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The Language of Fake News: Opening the Black-Box of Deep Learning Based Detectors
(Center for Brains, Minds and Machines (CBMM), 2018-11-01)
The digital information age has generated new outlets for content creators to publish so-called “fake news”, a new form of propaganda that is intentionally designed to mislead the reader. With the widespread effects of the ...
On the Forgetting of College Academice: at "Ebbinghaus Speed"?
(Center for Brains, Minds and Machines (CBMM), 2017-06-20)
How important are Undergraduate College Academics after graduation? How much do we actually remember after we leave the college classroom, and for how long? Taking a look at major University ranking methodologies one can ...
Streaming Normalization: Towards Simpler and More Biologically-plausible Normalizations for Online and Recurrent Learning
(Center for Brains, Minds and Machines (CBMM), arXiv, 2016-10-19)
We systematically explored a spectrum of normalization algorithms related to Batch Normalization (BN) and propose a generalized formulation that simultaneously solves two major limitations of BN: (1) online learning and ...
Foveation-based Mechanisms Alleviate Adversarial Examples
(Center for Brains, Minds and Machines (CBMM), arXiv, 2016-01-19)
We show that adversarial examples, i.e., the visually imperceptible perturbations that result in Convolutional Neural Networks (CNNs) fail, can be alleviated with a mechanism based on foveations---applying the CNN in ...
Theory IIIb: Generalization in Deep Networks
(Center for Brains, Minds and Machines (CBMM), arXiv.org, 2018-06-29)
The general features of the optimization problem for the case of overparametrized nonlinear networks have been clear for a while: SGD selects with high probability global minima vs local minima. In the overparametrized ...
Anchoring and Agreement in Syntactic Annotations
(Center for Brains, Minds and Machines (CBMM), arXiv, 2016-09-21)
Published in the Proceedings of EMNLP 2016
We present a study on two key characteristics of human syntactic annotations: anchoring and agreement. Anchoring is a well-known cognitive bias in human decision making, where ...
Classical generalization bounds are surprisingly tight for Deep Networks
(Center for Brains, Minds and Machines (CBMM), 2018-07-11)
Deep networks are usually trained and tested in a regime in which the training classification error is not a good predictor of the test error. Thus the consensus has been that generalization, defined as convergence of the ...
Universal Metaphysics
(2019-12-31)
The development of natural science especially physics allows us to understand to a large extent the material world. However, the world also contains a large amount of concepts that are non-material and abstract, which are ...
Understanding the Role of Recurrent Connections in Assembly Calculus
(Center for Brains, Minds and Machines (CBMM), 2022-07-06)
In this note, we explore the role of recurrent connections in Assembly Calculus through a number of experiments conducted on models with and without recurrent connections. We observe that as- semblies can be formed even ...
Computational role of eccentricity dependent cortical magnification
(Center for Brains, Minds and Machines (CBMM), arXiv, 2014-06-06)
We develop a sampling extension of M-theory focused on invariance to scale and translation. Quite surprisingly, the theory predicts an architecture of early vision with increasing receptive field sizes and a high resolution ...