Getting Started
Schedule
Invited Talks
Papers
ToT Award
Sponsors
Organizers
Help
Code of Conduct
Bookmarking / Agenda
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
Results
<<
<
Page 1 of 1
>>
>
Poster
Thu 7:30
Explicit Regularization of Stochastic Gradient Methods through Duality
Anant Raj · Francis Bach
Poster
Thu 7:30
Explore the Context: Optimal Data Collection for Context-Conditional Dynamics Models
Jan Achterhold · Joerg Stueckler
Poster
Wed 6:00
Direct-Search for a Class of Stochastic Min-Max Problems
Sotiris Anagnostidis · Aurelien Lucchi · Youssef Diouane
Poster
Wed 12:45
Local Stochastic Gradient Descent Ascent: Convergence Analysis and Communication Efficiency
yuyang deng · Mehrdad Mahdavi
Poster
Wed 12:45
Follow Your Star: New Frameworks for Online Stochastic Matching with Known and Unknown Patience
Nathaniel Grammel · Brian Brubach · Wei Ma · Aravind Srinivasan
Poster
Wed 6:00
Kernel Distributionally Robust Optimization: Generalized Duality Theorem and Stochastic Approximation
Jia-Jie Zhu · Wittawat Jitkrittum · Moritz Diehl · Bernhard Schölkopf
Poster
Tue 18:30
vqSGD: Vector Quantized Stochastic Gradient Descent
Venkata Gandikota · Daniel Kane · Raj Kumar Maity · Arya Mazumdar
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