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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
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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
Thu 7:30
No-regret Algorithms for Multi-task Bayesian Optimization
Sayak Ray Chowdhury · Aditya Gopalan
Poster
Tue 14:00
An Efficient Algorithm For Generalized Linear Bandit: Online Stochastic Gradient Descent and Thompson Sampling
QIN DING · Cho-Jui Hsieh · James Sharpnack
Poster
Tue 14:00
No-Regret Algorithms for Private Gaussian Process Bandit Optimization
Abhimanyu Dubey
Poster
Thu 7:30
Instance-Wise Minimax-Optimal Algorithms for Logistic Bandits
Marc Abeille · Louis Faury · Clement Calauzenes
Oral
Wed 9:30
Instance-Wise Minimax-Optimal Algorithms for Logistic Bandits
Marc Abeille · Louis Faury · Clement Calauzenes
Poster
Thu 7:30
Explore the Context: Optimal Data Collection for Context-Conditional Dynamics Models
Jan Achterhold · Joerg Stueckler
Poster
Tue 18:30
Corralling Stochastic Bandit Algorithms
Raman Arora · Teodor Vanislavov Marinov · Mehryar Mohri
Poster
Wed 12:45
DebiNet: Debiasing Linear Models with Nonlinear Overparameterized Neural Networks
Shiyun Xu · Zhiqi Bu
Poster
Thu 7:30
Smooth Bandit Optimization: Generalization to Holder Space
Yusha Liu · Yining Wang · Aarti Singh
Poster
Tue 18:30
Parametric Programming Approach for More Powerful and General Lasso Selective Inference
Vo Nguyen Le Duy · Ichiro Takeuchi
Poster
Tue 18:30
A Parameter-Free Algorithm for Misspecified Linear Contextual Bandits
Kei Takemura · Shinji Ito · Daisuke Hatano · Hanna Sumita · Takuro Fukunaga · Naonori Kakimura · Ken-ichi Kawarabayashi
Oral
Wed 8:45
Bandit algorithms: Letting go of logarithmic regret for statistical robustness
Kumar Ashutosh · Jayakrishnan Nair · Anmol Kagrecha · Krishna Jagannathan
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