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icml_category_dict.py
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icml_category_dict.py
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category_dict_icml15 = {
"Bandit Learning" : [["Bandits"]],
"Bayesian Nonparametrics" : [["Baysian Nonparametrics"]],
"Bayesian Optimization" : [["Optimization"], ["Baysian Optimization"]],
"Causality" : [["Causality"]],
"Clustering" : [["Clustering"]],
"Computational Advertising And Social Science" : [["Computational Advertising", "Social Science"]],
"Deep Learning" : [["Deep Learning"]],
"Deep Learning And Vision" : [["Deep Learning", "Computer Vision"]],
"Deep Learning Computations" : [["Deep Learning"]],
"Distributed Optimization" : [["Optimization"], ["Distributed Optimization"]],
"Feature Selection" : [["Feature Selection"]],
"Gaussian Processes" : [["Gaussian Processes"]],
"Hashing" : [["Hashing"]],
"Kernel Methods" : [["Kernel Methods"]],
"Large Scale Learning" : [["Large Scale Learning"]],
"Learning Theory" : [["Learning Theory"]],
"Manifold Learning" : [["Manifold Learning"]],
"Matrix Factorization" : [["Matrix Factorization"]],
"Monte Carlo Methods" : [["Monte Carlo Methods"]],
"Natural Language Processing" : [["Natural Language Processing"]],
"Networks And Graphs" : [["Networks", "Graph Analysis"]],
"Online Learning" : [["Online Learning"]],
"Optimization" : [["Optimization"]],
"Privacy" : [["Privacy"]],
"Probabilistic Models" : [["Probabilistic Models"]],
"Ranking Learning" : [["Ranking Learning"]],
"Reinforcement Learning" : [["Reinforcement Learning"]],
"Sparse Optimization" : [["Optimization"], ["Sparse Optimization"]],
"Sparsity" : [["Sparsity"]],
"Structured Prediction" : [["Structured Prediction"]],
"Submodularity" : [["Submodularity"]],
"Supervised Learning" : [["Supervised Learning"]],
"Time Series Analysis" : [["Time-Series"]],
"Topic Models" : [["Probabilistic Models"]],
"Transfer Learning" : [["Transfer Learning"]],
"Unsupervised Learning" : [["Unsupervised Learning"]],
"Variational Inference" : [["Approximate Inference"]],
"Vision" : [["Computer Vision"]]
}
category_dict_icml16 = {
"Applications and Time-Series Analysis" : [["Applications", "Time-Series"]],
"Approximate Inference" : [["Approximate Inference"]],
"Bandit Problems" : [["Bandits"]],
"Bayesian Nonparametric Methods" : [["Baysian Nonparametrics"]],
"Causal Inference" : [["Causal Inference"]],
"Clustering" : [["Clustering"]],
"Crowdsourcing and Interactive Learning" : [["Crowdsourcing", "Interactive Learning"]],
"Dimensionality Reduction / Private Learning" : [["Dimensionality Reduction", "Privacy"]],
"Feature Selection and Dimensionality Reduction" : [["Feature Selection", "Dimensionality Reduction"]],
"Gaussian Processes" : [["Gaussian Processes"]],
"Graph Analysis/ Spectral Methods" : [["Graph Analysis", "Spectral Methods"]],
"Graphical Models" : [["Probabilistic Models"]],
"Kernel Methods" : [["Kernel Methods"]],
"Large Scale Learning and Big Data" : [["Large Scale Learning"]],
"Learning Theory" : [["Learning Theory"]],
"Machine Learning Applications" : [["Applications"]],
"Matrix Factorization / Neuroscience Applications" : [["Matrix Factorization", "Neuroscience Applications"]],
"Matrix Factorization and Related Topics" : [["Matrix Factorization"]],
"Metric and Manifold Learning / Kernel Methods" : [["Metric Learning", "Manifold Learning", "Kernel Methods"]],
"Monte Carlo Methods" : [["Monte Carlo Methods"]],
"Multi-label, multi-task, and neural networks" : [["Multi-Label Learning", "Multi-Task Learning"], ["Deep Learning"]],
"Neural Networks and Deep Learning" : [["Deep Learning"]],
"Neural Networks and Deep Learning I" : [["Deep Learning"]],
"Neural Networks and Deep Learning II" : [["Deep Learning"]],
"Neural Networks and Deep Learning II (Computer Vision)" : [["Deep Learning"], ["Computer Vision"]],
"Online Learning" : [["Online Learning"]],
"Optimization" : [["Optimization"]],
"Optimization (Combinatorial)" : [["Optimization"], ["Combinatorial Optimization"]],
"Optimization (Continuous)" : [["Optimization"], ["Continuous Optimization"]],
"Optimization / Online Learning" : [["Optimization", "Online Learning"]],
"Privacy, Anonymity, and Security" : [["Privacy"]],
"Ranking and Preference Learning" : [["Ranking Learning", "Preference Learning"]],
"Reinforcement Learning" : [["Reinforcement Learning"]],
"Sampling / Kernel Methods" : [["Sampling", "Kernel Methods"]],
"Sparsity and Compressed Sensing" : [["Sparsity", "Compressed Sensing"]],
"Statistical Learning Theory" : [["Statistical Learning Theory"]],
"Structured Prediction / Monte Carlo Methods" : [["Structured Prediction", "Monte Carlo Methods"]],
"Supervised Learning" : [["Supervised Learning"]],
"Transfer Learning / Learning Theory" : [["Transfer Learning", "Learning Theory"]],
"Unsupervised Learning / Applications" : [["Unsupervised Learning", "Applications"]],
"Unsupervised Learning / Representation Learning" : [["Unsupervised Learning", "Representation Learning"]]
}
category_dict_icml17 = {
"Active Learning" : [["Active Learning"]],
"Applications" : [["Applications"]],
"Bayesian Nonparametrics" : [["Baysian Nonparametrics"]],
"Bayesian Optimization" : [["Optimization"], ["Baysian Optimization"]],
"Causal Inference" : [["Causal Inference"]],
"Clustering" : [["Clustering"]],
"Combinatorial Optimization" : [["Optimization"], ["Combinatorial Optimization"]],
"Continuous Control" : [["Continuous Control"]],
"Continuous Optimization" : [["Optimization"], ["Continuous Optimization"]],
"Deep Generative Models" : [["Deep Learning"], ["Deep Generative Models"]],
"Deep Learning" : [["Deep Learning"]],
"Deep Learning : Analysis": [["Deep Learning"]],
"Deep Learning : Backprop": [["Deep Learning"]],
"Deep Learning : Fisher Approximations": [["Deep Learning"]],
"Deep Learning : Hardware": [["Deep Learning"]],
"Deep Learning : Invariances": [["Deep Learning"]],
"Deep Learning : Learning To Learn": [["Deep Learning"]],
"Deep Learning : Metalearning": [["Deep Learning"]],
"Deep Learning : Probabilistic": [["Deep Learning"], ["Probabilistic Models"]],
"Deep Learning Theory" : [["Deep Learning"], ["Deep Learning Theory"]],
"Deep Reinforcement Learning" : [["Deep Reinforcement Learning"], ["Reinforcement Learning"]],
"Distributed Optimization" : [["Optimization"], ["Distributed Optimization"]],
"Ensemble Methods" : [["Ensemble Methods"]],
"Game Theory And Multiagents" : [["Game Theory", "Multi-Agent Learning"]],
"Gaussian Processes" : [["Gaussian Processes"]],
"Healthcare" : [["Healthcare"]],
"High Dimensional Estimation" : [["High Dimensional Estimation"]],
"Infomation Theory" : [["Information Theory"]],
"Kernel Methods" : [["Kernel Methods"]],
"Language" : [["Natural Language Processing"]],
"Large Scale Learning" : [["Large Scale Learning"]],
"Latent Feature Models" : [["Latent Feature Models"]],
"Learning Theory" : [["Learning Theory"]],
"Matrix Factorization" : [["Matrix Factorization"]],
"Metric Learning" : [["Metric Learning"]],
"Ml And Programming" : [["Ml And Programming"]],
"Monte Carlo Methods" : [["Monte Carlo Methods"]],
"Networks And Relational Learning" : [["Networks", "Relational Learning"]],
"Online Learning" : [["Online Learning"]],
"Privacy And Security" : [["Privacy"]],
"Probabilistic Inference" : [["Approximate Inference"]],
"Probabilistic Learning" : [["Probabilistic Models"]],
"Ranking And Preferences" : [["Ranking Learning", "Preference Learning"]],
"Recurrent Neural Networks" : [["Recurrent Neural Networks"]],
"Reinforcement Learning" : [["Reinforcement Learning"]],
"Robust Estimation" : [["Robustness"]],
"Semisupervised And Curriculum Learning" : [
["Semi-Supervised Learning", "Curriculum Learning"]
],
"Sparsity" : [["Sparsity"]],
"Spectral Methods" : [["Spectral Methods"]],
"Structured Prediction" : [["Structured Prediction"]],
"Supervised Learning" : [["Supervised Learning"]],
"Time Series" : [["Time-Series"]],
"Transfer And Multitask Learning": [["Transfer Learning", "Multi-Task Learning"]]
}
category_dict_icml18 = {
"Active Learning" : [["Active Learning"]],
"Approximate Inference" : [["Approximate Inference"]],
"Causal Inference" : [["Causal Inference"]],
"Clustering" : [["Clustering"]],
"Computer Vision" : [["Computer Vision"]],
"Deep Learning (Adversarial)" : [["Deep Learning", "Adversarial"]],
"Deep Learning (Bayesian)" : [["Deep Learning", "Baysian Deep Learning"]],
"Deep Learning (Neural Network Architectures)" : [["Deep Learning", "Architectures"]],
"Deep Learning (Theory)" : [["Deep Learning", "Deep Learning Theory"]],
"Dimensionality Reduction" : [["Dimensionality Reduction"]],
"Feature Selection" : [["Feature Selection"]],
"Gaussian Processes" : [["Gaussian Processes"]],
"Generative Models" : [["Generative Models"]],
"Graphical Models" : [["Probabilistic Models"]],
"Kernel Methods" : [["Kernel Methods"]],
"Large Scale Learning and Big Data" : [["Large Scale Learning"]],
"Matrix Factorization" : [["Matrix Factorization"]],
"Monte Carlo Methods" : [["Monte Carlo Methods"]],
"Multi-Agent Learning" : [["Multi-Agent Learning"]],
"Natural Language and Speech Processing" : [["Natural Language Processing", "Speech Processing"]],
"Networks and Relational Learning" : [["Networks", "Relational Learning"]],
"Online Learning" : [["Online Learning"]],
"Optimization (Bayesian)" : [["Optimization"], ["Baysian Optimization"]],
"Optimization (Combinatorial)" : [["Optimization"], ["Combinatorial Optimization"]],
"Optimization (Convex)" : [["Optimization"], ["Convex Optimization"]],
"Optimization (Non-convex)" : [["Optimization"], ["Non-Convex Optimization"]],
"Other Applications" : [["Applications"]],
"Other Models and Methods" : [["Other Models and Methods"]],
"Parallel and Distributed Learning" : [["Optimization"], ["Distributed Optimization"]],
"Privacy, Anonymity, and Security" : [["Privacy"]],
"Ranking and Preference Learning" : [["Ranking Learning", "Preference Learning"]],
"Reinforcement Learning" : [["Reinforcement Learning"]],
"Representation Learning" : [["Representation Learning"]],
"Society Impacts of Machine Learning" : [["Society Impacts of Machine Learning"]],
"Sparsity and Compressed Sensing" : [["Sparsity", "Compressed Sensing"]],
"Spectral Methods" : [["Spectral Methods"]],
"Statistical Learning Theory" : [["Statistical Learning Theory"]],
"Structured Prediction" : [["Structured Prediction"]],
"Supervised Learning" : [["Supervised Learning"]],
"Time-Series Analysis" : [["Time-Series"]],
"Transfer and Multi-Task Learning" : [["Transfer Learning", "Multi-Task Learning"]],
"Unsupervised Learning" : [["Unsupervised Learning"]]
}
category_dict_icml19 = {
"Active Learning" : [["Active Learning"]],
"Adversarial Examples" : [["Adversarial"]],
"Applications" : [["Applications"]],
"Applications: Computer Vision" : [["Applications"], ["Computer Vision"]],
"Applications: Natural Language Processing" : [["Applications"], ["Natural Language Processing"]],
"Approximate Inference" : [["Approximate Inference"]],
"Bandits and Multiagent Learning" : [["Bandits", "Multi-Agent Learning"]],
"Bayesian Deep Learning" : [["Deep Learning"], ["Baysian Deep Learning"]],
"Bayesian Methods" : [["Baysian Methods"]],
"Bayesian Non-parametrics" : [["Baysian Nonparametrics"]],
"Causality" : [["Causality"]],
"Combinatorial Optimization" : [["Combinatorial Optimization"]],
"Convex Optimization" : [["Optimization"], ["Convex Optimization"]],
"Deep Generative Models" : [["Deep Learning"], ["Deep Generative Models"]],
"Deep Learning" : [["Deep Learning"]],
"Deep Learning Algorithms" : [["Deep Learning"]],
"Deep Learning Architectures" : [["Deep Learning"], ["Architectures"]],
"Deep Learning Optimization" : [["Deep Learning"], ["Optimization"]],
"Deep Learning Theory" : [["Deep Learning"], ["Deep Learning Theory"]],
"Deep RL" : [["Deep Learning"], ["Deep Reinforcement Learning"]],
"Deep Sequence Models" : [["Deep Learning"]],
"Fairness" : [["Fairness"]],
"Gaussian Processes" : [["Gaussian Processes"]],
"General ML" : [["General ML"]],
"Generative Adversarial Networks" : [["Generative Models"]],
"Generative Models" : [["Generative Models"]],
"Information Theory and Estimation" : [["Information Theory", "Estimation"]],
"Interpretability" : [["Interpretability"]],
"Kernel Methods" : [["Kernel Methods"]],
"Large Scale Learning and Systems" : [["Large Scale Learning"]],
"Learning Theory" : [["Learning Theory"]],
"Learning Theory: Games" : [["Learning Theory", "Games"]],
"Monte Carlo Methods" : [["Monte Carlo Methods"]],
"Networks and Relational Learning" : [["Networks", "Relational Learning"]],
"Non-convex Optimization" : [["Optimization"], ["Non-Convex Optimization"]],
"Online Learning" : [["Online Learning"]],
"Optimization" : [["Optimization"]],
"Optimization and Graphical Models" : [["Optimization", "Probabilistic Models"]],
"Optimization: Convex and Non-convex" : [["Optimization"], ["Convex Optimization", "Non-Convex Optimization"]],
"Privacy" : [["Privacy"]],
"Privacy and Fairness" : [["Privacy", "Fairness"]],
"Probabilistic Inference" : [["Probabilistic Inference"]],
"Ranking and Preference Learning" : [["Ranking Learning", "Preference Learning"]],
"Reinforcement Learning" : [["Reinforcement Learning"]],
"Reinforcement Learning Theory" : [["Reinforcement Learning"]],
"Reinforcement Learning and Bandits" : [["Reinforcement Learning", "Bandits"]],
"Representation Learning" : [["Representation Learning"]],
"Robust Statistics and Interpretability" : [["Robustness", "Interpretability"]],
"Robust Statistics and Machine Learning" : [["Robustness"]],
"Statistical Learning Theory" : [["Statistical Learning Theory"]],
"Supervised Learning" : [["Supervised Learning"]],
"Supervised and Transfer Learning" : [["Supervised Learning", "Transfer Learning"]],
"Time Series" : [["Time-Series"]],
"Transfer and Multitask Learning" : [["Transfer Learning", "Multi-Task Learning"]],
"Unsupervised Learning" : [["Unsupervised Learning"]]
}