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11/18/2021
You Only Sample (Almost) Once: Linear Cost Self-Attention Via Bernoulli Sampling
Transformer-based models are widely used in natural language processing ...
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10/29/2021
Domain Agnostic Few-Shot Learning For Document Intelligence
Few-shot learning aims to generalize to novel classes with only a few sa...
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06/25/2021
Efficient Document Image Classification Using Region-Based Graph Neural Network
Document image classification remains a popular research area because it...
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06/01/2021
Weighting vectors for machine learning: numerical harmonic analysis applied to boundary detection
Metric space magnitude, an active field of research in algebraic topolog...
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02/07/2021
Nyströmformer: A Nyström-Based Algorithm for Approximating Self-Attention
Transformers have emerged as a powerful tool for a broad range of natura...
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01/31/2021
A Simple yet Brisk and Efficient Active Learning Platform for Text Classification
In this work, we propose the use of a fully managed machine learning ser...
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01/31/2021
Graph Neural Networks to Predict Customer Satisfaction Following Interactions with a Corporate Call Center
Customer satisfaction is an important factor in creating and maintaining...
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12/30/2020
SGD Distributional Dynamics of Three Layer Neural Networks
With the rise of big data analytics, multi-layer neural networks have su...
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06/24/2020
Practical applications of metric space magnitude and weighting vectors
Metric space magnitude, an active subject of research in algebraic topol...
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11/08/2018
Ordinal Regression using Noisy Pairwise Comparisons for Body Mass Index Range Estimation
Ordinal regression aims to classify instances into ordinal categories. I...
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03/15/2012