First provide a summary of the paper, and then address the following criteria: Quality, clarity, originality and significance. Review for Exponential Concentration of a Density Functional Estimator This paper derives an exponential concentration inequality for a plug-in estimator of a class of integral functionals of one or more continuous probability densities, which includes entropy, divergence, mutual information, and others. From the concentration inequality and an analysis of the bias, mean squared error convergence rates of the estimator are derived. It is then shown how the concentration inequality can be used to find bounds on the error of an estimator for conditional mutual information. This work could be significant in that the results can be applied to a large class of integral functionals of probability densities.

First provide a summary of the paper, and then address the following criteria: Quality, clarity, originality and significance. In this article, the authors propose a framework for performing model comparison of Bayesian models on behavioral data. To do so, they summarize the Bayesian Decision Theory framework, pinpoint areas of non-identifiability, and outline the types of constraints that can be used to make each term in the Bayesian framework identifiable. They then make assumptions to constrain each term in the Bayesian framework, explore how differentiable parameter values are in their model, and apply the technique to two studies that use Bayesian decision theory to explain behavioral responses: time interval estimation and motion perception. Issues of identifiability of internal representations and processes have been prominent issues within cognitive science and psychology for decades.

First provide a summary of the paper, and then address the following criteria: Quality, clarity, originality and significance. SUMMARY This paper proposes a nuclear norm penalized estimator for matrix completion problem, where the observations take a finite (discrete) number of values. Both with theoretical analysis and with numerical experiment, the authors verify the proposed approach is effective. I understand that there are cases where the observations are discrete and that we may need a distinguished algorithm for them, the recommendation systems may not be a good example. Although most recommender system datasets allow finite number of possible ratings (usually 1 to 5 stars), the output does not need to be finite.

First provide a summary of the paper, and then address the following criteria: Quality, clarity, originality and significance. This paper proposes a method to recover signals from compressive measurements. The method consists of jointly estimating the signal and a Gaussian Mixture Model (GMM) capable of representing it succinctly. The main contribution of the paper is the idea of imposing a sparse structure on the GMM adapted to the case when the signal of interest corresponds to image patches. This is further exploited by a more structured prior that promotes an appropriate group-sparsity pattern (essentially interactions between adjoining pixels are not penalized by the sparsity-inducing penalty).

First provide a summary of the paper, and then address the following criteria: Quality, clarity, originality and significance. Q2: Please summarize your review in 1-2 sentences very nice, could become new standard, provided some guidance on choosing b is provided, and demonstration that performance is robust to this choice of b, and accuracy is not so much worse than cross-validation. First provide a summary of the paper, and then address the following criteria: Quality, clarity, originality and significance. The authors propose a novel bias-corrected estimator of covariance matrices for autocorrelated data. They provide simulated data as well as a real-world data set on brain-computer interfacing to demonstrate the superior performance of their estimator in comparison to a standard-, a shrinkage-, and the Sancetta estimator.

This paper investigates evaluation of learned multiagent strategies given noisy game outcomes.

These algorithms are typically employed in settings where the number of players and the type of interaction (competitive, cooperative, etc.) are both

First provide a summary of the paper, and then address the following criteria: Quality, clarity, originality and significance. The paper introduces a theoretical framework which combines both dynamic and correlated topic models. The proposed approach is based on a latent factor model. The authors provide an interesting discussion on admixture models (traditional topic models) versus factor models. One of the main advantages of the chosen approach is the ability to model both positive topic usage and negative topic usage.

First provide a summary of the paper, and then address the following criteria: Quality, clarity, originality and significance. This paper considers the estimation of an unknown vector v0 from noisy quadratic observations and some additional information regarding v0. Specifically, it considers that the unknown vector v0 is from a convex cone. It rigorously shows that the resulting optimization problem is tractable. Note that the resulting optimization problem in Eq.(3) is non-convex.