano Ermon
Poster
Wed 6:00
Collaborative Classification from Noisy Labels
Lucas Maystre · Nagarjuna Kumarappan · Judith Bütepage · Mounia Lalmas
Oral
Thu 15:30
Misspecification in Prediction Problems and Robustness via Improper Learning
Annie Marsden · John Duchi · Gregory Valiant
Poster
Thu 7:30
Variational Autoencoder with Learned Latent Structure
Marissa Connor · Gregory Canal · Christopher Rozell
Poster
Thu 7:30
Learning User Preferences in Non-Stationary Environments
Wasim Huleihel · Soumyabrata Pal · Ofer Shayevitz
Poster
Tue 18:30
Beyond Marginal Uncertainty: How Accurately can Bayesian Regression Models Estimate Posterior Predictive Correlations?
Chaoqi Wang · Shengyang Sun · Roger Grosse
Poster
Wed 6:00
Predictive Complexity Priors
Eric Nalisnick · Jonathan Gordon · Jose Miguel Hernandez-Lobato
Poster
Tue 14:00
Misspecification in Prediction Problems and Robustness via Improper Learning
Annie Marsden · John Duchi · Gregory Valiant
Poster
Tue 18:30
Predictive Power of Nearest Neighbors Algorithm under Random Perturbation
Yue Xing · Qifan Song · Guang Cheng
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