49 citations · 212 across the 14 of their papers we have counts for
27 papers
Neural-guided, Bidirectional Program Search for Abstraction and Reasoning
Simon Alford, Anshula Gandhi, Akshay Rangamani +6
One of the challenges facing artificial intelligence research today is designing systems capable of utilizing systematic reasoning to generalize to new tasks. The Abstraction and R…
Distribution of Classification Margins: Are All Data Equal?
Andrzej Banburski, Fernanda De La Torre, Nishka Pant +2
Recent theoretical results show that gradient descent on deep neural networks under exponential loss functions locally maximizes classification margin, which is equivalent to minim…
The Effects of Image Distribution and Task on Adversarial Robustness
Owen Kunhardt, Arturo Deza, Tomaso Poggio
In this paper, we propose an adaptation to the area under the curve (AUC) metric to measure the adversarial robustness of a model over a particular -interval (inter…
Explicit regularization and implicit bias in deep network classifiers trained with the square loss
Tomaso Poggio, Qianli Liao
Deep ReLU networks trained with the square loss have been observed to perform well in classification tasks. We provide here a theoretical justification based on analysis of the ass…
CUDA-Optimized real-time rendering of a Foveated Visual System
Elian Malkin, Arturo Deza, Tomaso Poggio
The spatially-varying field of the human visual system has recently received a resurgence of interest with the development of virtual reality (VR) and neural networks. The computat…
Biologically Inspired Mechanisms for Adversarial Robustness
Manish V. Reddy, Andrzej Banburski, Nishka Pant +1
A convolutional neural network strongly robust to adversarial perturbations at reasonable computational and performance cost has not yet been demonstrated. The primate visual ventr…