Expo
Getting Started
Schedule
Tutorials
Invited Talks
Papers
Awards
Workshops
Town Hall
Socials
Login
firstbacksecondback
Search All 2021 Events
Filter by Keyword:
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
9 Results
<<
<
Page 1 of 1
>>
>
Poster
Thu 7:30
A Stein Goodness-of-test for Exponential Random Graph Models
Wenkai Xu · Gesine Reinert
Poster
Tue 18:30
Entropy Partial Transport with Tree Metrics: Theory and Practice
Tam Le · Truyen Nguyen
Poster
Tue 18:30
Graph Gamma Process Linear Dynamical Systems
Rahi Kalantari · Mingyuan Zhou
Poster
Tue 18:30
GANs with Conditional Independence Graphs: On Subadditivity of Probability Divergences
Mucong Ding · Constantinos Daskalakis · Soheil Feizi
Poster
Tue 18:30
Flow-based Alignment Approaches for Probability Measures in Different Spaces
Tam Le · Nhat Ho · Makoto Yamada
Poster
Tue 14:00
Minimax Optimal Regression over Sobolev Spaces via Laplacian Regularization on Neighborhood Graphs
Alden Green · Sivaraman Balakrishnan · Ryan Tibshirani
Poster
Thu 7:30
Causal Inference under Networked Interference and Intervention Policy Enhancement
Yunpu Ma · Volker Tresp
Poster
Thu 7:30
Generalized Spectral Clustering via Gromov-Wasserstein Learning
Samir Chowdhury · Tom Needham
Poster
Wed 12:45
Differentially Private Analysis on Graph Streams
Jalaj Upadhyay · Sarvagya Upadhyay · Raman Arora
AISTATS uses cookies to remember that you are logged in. By using our websites, you agree to the placement of these cookies.
Our Privacy Policy »
Accept Cookies