Re "...how decomposing the polytope now allows it to be mapped?" If you meant "how does the decomposition help map the problem of computing an optimal correlated Re "I wasn't sure what I was supposed to take away from the experiments" As We'll take all of them into account. Re "broader impact" Thanks for the feedback, we agree with all your points. As you correctly recognized, we use the term "social welfare" to mean the sum of utilities of the players as is typical in the game The maximum payoff is 15. Gurobi is freely available for academic use, but we'll also mention the open-source We are definitely the first to compute optimal EFCE in it. We strongly disagree that " this paper just tells us that the work in Farina et al. [12] is Extending the construction by Farina et al. to handle the more general We strongly disagree with that.

First provide a summary of the paper, and then address the following criteria: Quality, clarity, originality and significance. This paper propose to use CNN to classify rhythms from EEG recordings. A dataset with 13 subjects is analyzed. Temporal and spatiotemporal (STFT) data representation are investigated. The paper is well written with a good review of the relevant literature.

First provide a summary of the paper, and then address the following criteria: Quality, clarity, originality and significance. The authors present a novel approach to learning to rank. In contrast to traditional approaches, the idea is to focus on the number of positive instances that are ranked before the first negative one. Following a large-margin approach leads to primal and dual representations. Compared to similar approaches, the complexity is only linear in the number of instances.

We distinguish two extremal regimes in terms of generalization behavior: "adaptive" and