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Search All 2021 Events
Filter by Keyword:
Algorithms
Algorithms -> Active Learning; Algorithms -> Classification; Algorithms
Algorithms -> Adaptive Data Analysis; Optimization
Algorithms -> Adversarial Learning; Algorithms
Algorithms -> Bandit Algorithms; Algorithms
Algorithms -> Bandit Algorithms; Reinforcement Learning and Planning
Algorithms -> Bandit Algorithms; Reinforcement Learning and Planning -> Reinforcement Learning; Theory
Algorithms -> Boosting and Ensemble Methods; Algorithms -> Model Selection and Structure Learning; Theory
Algorithms -> Boosting and Ensemble Methods; Probabilistic Methods; Probabilistic Methods
Algorithms -> Classification; Algorithms
Algorithms -> Classification; Algorithms -> Meta-Learning; Algorithms -> Multitask and Transfer Learning; Algorithms
Algorithms -> Classification; Applications -> Computational Social Science; Applications
Algorithms -> Classification; Deep Learning; Deep Learning
Algorithms -> Classification; Deep Learning; Deep Learning -> Predictive Models; Deep Learning
Algorithms -> Clustering; Applications -> Hardware and Systems; Applications
Algorithms -> Clustering; Theory
Algorithms -> Collaborative Filtering; Algorithms -> Large Scale Learning; Applications
Algorithms -> Collaborative Filtering; Applications -> Information Retrieval; Applications
Algorithms -> Density Estimation; Deep Learning -> Adversarial Networks; Deep Learning -> Generative Models; Theory
Algorithms -> Few-Shot Learning; Algorithms
Algorithms -> Image Segmentation; Algorithms -> Similarity and Distance Learning; Algorithms
Algorithms -> Image Segmentation; Applications -> Computer Vision; Applications -> Image Segmentation; Applications
Algorithms -> Kernel Methods; Optimization -> Non-Convex Optimization; Theory
Algorithms -> Large Scale Learning; Algorithms
Algorithms -> Large Scale Learning; Algorithms -> Regression; Algorithms -> Sparsity and Compressed Sensing; Algorithms
Algorithms -> Large Scale Learning; Applications -> Natural Language Processing; Deep Learning
Algorithms -> Large Scale Learning; Deep Learning -> Efficient Training Methods; Deep Learning
Algorithms -> Large Scale Learning; Probabilistic Methods
Algorithms -> Meta-Learning; Applications -> Object Recognition; Data, Challenges, Implementations, and Software
Algorithms -> Missing Data; Algorithms
Algorithms -> Missing Data; Algorithms -> Uncertainty Estimation; Probabilistic Methods
Algorithms -> Missing Data; Theory
Algorithms -> Multitask and Transfer Learning; Algorithms
Algorithms -> Multitask and Transfer Learning; Probabilistic Methods
Algorithms -> Online Learning; Theory -> Computational Complexity; Theory
Algorithms; Optimization -> Convex Optimization; Optimization -> Stochastic Optimization; Theory
Algorithms -> Ranking and Preference Learning; Theory
Algorithms -> Regression; Algorithms -> Spectral Methods; Optimization -> Convex Optimization; Theory
Algorithms -> Regression; Applications -> Health; Theory -> Learning Theory; Theory
Algorithms -> Regression; Optimization -> Convex Optimization; Theory -> Learning Theory; Theory
Algorithms -> Regression; Probabilistic Methods; Probabilistic Methods
Algorithms -> Representation Learning; Algorithms -> Sparse Coding and Dimensionality Expansion; Applications
Algorithms -> Representation Learning; Algorithms -> Structured Prediction; Applications
Algorithms -> Representation Learning; Neuroscience and Cognitive Science
Algorithms -> Representation Learning; Neuroscience and Cognitive Science; Neuroscience and Cognitive Science
Algorithms -> Representation Learning; Optimization
Algorithms -> Sparse Coding and Dimensionality Expansion; Applications -> Denoising; Applications
Algorithms -> Sparsity and Compressed Sensing; Applications -> Information Retrieval; Applications
Algorithms -> Sparsity and Compressed Sensing; Optimization; Theory
Algorithms -> Uncertainty Estimation; Applications; Probabilistic Methods
Algorithms -> Unsupervised Learning; Applications
Algorithms -> Unsupervised Learning; Deep Learning
Applications -> Body Pose, Face, and Gesture Analysis; Applications -> Computer Vision; Deep Learning
Applications -> Computational Biology and Bioinformatics; Applications -> Health; Deep Learning
Applications -> Computer Vision; Applications -> Object Detection; Applications
Applications -> Computer Vision; Applications -> Visual Scene Analysis and Interpretation; Deep Learning
Applications -> Computer Vision; Deep Learning
Applications -> Computer Vision; Deep Learning -> Adversarial Networks; Deep Learning
Applications -> Computer Vision; Deep Learning -> Deep Autoencoders; Deep Learning
Applications -> Object Detection; Deep Learning
Applications -> Object Detection; Neuroscience and Cognitive Science
Applications -> Time Series Analysis; Deep Learning
Applications -> Time Series Analysis; Probabilistic Methods; Probabilistic Methods
Data, Challenges, Implementations, and Software
Deep Learning -> Adversarial Networks; Deep Learning
Deep Learning -> Biologically Plausible Deep Networks; Deep Learning
Deep Learning -> Biologically Plausible Deep Networks; Neuroscience and Cognitive Science
Deep Learning -> CNN Architectures; Deep Learning
Deep Learning -> Deep Autoencoders; Deep Learning -> Generative Models; Probabilistic Methods; Probabilistic Methods
Deep Learning; Deep Learning
Deep Learning; Deep Learning -> CNN Architectures; Theory
Deep Learning; Deep Learning -> Predictive Models; Deep Learning
Deep Learning -> Efficient Training Methods; Deep Learning
Deep Learning -> Predictive Models; Deep Learning
Deep Learning -> Recurrent Networks; Theory
Neuroscience and Cognitive Science
Neuroscience and Cognitive Science -> Cognitive Science; Neuroscience and Cognitive Science
Neuroscience and Cognitive Science -> Human or Animal Learning; Probabilistic Methods
Neuroscience and Cognitive Science -> Memory; Optimization -> Combinatorial Optimization; Optimization
Neuroscience and Cognitive Science -> Neural Coding; Neuroscience and Cognitive Science
Neuroscience and Cognitive Science -> Reasoning; Optimization
Optimization -> Convex Optimization; Probabilistic Methods; Theory; Theory
Optimization; Optimization
Probabilistic Methods; Probabilistic Methods
Reinforcement Learning and Planning
Reinforcement Learning and Planning -> Markov Decision Processes; Reinforcement Learning and Planning
Social Aspects of Machine Learning
Theory; Theory
22 Results
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Oral Session
Thu 7:00
Bayesian Methods
Poster
Wed 21:00
Non-Exponentially Weighted Aggregation: Regret Bounds for Unbounded Loss Functions
Pierre Alquier
Poster
Tue 21:00
Oblivious Sketching-based Central Path Method for Linear Programming
Zhao Song · Zheng Yu
Spotlight
Wed 17:20
Non-Exponentially Weighted Aggregation: Regret Bounds for Unbounded Loss Functions
Pierre Alquier
Spotlight
Tue 19:20
Oblivious Sketching-based Central Path Method for Linear Programming
Zhao Song · Zheng Yu
Spotlight
Thu 6:25
Finite mixture models do not reliably learn the number of components
Diana Cai · Trevor Campbell · Tamara Broderick
Poster
Thu 9:00
Finite mixture models do not reliably learn the number of components
Diana Cai · Trevor Campbell · Tamara Broderick
Poster
Thu 9:00
Streaming Bayesian Deep Tensor Factorization
Shikai Fang · Zheng Wang · Zhimeng Pan · Ji Liu · Shandian Zhe
Spotlight
Thu 6:35
Streaming Bayesian Deep Tensor Factorization
Shikai Fang · Zheng Wang · Zhimeng Pan · Ji Liu · Shandian Zhe
Spotlight
Wed 6:40
Provable Robustness of Adversarial Training for Learning Halfspaces with Noise
Difan Zou · Spencer Frei · Quanquan Gu
Poster
Wed 9:00
Provable Robustness of Adversarial Training for Learning Halfspaces with Noise
Difan Zou · Spencer Frei · Quanquan Gu
Poster
Thu 21:00
Bayesian Structural Adaptation for Continual Learning
Abhishek Kumar · Sunabha Chatterjee · Piyush Rai
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