G : Bandits , Experts and Games 09 / 12 / 16 Lecture 4 : Lower Bounds ( ending ) ; Thompson Sampling

اسناد مشابه

• G : Bandits , Experts and Games 09 / 19 / 16 Lecture 3 : Lower Bounds for Bandit Algorithms

  سند علمی۲۰۱۶Alex Slivkins, Karthik A Sankararaman

  Note that (2) implies (1) since: if regret is high in expectation over problem instances, then there exists at least one problem instance with high regret. Also, (1) implies (2) if |F| is a constant. This can be seen as follows: suppose we know that for any algorithm we have high

• G : Bandits , Experts and Games 09 / 12 / 16 Lecture 2 : Multi - arm Bandits with i . i . d Rewards

  سند علمی۲۰۱۶Amr Sharaf, Liqian Zhang

  In the multi-arm bandit problem with iid rewards, the learner selects an arm a ∈ A at every time step t. Learning proceeds in rounds, and we assume that the number of rounds is fixed, and indexed by t = 1 · · ·T . At each round, the algorithm chooses one action at (we’ll use the

• G : Bandits , Experts and Games 10 / 10 / 16 Lecture 6 : Lipschitz Bandits

  سند علمی۲۰۱۶Alex Slivkins, Shuo Li, Sheng Yang

  Motivation: similarity between arms. In various bandit problems, we may have information on similarity between arms, in the sense that ‘similar’ arms have similar expected rewards. For example, arms can correspond to “items” (e.g., documents) with feature vectors, and similarity

• G : Bandits , Experts and Games 11 / 07 / 16 Lecture 10 : Contextual Bandits

  سند علمی۲۰۱۷Alex Slivkins, Guowei Sun, Cheng Jie

  • algorithm observes a “context” xt, • algorithm picks an arm at, • reward rt ∈ [0, 1] is realized. The reward rt depends both on the context xt and the chosen action at. Formally, make the IID assumption: rt is drawn independently from some distribution that depends on the (xt,

• Complexity ( for Algorithm Designers ) Lecture # 8 : Lower Bounds in Algorithmic Game Theory ∗

  سند علمی۲۰۱۵Tim Roughgarden

  This lecture explains some applications of communication complexity to proving lower bounds in algorithmic game theory (AGT), at the border of computer science and economics. There are a number of situations in AGT where the natural description size of an object is exponential a

• Complexity ( for Algorithm Designers ) Lecture # 7 : Lower Bounds in Algorithmic Game Theory ∗

  سند علمی۲۰۱۵Tim Roughgarden

  This lecture explains some applications of communication complexity to proving lower bounds in algorithmic game theory (AGT), at the border of computer science and economics. In AGT, the natural description size of an object is often exponential in a parameter of interest, and th