Search Results for author:
Found 4 papers, 3 papers with code
On the Measure of Intelligence
To make deliberate progress towards more intelligent and more human-like artificial systems, we need to be following an appropriate feedback signal: we need to be able to define and evaluate intelligence in a way that enables comparisons between two systems, as well as comparisons with humans.
HolStep: A Machine Learning Dataset for Higher-order Logic Theorem Proving
We propose various machine learning tasks that can be performed on this dataset, and discuss their significance for theorem proving.
Ranked #3 on
Automated Theorem Proving
on HolStep (Unconditional)
Xception: Deep Learning with Depthwise Separable Convolutions
We present an interpretation of Inception modules in convolutional neural networks as being an intermediate step in-between regular convolution and the depthwise separable convolution operation (a depthwise convolution followed by a pointwise convolution).
Ranked #5 on
Classification
on InDL
Information-theoretical label embeddings for large-scale image classification
We present a method for training multi-label, massively multi-class image classification models, that is faster and more accurate than supervision via a sigmoid cross-entropy loss (logistic regression).
