495 citations · 2.3k across the 36 of their papers we have counts for
9 papers · 1 filter
Repairing Systematic Outliers by Learning Clean Subspaces in VAEs
Simao Eduardo, Kai Xu, Alfredo Nazabal +1
Data cleaning often comprises outlier detection and data repair. Systematic errors result from nearly deterministic transformations that occur repeatedly in the data, e.g. specific…
HOUDINI: Lifelong Learning as Program Synthesis
Lazar Valkov, Dipak Chaudhari, Akash Srivastava +2
We present a neurosymbolic framework for the lifelong learning of algorithmic tasks that mix perception and procedural reasoning. Reusing high-level concepts across domains and lea…
Interpreting Deep Classifier by Visual Distillation of Dark Knowledge
Kai Xu, Dae Hoon Park, Chang Yi +1
Interpreting black box classifiers, such as deep networks, allows an analyst to validate a classifier before it is deployed in a high-stakes setting. A natural idea is to visualize…
Learning Continuous Semantic Representations of Symbolic Expressions
Miltiadis Allamanis, Pankajan Chanthirasegaran, Pushmeet Kohli +1
Combining abstract, symbolic reasoning with continuous neural reasoning is a grand challenge of representation learning. As a step in this direction, we propose a new architecture,…
A Convolutional Attention Network for Extreme Summarization of Source Code
Miltiadis Allamanis, Hao Peng, Charles Sutton
Attention mechanisms in neural networks have proved useful for problems in which the input and output do not have fixed dimension. Often there exist features that are locally trans…
Blending LSTMs into CNNs
Krzysztof J. Geras, Abdel-rahman Mohamed, Rich Caruana +6
We consider whether deep convolutional networks (CNNs) can represent decision functions with similar accuracy as recurrent networks such as LSTMs. First, we show that a deep CNN wi…