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02/14/2020
Generalization and Representational Limits of Graph Neural Networks
We address two fundamental questions about graph neural networks (GNNs)....
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02/13/2020
Learn to Expect the Unexpected: Probably Approximately Correct Domain Generalization
Domain generalization is the problem of machine learning when the traini...
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08/27/2019
Multiresolution Transformer Networks: Recurrence is Not Essential for Modeling Hierarchical Structure
The architecture of Transformer is based entirely on self-attention, and...
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05/29/2019
Strategic Prediction with Latent Aggregative Games
We introduce a new class of context dependent, incomplete information ga...
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05/29/2019
Solving graph compression via optimal transport
We propose a new approach to graph compression by appeal to optimal tran...
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10/16/2018
Peek Search: Near-Optimal Online Markov Decoding
We resolve the fundamental problem of online decoding with ergodic Marko...
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03/06/2018
Learning SMaLL Predictors
We present a new machine learning technique for training small resource-...
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09/14/2017
Supervising Unsupervised Learning
We introduce a framework to leverage knowledge acquired from a repositor...
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12/29/2016
Meta-Unsupervised-Learning: A supervised approach to unsupervised learning
We introduce a new paradigm to investigate unsupervised learning, reduci...
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06/25/2015
CRAFT: ClusteR-specific Assorted Feature selecTion
We present a framework for clustering with cluster-specific feature sele...
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04/19/2015