"NIPS 2013 Neural Information Processing Systems December 5 - 10, Lake Tahoe, Nevada, USA",,, "Paper ID:","1011" "Title:","Distributed k-means and k-median clustering on general communication topologies" Reviews First provide a summary of the paper, and then address the following criteria: Quality, clarity, originality and significance. The paper provides provably efficient algorithms for performing k-means and k-median clustering in the distributed setting. The main focus of the paper is minimizing communication cost in the distributed network. Although, i am not very much aware of the literature, the paper seems to provide a very novel idea of distributed coresets that leads to clustering algorithms which provably improves the state of the art communication complexity significantly. Existing approaches only use the idea of approximating coresets by taking the union of local coresets.

However, we now trust that the reviewers are satisfied with the rigour and the correctness of the methodology and the proofs. Therefore, we can drop the proofs of lemmas 4.1 and 4.2 and make the proof of theorem 4.3 more concise so as to have space to expand the introduction to highlight the above points (explained in detail in section 3 below) and add a few words about the replica technique, and include a concluding section.

First provide a summary of the paper, and then address the following criteria: Quality, clarity, originality and significance. This paper presents an approach to exploit the local similarity structure for zero-shot or a few-shot problem. The idea is to not only use mid-level representation such as attributes which help in zero-shot problem but also ensure that the unlabeled data is labeled such that similar images receive similar label. Overall, I like the direction of the paper. I think exploiting graph structure is an interesting idea which hasn't been looked into the zero-shot problem (as far as I know).

First provide a summary of the paper, and then address the following criteria: Quality, clarity, originality and significance. The goal of this paper is to build a markov chain that will sample from a determinantal point process. One that mixes rapidly, and improves on the O(n^3) direct computation. One benefit is that as the set of elements in the DPP changes, there is no expensive eigenvalue decomposition. The fast algorithm is achieved with the realization that the algorithm doesn't require the computation of matrix determinants, but the ratio of determinants.

It should read "unions" of subspaces. Thank you for pointing out the typo.

First provide a summary of the paper, and then address the following criteria: Quality, clarity, originality and significance. The paper proposes to use random functions as an approximation to kernel functions and then proposes to do stochastic gradient descent. Convergence rates and generalisation bounds are derived. Experimental results on large datasets are presented. The idea of introducing random functions to approximate kernel functions and then using SGD is very interesting.

"NIPS Neural Information Processing Systems 8-11th December 2014, Montreal, Canada",,, "Paper ID:","592" "Title:","Inferring synaptic conductances from spike trains with a biophysically inspired point process model" Current Reviews First provide a summary of the paper, and then address the following criteria: Quality, clarity, originality and significance. The authors propose a conductance based spiking model (CBSM) that is more biophysically realistic than the currently popular generalized linear model (GLM). Furthermore, the authors present CBSM as a generalization of the GLM and propose a set of constraints that can reduce it to a GLM and a GLM variant that would be as adaptive as the CBSM. The proposed model is an interesting extension to current spiking models in that it is parametrized in a more descriptive way of the spiking process without sacrificing much of the mathematical convenience of the GLM. One thing that could raise some concerns stems from the last paragraph of page 6.

First provide a summary of the paper, and then address the following criteria: Quality, clarity, originality and significance. The paper proposes to use a deep convolutional neural network for denoising images by generating a lot of noisy and noiseless image pairs using a synthetic blurring process. The proposed method achieves good results on a number of image deblurring tasks. The idea is simple and elegant. It is observed that a 2D deconvolution, which is an inverse of the convolution operator, is itself a 2D convolution operator, albeit with a very large support.

Interesting method that will undoubtedly find an audience. Current application limited, but likely to extend to other, more general cases. Reasonably well written, though could be improved.

First provide a summary of the paper, and then address the following criteria: Quality, clarity, originality and significance. This is a very well-written paper that explores the use of weighted importance sampling to speed up learning in off-policy LSTD-type algorithms. The theoretical results are solid and what one would expect. The computational results are striking. The technique could serve as a useful component in design of RL algorithms. Q2: Please summarize your review in 1-2 sentences The paper is very well-written and presents a useful idea validated by striking computational results.