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Reviews: Tagger: Deep Unsupervised Perceptual Grouping

Neural Information Processing Systems

UPDATE: I thank the authors for their convincing rebuttal, and in view of the promised updates on the technical specifications and description of the method, I increased the scores for "Technical quality" and "Clarity and presentation". My only major concern I still have is the lack of a suitable baseline to compare with. In particular, I do not agree that a comparison to [1] is impossible without their code. Instead, I'd encourage the authors to compare their method on the multi-MNIST benchmark described in Figure 1 [1] (and to just use the numbers provided by [1] for comparison without re-simulation). This would significantly strengthen the results. Unfortunately, however, I see two major flaws with the current presentation of the material: ** Literature and comparison to competitors First, the literature on this topic seems not to be suitably accounted for.



Review of The Rise of the Expert Company

Chalmers, Robert A.

AI Magazine

The authors of this book, Edward A. Feigenbaum, Pamela McCorduck, and H. Penny Nii, have given us an absorbing collection of tales about the successful integration of expert systems into mainstream industry.


Review of Computer Experience and Cognitive Development

Selfridge, Mallory

AI Magazine

It is important material, but it by a main text that consists mostly of belongs earlier in the book. I feel the Robert A. Chalmers engaging narratives about how some lack of a strong positive closing, the The authors of The Rise


Review of Perceptrons

Grossberg, Stephen

AI Magazine

It is important material, but it by a main text that consists mostly of belongs earlier in the book. I feel the Robert A. Chalmers engaging narratives about how some lack of a strong positive closing, the The authors of The Rise