Keyphrases
PAC-Bayesian Bounds
66%
PAC-Bayesian Analysis
66%
Regret
66%
Regret Bounds
50%
Quasi-convex
33%
Ranker
33%
Statistical Learning Theory
33%
Popper
33%
Karl Popper
33%
Falsifiability
33%
PAC-Bayesian Inequalities
33%
Majority Vote
33%
Easy Data
33%
Effective Range
33%
Contextual Bandits
33%
UCB1
33%
EXP3
33%
Adversarial Bandit
33%
Random Forest
33%
Adversarial multi-armed Bandit
33%
Stochastic Bandits
33%
Adaptation
33%
PAC-Bayesian
30%
Second-order Difference
25%
Pseudo-regret
25%
Tight
19%
Hypothesis Space
16%
Learning from Examples
16%
Number of States
16%
Stochastic Optimality
16%
Online Mirror Descent
16%
Expert Advice
16%
Entropy Regularizer
16%
Gap Measurement
16%
Stochastic Regime
16%
Additive Factors
16%
Online Shortest Path
16%
Thompson Sampling
16%
Exploration-exploitation
16%
Easiness
16%
Adversarial Loss
16%
Impossibility Results
16%
Computer Science
Electronic Learning
66%
Learning Algorithm
50%
Fundamental Problem
33%
Randomized Algorithm
33%
Problem Instance
33%
Statistical Learning Theory
33%
Cartesian Product
33%
Side Information
33%
Parametrization
33%
Clustering Graph
33%
Online Evaluation
33%
Reducing Error
33%
Optimal Algorithm
33%
Implicit User Feedback
33%
Markov Decision Process
33%
Process Problem
16%
Individual Classifier
16%
Gibbs Classifier
16%
Efficient Algorithm
16%
Shortest Path Problem
16%
Mathematics
Stochastics
100%
Markov Decision Process
33%
Open Problem
33%
Transition Probability
33%
Posterior Distribution
33%
Bayesian
33%
Sufficient Condition
33%
Cartesian Product
33%
Probability Distribution
33%
Cross-Validation
16%
Kullback-Leibler Divergence
16%
Probability Inequality
16%
Shifted Sequence
16%
Upper Bound
16%
Loss Function
16%
Path Problem
16%
Minimizes
16%
Weaker Assumption
16%
