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05/09/2023
Comparing Foundation Models using Data Kernels
Recent advances in self-supervised learning and neural network scaling h...
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02/27/2023
Approximately optimal domain adaptation with Fisher's Linear Discriminant Analysis
We propose a class of models based on Fisher's Linear Discriminant (FLD)...
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05/28/2022
Deep Learning with Label Noise: A Hierarchical Approach
Deep neural networks are susceptible to label noise. Existing methods to...
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02/25/2022
Mental State Classification Using Multi-graph Features
We consider the problem of extracting features from passive, multi-chann...
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09/29/2021
Towards a theory of out-of-distribution learning
What is learning? 20^st century formalizations of learning theory – whic...
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06/23/2021
Leveraging semantically similar queries for ranking via combining representations
In modern ranking problems, different and disparate representations of t...
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02/20/2021
Inducing a hierarchy for multi-class classification problems
In applications where categorical labels follow a natural hierarchy, cla...
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01/29/2021
Subgraph nomination: Query by Example Subgraph Retrieval in Networks
This paper introduces the subgraph nomination inference task, in which e...
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11/12/2020
A partition-based similarity for classification distributions
Herein we define a measure of similarity between classification distribu...
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08/21/2020
Correcting a Nonparametric Two-sample Graph Hypothesis Test for Graphs with Different Numbers of Vertices
Random graphs are statistical models that have many applications, rangin...
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05/20/2020
Learning to rank via combining representations
Learning to rank – producing a ranked list of items specific to a query ...
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04/27/2020
A general approach to progressive intelligence
In biological learning, data is used to improve performance on the task ...
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04/27/2020
