אירועים והרצאות בפקולטה למדעי המחשב ע"ש הנרי ומרילין טאוב

We extend the standard online worst-case model to accommodate past experience which is available to the online player in many practical scenarios. We do this by revealing a random sample of the adversarial input to the online player ahead of time. The online player competes with the expected optimal value on the part of the input that arrives online. Our model bridges between existing online stochastic models (e.g., items are drawn i.i.d. from a distribution) and the online worst-case model. We also extend in a similar manner (by revealing a sample) the online random-order model. We study the secretary problem and online matching problems in our new models. We also study the online facility location problem and obtain improved bounds in the standard random-order model.